From 311d4b71e2f6668c04ce3864a7e5ae5f5f2fc3f2 Mon Sep 17 00:00:00 2001
From: shi chuang <709010312@qq.com>
Date: Thu, 16 Jul 2026 00:02:55 +0800
Subject: [PATCH 1/3] feat: complete Simplified Chinese localization

---
 CHANGELOG.md                                  |   2 +
 README.md                                     |   2 +-
 frontend/dashboard/src/App.tsx                |   6 +-
 .../src/app/DocumentLocalizationBridge.tsx    | 151 ++++
 frontend/dashboard/src/app/i18n.ts            |  69 ++
 .../src/app/zh-Hans/advancedPages.ts          | 468 +++++++++++
 frontend/dashboard/src/app/zh-Hans/common.ts  | 269 ++++++
 .../dashboard/src/app/zh-Hans/corePages.ts    | 730 +++++++++++++++++
 .../src/app/zh-Hans/diagnosticsReports.ts     | 773 ++++++++++++++++++
 .../src/app/zh-Hans/translate.test.ts         |  95 +++
 .../dashboard/src/app/zh-Hans/translate.ts    |  86 ++
 frontend/dashboard/src/app/zh-Hans/types.ts   |   4 +
 frontend/dashboard/src/charts/LineChart.tsx   |   8 +-
 .../dashboard/src/components/DataTable.tsx    |  60 +-
 .../dashboard/src/components/MetricCard.tsx   |  12 +-
 frontend/dashboard/src/components/Panel.tsx   |   6 +-
 .../dashboard/src/components/StatusBadge.tsx  |   4 +-
 .../dashboard/src/design/PageLoadProgress.tsx |  22 +-
 .../src/design/primitives/Primitives.tsx      |  50 +-
 .../cache-context/CacheContextPage.tsx        |  15 +-
 .../callInvestigatorReadout.test.ts           |   1 +
 .../src/features/calls/CallsExplorerView.tsx  |   6 +-
 .../diagnostics/DiagnosticSnapshotMatrix.tsx  |  10 +-
 .../src/features/explore/EvidenceGrid.tsx     |  28 +-
 .../investigator/InvestigatorPage.tsx         |  22 +-
 .../src/features/limits/LimitsPage.tsx        |   4 +-
 .../features/overview/OverviewRecentCalls.tsx |   8 +-
 .../src/features/reports/ReportsPage.tsx      |   4 +-
 .../dashboard/src/features/shared/tables.tsx  |  15 +-
 .../src/features/threads/ThreadInspector.tsx  |  29 +-
 .../features/threads/ThreadsExplorerView.tsx  |  10 +-
 .../src/visualization/react/Visualization.tsx |  74 +-
 .../react/VisualizationState.tsx              |   6 +-
 .../react/VisualizationTable.tsx              |   4 +-
 .../react/localizeVisualizationSpec.test.ts   |  78 ++
 .../react/localizeVisualizationSpec.ts        | 153 ++++
 .../src/visualization/renderer/modelShared.ts |   2 +-
 .../src/visualization/spec/accessibility.ts   |  13 +-
 .../dashboard/src/visualization/spec/types.ts |   1 +
 .../cli/commands_lifecycle.py                 |  61 +-
 src/codex_usage_tracker/cli/dashboard.py      |  12 +-
 src/codex_usage_tracker/cli/help_i18n.py      | 170 ++++
 src/codex_usage_tracker/cli/main.py           |   9 +-
 src/codex_usage_tracker/cli/parser.py         |   7 +-
 .../dashboard/locales/zh-Hans.json            | 306 +++----
 .../plugin_data/dashboard/react/assets/App.js |  56 +-
 .../react/assets/CacheContextPage.js          |   2 +-
 .../dashboard/react/assets/CallsPage.js       |   2 +-
 .../dashboard/react/assets/DataTable.js       |   6 +-
 .../dashboard/react/assets/DiagnosticsPage.js |   2 +-
 .../dashboard/react/assets/EvidenceGrid.js    |   4 +-
 .../react/assets/ExploreWorkspaceSwitcher.js  |   2 +-
 .../react/assets/InvestigatorPage.js          |   6 +-
 .../dashboard/react/assets/LineChart.js       |   2 +-
 .../dashboard/react/assets/OverviewPage.js    |   2 +-
 .../react/assets/PageLoadProgress.js          |   2 +-
 .../dashboard/react/assets/Panel.js           |   2 +-
 .../dashboard/react/assets/Primitives.js      |   2 +-
 .../dashboard/react/assets/ReportsPage.js     |   2 +-
 .../dashboard/react/assets/ThreadsPage.js     |   4 +-
 .../react/assets/UsageConstellation.js        |   6 +-
 .../dashboard/react/assets/UsageDrainPage.js  |   2 +-
 .../dashboard/react/assets/overviewQueries.js |   4 +-
 .../dashboard/react/assets/runtime.js         |   2 +-
 src/codex_usage_tracker/server/api.py         |  27 +-
 tests/cli/test_cli_help_i18n.py               |  38 +
 tests/server/test_server_api.py               |  28 +-
 67 files changed, 3671 insertions(+), 397 deletions(-)
 create mode 100644 frontend/dashboard/src/app/DocumentLocalizationBridge.tsx
 create mode 100644 frontend/dashboard/src/app/zh-Hans/advancedPages.ts
 create mode 100644 frontend/dashboard/src/app/zh-Hans/common.ts
 create mode 100644 frontend/dashboard/src/app/zh-Hans/corePages.ts
 create mode 100644 frontend/dashboard/src/app/zh-Hans/diagnosticsReports.ts
 create mode 100644 frontend/dashboard/src/app/zh-Hans/translate.test.ts
 create mode 100644 frontend/dashboard/src/app/zh-Hans/translate.ts
 create mode 100644 frontend/dashboard/src/app/zh-Hans/types.ts
 create mode 100644 frontend/dashboard/src/visualization/react/localizeVisualizationSpec.test.ts
 create mode 100644 frontend/dashboard/src/visualization/react/localizeVisualizationSpec.ts
 create mode 100644 src/codex_usage_tracker/cli/help_i18n.py
 create mode 100644 tests/cli/test_cli_help_i18n.py

diff --git a/CHANGELOG.md b/CHANGELOG.md
index faf9ee5f..043e54cb 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -2,6 +2,8 @@
 
 ## Unreleased
 
+- Complete the Simplified Chinese dashboard experience across React views, visualization metadata, tables, accessibility text, CLI help, and dashboard lifecycle messages while preserving user-provided data verbatim.
+
 ## 0.18.0 - 2026-07-15
 
 - Exclude exact historical calls copied by cloned Codex tasks from default dashboard, CLI, MCP, report, allowance, compression, recommendation, and export totals while retaining every physical source row for local provenance.
diff --git a/README.md b/README.md
index 158fdacc..1b2c17ca 100644
--- a/README.md
+++ b/README.md
@@ -214,7 +214,7 @@ CODEX_USAGE_TRACKER_LANG=vi codex-usage-tracker serve-dashboard --open
 
 The dashboard also includes a language selector. Browser selections are stored locally and can override the generated default for that browser.
 
-Supported dashboard locales include English, Vietnamese, Spanish, French, German, Portuguese, Japanese, Simplified Chinese, Korean, Russian, Italian, and Arabic. This localizes dashboard UI text, not raw Codex log content, thread names, project names, paths, full CLI output, or data exports.
+Supported dashboard locales include English, Vietnamese, Spanish, French, German, Portuguese, Japanese, Simplified Chinese, Korean, Russian, Italian, and Arabic. Simplified Chinese also localizes CLI help and dashboard lifecycle messages. Localization never rewrites raw Codex log content, thread names, project names, paths, or data exports.
 
 ### Adding A Dashboard Language
 
diff --git a/frontend/dashboard/src/App.tsx b/frontend/dashboard/src/App.tsx
index dbdccf45..1e6ff831 100644
--- a/frontend/dashboard/src/App.tsx
+++ b/frontend/dashboard/src/App.tsx
@@ -6,6 +6,7 @@ import { errorMessage, refreshProgressLabel, type RefreshOptions } from './app/d
 import { historyScopeFromPayload, historyScopeStatusLabel } from './app/historyScope';
 import { createShellI18n, initialDashboardLanguage, storeDashboardLanguage } from './app/i18n';
 import { ShellI18nProvider } from './app/i18nContext';
+import { DocumentLocalizationBridge } from './app/DocumentLocalizationBridge';
 import { modelWithLegacyShellFilters } from './app/legacyShellFilters';
 import { navItems, secondaryNavItems, type ViewId } from './app/navigation';
 import { RowLimitControl } from './app/RowLimitControl';
@@ -526,7 +527,8 @@ function clearInvestigationPreset() {
 
   return (
     <ShellI18nProvider value={shellI18n}>
-      <div className="app-shell">
+      <DocumentLocalizationBridge />
+      <div className="app-shell" data-dashboard-localization-root>
       <aside className="sidebar">
         <div className="brand">
           <div className="brand-mark">
@@ -597,7 +599,7 @@ placeholder={shellI18n.t('filter.search_placeholder', 'Search calls, threads, mo
 {shellI18n.languages.length > 1 ? (
 <label className="topbar-select">
 <span>{shellI18n.t('language.label', 'Language')}</span>
-<select aria-label={shellI18n.t('language.label', 'Language')} value={shellI18n.language} onChange={event => handleLanguageChange(event.target.value)}>
+<select data-localization-skip="true" aria-label={shellI18n.t('language.label', 'Language')} value={shellI18n.language} onChange={event => handleLanguageChange(event.target.value)}>
 {shellI18n.languages.map(languageOption => (
 <option key={languageOption.code} value={languageOption.code}>
 {languageOption.native_name || languageOption.english_name || languageOption.code}
diff --git a/frontend/dashboard/src/app/DocumentLocalizationBridge.tsx b/frontend/dashboard/src/app/DocumentLocalizationBridge.tsx
new file mode 100644
index 00000000..7f51845a
--- /dev/null
+++ b/frontend/dashboard/src/app/DocumentLocalizationBridge.tsx
@@ -0,0 +1,151 @@
+import { useLayoutEffect } from 'react';
+
+import { useShellI18n } from './i18nContext';
+
+const translatedAttributes = ['aria-description', 'aria-label', 'aria-valuetext', 'title', 'placeholder', 'alt'] as const;
+const skippedElementNames = new Set(['CODE', 'KBD', 'PRE', 'SAMP', 'SCRIPT', 'STYLE', 'TEXTAREA']);
+
+type TextTranslationRecord = { source: string; translated: string };
+type AttributeTranslationRecord = { source: string; translated: string };
+
+const textTranslations = new WeakMap<Text, TextTranslationRecord>();
+const attributeTranslations = new WeakMap<Element, Map<string, AttributeTranslationRecord>>();
+
+export function DocumentLocalizationBridge() {
+  const i18n = useShellI18n();
+
+  useLayoutEffect(() => {
+    const root = document.querySelector<HTMLElement>('[data-dashboard-localization-root]');
+    if (!root) return undefined;
+
+    if (i18n.language !== 'zh-Hans') {
+      restoreTree(root);
+      document.title = 'Codex Usage Tracker React Dashboard';
+      return undefined;
+    }
+
+    document.title = 'Codex Usage Tracker · 用量仪表盘';
+    localizeTree(root, i18n.translateText);
+    const observer = new MutationObserver(records => {
+      for (const record of records) {
+        if (record.type === 'characterData' && record.target instanceof Text) {
+          localizeTextNode(record.target, i18n.translateText);
+          continue;
+        }
+        if (record.type === 'attributes' && record.target instanceof Element) {
+          localizeElementAttributes(record.target, i18n.translateText);
+          continue;
+        }
+        for (const node of record.addedNodes) {
+          if (node instanceof Text) {
+            localizeTextNode(node, i18n.translateText);
+          } else if (node instanceof Element) {
+            localizeTree(node, i18n.translateText);
+          }
+        }
+      }
+    });
+    observer.observe(root, {
+      attributes: true,
+      attributeFilter: [...translatedAttributes],
+      characterData: true,
+      childList: true,
+      subtree: true,
+    });
+    return () => observer.disconnect();
+  }, [i18n]);
+
+  return null;
+}
+
+function localizeTree(root: Element, translate: (value: string) => string) {
+  if (shouldSkipElement(root)) return;
+  localizeElementAttributes(root, translate);
+  const walker = document.createTreeWalker(root, NodeFilter.SHOW_ELEMENT | NodeFilter.SHOW_TEXT);
+  let node = walker.nextNode();
+  while (node) {
+    if (node instanceof Element) {
+      if (shouldSkipElement(node)) {
+        node = nextNodeAfterSubtree(walker, node, root);
+        continue;
+      }
+      localizeElementAttributes(node, translate);
+    } else if (node instanceof Text) {
+      localizeTextNode(node, translate);
+    }
+    node = walker.nextNode();
+  }
+}
+
+function nextNodeAfterSubtree(walker: TreeWalker, element: Element, root: Element): Node | null {
+  let current: Node | null = element;
+  while (current && current !== root) {
+    const sibling = walker.nextSibling();
+    if (sibling) return sibling;
+    current = current.parentNode;
+    if (current) walker.currentNode = current;
+  }
+  return null;
+}
+
+function localizeTextNode(node: Text, translate: (value: string) => string) {
+  const parent = node.parentElement;
+  if (!parent || shouldSkipElement(parent)) return;
+  const current = node.nodeValue ?? '';
+  const previous = textTranslations.get(node);
+  const source = previous && (current === previous.source || current === previous.translated)
+    ? previous.source
+    : current;
+  const match = source.match(/^(\s*)([\s\S]*?)(\s*)$/u);
+  if (!match || !match[2]) return;
+  const translatedCore = translate(match[2]);
+  const translated = `${match[1]}${translatedCore}${match[3]}`;
+  textTranslations.set(node, { source, translated });
+  if (translated !== current) node.nodeValue = translated;
+}
+
+function localizeElementAttributes(element: Element, translate: (value: string) => string) {
+  if (shouldSkipElement(element)) return;
+  const records = attributeTranslations.get(element) ?? new Map<string, AttributeTranslationRecord>();
+  for (const attribute of translatedAttributes) {
+    const current = element.getAttribute(attribute);
+    if (!current) continue;
+    const previous = records.get(attribute);
+    const source = previous && (current === previous.source || current === previous.translated)
+      ? previous.source
+      : current;
+    const translated = translate(source);
+    records.set(attribute, { source, translated });
+    if (translated !== current) element.setAttribute(attribute, translated);
+  }
+  if (records.size) attributeTranslations.set(element, records);
+}
+
+function restoreTree(root: Element) {
+  const walker = document.createTreeWalker(root, NodeFilter.SHOW_ELEMENT | NodeFilter.SHOW_TEXT);
+  restoreElementAttributes(root);
+  let node = walker.nextNode();
+  while (node) {
+    if (node instanceof Text) {
+      const record = textTranslations.get(node);
+      if (record && node.nodeValue === record.translated) node.nodeValue = record.source;
+    } else if (node instanceof Element) {
+      restoreElementAttributes(node);
+    }
+    node = walker.nextNode();
+  }
+}
+
+function restoreElementAttributes(element: Element) {
+  const records = attributeTranslations.get(element);
+  if (!records) return;
+  for (const [attribute, record] of records) {
+    if (element.getAttribute(attribute) === record.translated) {
+      element.setAttribute(attribute, record.source);
+    }
+  }
+}
+
+function shouldSkipElement(element: Element): boolean {
+  return skippedElementNames.has(element.tagName) || Boolean(element.closest('[data-localization-skip="true"]'));
+}
diff --git a/frontend/dashboard/src/app/i18n.ts b/frontend/dashboard/src/app/i18n.ts
index 9b148456..8a109a67 100644
--- a/frontend/dashboard/src/app/i18n.ts
+++ b/frontend/dashboard/src/app/i18n.ts
@@ -1,5 +1,9 @@
 import type { DashboardBootPayload, DashboardLanguage } from '../api/types';
 import type { ViewId } from './navigation';
+import {
+  translateZhHansUiText,
+  type CatalogTemplateTranslation,
+} from './zh-Hans/translate';
 
 const languageStorageKey = 'codex-usage-dashboard-language';
 
@@ -57,6 +61,7 @@ export type ShellI18n = {
   direction: 'ltr' | 'rtl';
   languages: DashboardLanguage[];
   t: (key: string, fallback?: string) => string;
+  translateText: (value: string) => string;
   navLabel: (view: ViewId, fallback: string) => string;
 };
 
@@ -72,6 +77,14 @@ export function createShellI18n(payload: DashboardBootPayload | null, language:
     ...englishTranslations,
     ...selectedTranslations,
   };
+  const catalogLiteralTranslations = buildCatalogLiteralTranslations(
+    englishTranslations,
+    selectedTranslations,
+  );
+  const catalogTemplateTranslations = buildCatalogTemplateTranslations(
+    englishTranslations,
+    selectedTranslations,
+  );
   const languageMeta = languages.find(entry => entry.code === normalized);
   const direction = languageMeta?.dir === 'rtl' || (!languageMeta && payload?.language_direction === 'rtl') ? 'rtl' : 'ltr';
   return {
@@ -79,6 +92,16 @@ export function createShellI18n(payload: DashboardBootPayload | null, language:
     direction,
     languages,
     t: (key, fallback) => translations[key] ?? fallback ?? key,
+    translateText: value => {
+      if (normalized === 'zh-Hans') {
+        return translateZhHansUiText(
+          value,
+          catalogLiteralTranslations,
+          catalogTemplateTranslations,
+        );
+      }
+      return catalogLiteralTranslations.get(value) ?? value;
+    },
     navLabel: (view, fallback) => {
       const key = navTranslationKeys[view];
       return key ? translations[key] ?? fallback : fallback;
@@ -86,6 +109,52 @@ export function createShellI18n(payload: DashboardBootPayload | null, language:
   };
 }
 
+function buildCatalogTemplateTranslations(
+  englishTranslations: Record<string, string>,
+  selectedTranslations: Record<string, string>,
+): ReadonlyArray<CatalogTemplateTranslation> {
+  const templates: CatalogTemplateTranslation[] = [];
+  for (const [key, englishValue] of Object.entries(englishTranslations)) {
+    const selectedValue = selectedTranslations[key];
+    if (!selectedValue || selectedValue === englishValue || !englishValue.includes('{')) continue;
+    const placeholders: string[] = [];
+    const patternParts: string[] = [];
+    let cursor = 0;
+    for (const match of englishValue.matchAll(/\{([A-Za-z][A-Za-z0-9_]*)\}/gu)) {
+      const index = match.index ?? cursor;
+      patternParts.push(escapeRegularExpression(englishValue.slice(cursor, index)));
+      patternParts.push('(.+?)');
+      placeholders.push(match[1]);
+      cursor = index + match[0].length;
+    }
+    patternParts.push(escapeRegularExpression(englishValue.slice(cursor)));
+    templates.push({
+      pattern: new RegExp(`^${patternParts.join('')}$`, 'u'),
+      placeholders,
+      translatedTemplate: selectedValue,
+    });
+  }
+  return templates.sort((left, right) => right.translatedTemplate.length - left.translatedTemplate.length);
+}
+
+function escapeRegularExpression(value: string): string {
+  return value.replace(/[.*+?^${}()|[\]\\]/gu, '\\$&');
+}
+
+function buildCatalogLiteralTranslations(
+  englishTranslations: Record<string, string>,
+  selectedTranslations: Record<string, string>,
+): ReadonlyMap<string, string> {
+  const literals = new Map<string, string>();
+  for (const [key, englishValue] of Object.entries(englishTranslations)) {
+    const selectedValue = selectedTranslations[key];
+    if (selectedValue && selectedValue !== englishValue) {
+      literals.set(englishValue, selectedValue);
+    }
+  }
+  return literals;
+}
+
 function dashboardLanguages(payload: DashboardBootPayload | null): DashboardLanguage[] {
   const languages = payload?.available_languages?.filter(language => language.code) ?? [];
   return languages.length ? languages : [{ code: 'en', english_name: 'English', native_name: 'English', dir: 'ltr' }];
diff --git a/frontend/dashboard/src/app/zh-Hans/advancedPages.ts b/frontend/dashboard/src/app/zh-Hans/advancedPages.ts
new file mode 100644
index 00000000..30eacaf9
--- /dev/null
+++ b/frontend/dashboard/src/app/zh-Hans/advancedPages.ts
@@ -0,0 +1,468 @@
+import type { ZhHansPattern } from './types';
+
+export const advancedPagesZhHansTranslations: Readonly<Record<string, string>> = {
+  // Investigator workspace.
+  'Where is avoidable token waste concentrated?': '可避免的token浪费主要集中在哪里？',
+  'Stored diagnostics ready': '已存储的诊断数据已就绪',
+  'Refreshing investigation evidence...': '正在刷新调查证据…',
+  'Strict local evidence bundle exported': '已导出严格本地证据包',
+  'Refresh evidence': '刷新证据',
+  'Refreshing investigation evidence': '正在刷新调查证据',
+  'Loading investigation evidence': '正在加载调查证据',
+  'Live report services': '实时报告服务',
+  'Loaded aggregate fallback': '已加载的聚合回退数据',
+  'linked evidence rows': '关联证据记录',
+  'Content access enabled': '内容访问已启用',
+  'Content access off': '内容访问未启用',
+  'Testing': '正在检验',
+  'Test hypothesis': '检验假设',
+  'Enable in Settings': '在设置中启用',
+  'Local pattern': '本地模式',
+  'Linked rows': '关联记录',
+  'Impact signal': '影响信号',
+  'Ranking score': '排序评分',
+  'No investigation evidence is available for the loaded scope.': '已加载范围内没有可用的调查证据。',
+  'Root-cause workspace': '根因分析工作区',
+  'Ranked waste signals, linked evidence, and one explicit verification path.': '对浪费信号排序，关联证据，并提供一条明确的验证路径。',
+  'Export evidence': '导出证据',
+  'Selected finding': '所选发现',
+  'Ranked findings': '已排序发现',
+  'Confidence, scope, and evidence stay visible while comparing.': '比较时始终显示置信度、范围和证据。',
+  'Recommended change': '建议的改进',
+  'Deterministic action from the selected evidence family.': '根据所选证据类别给出的确定性操作。',
+  'Verify with': '验证依据',
+  'Missing access': '缺少的访问权限',
+  'Verify in call': '在调用中验证',
+  'Evidence ledger': '证据台账',
+  'Each supported row opens the underlying call or thread.': '每条有支撑的记录都可打开对应调用或线程。',
+  'Local hypothesis trace': '本地假设追踪',
+  'Bounded pattern exploration over the local content/event index.': '在本地内容/事件索引上进行有界模式探索。',
+  'Investigation question': '调查问题',
+  'Method and caveats': '方法与注意事项',
+  'No supported local pattern met the current threshold.': '没有达到当前阈值且有证据支持的本地模式。',
+  'Open call': '打开调用',
+  'Open thread': '打开线程',
+  'No linked record': '没有关联记录',
+  'Pattern': '模式',
+  'Events': '事件数',
+  'Tokens': 'token数',
+  'Evidence': '证据',
+  'Detail': '详情',
+  'Source': '来源',
+  'Open': '打开',
+  'This finding has no directly linked evidence rows at the current scope.': '当前范围内，此发现没有直接关联的证据记录。',
+  'Local Codex logs only; this is not an official OpenAI usage ledger.': '仅使用本地 Codex 日志；这不是 OpenAI 官方用量台账。',
+  'Static fallback findings use loaded aggregate rows and cannot identify shell or file rediscovery directly.': '静态回退发现仅使用已加载的聚合记录，无法直接识别 Shell 重复操作或文件重复查找。',
+  'Waste fingerprint matrix': '浪费特征矩阵',
+  'Recurring diagnostic patterns by thread or aggregate scope; darker cells carry more supporting events.': '按线程或聚合范围展示重复出现的诊断模式；颜色越深，支撑事件越多。',
+  'No diagnostic fingerprints are available for the current scope.': '当前范围内没有可用的诊断特征。',
+  'Event counts rank evidence volume, not guaranteed token savings.': '事件数只用于衡量证据量，并不保证可以节省相应token。',
+  'Use arrow keys to move between cells; use the synchronized table for exact values.': '使用方向键在单元格之间移动；精确数值请查看同步表格。',
+  'Waste fingerprints by thread and diagnostic family': '按线程和诊断类别展示浪费特征',
+  'Diagnostic family': '诊断类别',
+  'Supporting events': '支撑事件数',
+  'Finding': '发现',
+  'The local report found a repeatable aggregate signal worth reviewing.': '本地报告发现了值得检查的可重复聚合信号。',
+  'Inspect the strongest supporting evidence before changing the workflow.': '更改工作流前，请先检查最有力的支撑证据。',
+  'No additional access is required for the aggregate evidence.': '查看聚合证据无需额外访问权限。',
+  'No raw fragments are included.': '不包含原始片段。',
+  'Agentic investigation': '智能体调查',
+  'Supporting activity': '支撑活动',
+  'Stored diagnostic snapshot': '已存储的诊断快照',
+  'Outcome quality remains outside aggregate telemetry.': '聚合遥测无法判断结果质量。',
+  'Live diagnostics are unavailable in static mode.': '静态模式下无法使用实时诊断。',
+  'This module uses aggregate or stored diagnostic fields and omits raw fragments.': '此模块使用聚合或已存储的诊断字段，并省略原始片段。',
+  'Diagnostic snapshot': '诊断快照',
+  'Static mode cannot inspect indexed commands or repeated safe file identities.': '静态模式无法检查已索引命令或重复出现的安全文件标识。',
+  'Only loaded aggregate call fields are used.': '仅使用已加载的聚合调用字段。',
+  'Cache and context pressure': '缓存与上下文压力',
+  'Inspect a high-token evidence call, preserve a concise handoff, and start fresh before cold context is resent.': '检查高token证据调用，保留简洁交接信息，并在冷上下文被重新发送前开启新线程。',
+  'Aggregate evidence cannot determine whether the large context was necessary for output quality.': '聚合证据无法判断大量上下文是否确实为输出质量所必需。',
+  'No prompt or raw tool output is included.': '不包含提示词或原始工具输出。',
+  'Loaded call aggregates': '已加载的调用聚合数据',
+  'aggregate call': '聚合调用',
+  'Open the call and verify whether the context and effort matched the task.': '打开调用，确认上下文和推理强度是否与任务匹配。',
+  'Shell churn': 'Shell 重复操作',
+  'read pattern': '读取模式',
+  'File rediscovery': '文件重复查找',
+  'Low output': '低输出',
+  'Usage driver': '用量驱动因素',
+  'Guided summary': '引导式摘要',
+  'File modifications': '文件修改',
+  'Read productivity': '读取产出效率',
+  'Tool output pressure': '工具输出压力',
+  'File read patterns': '文件读取模式',
+  'File modification concentration': '文件修改集中度',
+  'Read-to-change productivity': '读取到修改的产出效率',
+  'Usage concentration': '用量集中度',
+  'Guided usage summary': '引导式用量摘要',
+  'Diagnostic evidence': '诊断证据',
+  'Replace repeated inspection sequences with one scoped script or reusable task.': '将重复检查步骤替换为一个范围明确的脚本或可复用任务。',
+  'Keep a short repository orientation note and reuse prior findings before reopening the same files.': '保留简短的仓库导览说明，重新打开相同文件前先复用已有发现。',
+  'Bound command output and summarize noisy tool results before the next model turn.': '限制命令输出，并在下一轮模型调用前总结冗长的工具结果。',
+  'Use a concise handoff and start a fresh thread before a cold resume resends large context.': '使用简洁交接信息，并在冷恢复重新发送大量上下文前开启新线程。',
+  'Inspect the dominant thread before applying a broad workflow change.': '大范围调整工作流前，请先检查占主导地位的线程。',
+  'Open the strongest evidence row and verify the suspected waste before changing the workflow.': '更改工作流前，请打开最有力的证据记录并验证疑似浪费。',
+  'No diagnostic fingerprints are available.': '没有可用的诊断特征。',
+  'Investigation report': '调查报告',
+  'high': '高',
+  'medium': '中',
+  'low': '低',
+  'evidence': '有证据',
+  'no evidence': '无证据',
+  'no_evidence': '无证据',
+
+  // Compression Lab.
+  'Context efficiency research': '上下文效率研究',
+  'Measure repeated context and tool-output exposure, allocate overlap once, and rank the largest local savings opportunities.': '测量重复上下文和工具输出暴露，统一分配重叠部分，并对最大的本地节省机会排序。',
+  'No current profile': '当前没有分析档案',
+  'Refresh analysis': '刷新分析',
+  'Analyze usage': '分析用量',
+  'Analyzing': '正在分析',
+  'Compression analysis progress': '上下文压缩分析进度',
+  'Waiting for the usage refresh to finish before starting analysis...': '正在等待用量刷新完成，然后开始分析…',
+  'Loading the newest exact-scope profile...': '正在加载最新的精确范围分析档案…',
+  'Compression Lab jobs run against the local SQLite index and are unavailable in static-file mode.': '上下文压缩实验室任务基于本地 SQLite 索引运行，静态文件模式下不可用。',
+  'No analysis for this scope yet': '尚未分析此范围',
+  'Start one persistent run. Returning to this scope will reuse the completed profile until its source revision changes.': '启动一次持久化分析。再次进入此范围时，会复用已完成的分析档案，直到源数据修订发生变化。',
+  'Overlap-adjusted portfolio': '已扣除重叠的机会组合',
+  'Profile complete': '分析档案已完成',
+  'Observed exposure': '观测暴露量',
+  'Tokens in analyzed components': '已分析组件中的token数',
+  'Likely avoidable': '可能可避免',
+  'Overlap-adjusted estimate': '已扣除重叠的估算值',
+  'Estimate range': '估算范围',
+  'Low to high heuristic': '启发式低值至高值',
+  'Candidates': '候选项',
+  'Opportunity families': '机会类别',
+  'Largest overlap-adjusted detector portfolios first.': '优先显示扣除重叠后规模最大的检测器机会组合。',
+  'Shared MCP profile': '共享 MCP 分析档案',
+  'Compression opportunity families': '上下文压缩机会类别',
+  'Family': '类别',
+  'Likely savings': '可能节省量',
+  'Range': '范围',
+  'Profile integrity': '分析档案完整性',
+  'Scope, coverage, and disclosure state for this result.': '此结果的范围、覆盖度和披露状态。',
+  'Cache': '缓存',
+  'Calls covered': '覆盖的调用数',
+  'Content mode': '内容模式',
+  'Raw fragments': '原始片段',
+  'Included': '已包含',
+  'Not included': '未包含',
+  'Build time': '生成耗时',
+  'Coverage warning': '覆盖度警告',
+  'Interpretation limits': '解读限制',
+  'Exact warm profile': '精确热缓存档案',
+  'Incremental profile': '增量分析档案',
+  'Reused profile': '复用的分析档案',
+  'Fresh profile': '新生成的分析档案',
+  'Preparing detector pipeline': '正在准备检测器流水线',
+  'detectors': '个检测器',
+  'records examined': '条记录已检查',
+  'tokens are the current likely savings estimate': '个token是当前可能节省量估算值',
+  'ranked candidates. Exposure is measured; avoidability remains an estimate.': '个已排序候选项。暴露量为实测值，可避免程度仍为估算值。',
+  'Compression analysis failed': '上下文压缩分析失败',
+  'Profile unavailable': '分析档案不可用',
+  'aggregate': '聚合数据',
+  'unclassified': '未分类',
+
+  // Allowance and limits research.
+  'Stored allowance evidence ready': '已存储的限额证据已就绪',
+  'Weekly primary signal selected': '已选择每周主要信号',
+  '5-hour noisy context selected': '已选择 5 小时噪声上下文',
+  'Refreshing allowance evidence...': '正在刷新限额证据…',
+  'Allowance refresh failed': '限额证据刷新失败',
+  'Allowance evidence refreshed': '限额证据已刷新',
+  'Strict allowance evidence exported': '已导出严格限额证据',
+  'Weekly hypothesis evaluated against detector output': '已使用检测器输出评估每周假设',
+  'Loading allowance history and detector': '正在加载限额历史记录与检测器',
+  'Exporting': '正在导出',
+  'Live detector payload': '实时检测器数据',
+  'Local claim threshold met': '已达到本地结论阈值',
+  'Research caution': '研究结论需谨慎',
+  'Outside usage possible': '可能存在外部用量',
+  'No large outside-usage flag': '未发现明显的外部用量信号',
+  'Weekly evidence first, rolling-window context second, and no claim beyond the loaded local data.': '以每周证据为主、滚动窗口上下文为辅，结论不超出已加载的本地数据。',
+  'Observed snapshots': '观测快照数',
+  'Weekly primary signal': '每周主要信号',
+  'Positive spans': '正向区间数',
+  'Candidate ratio': '候选比例',
+  'Recent vs earlier proxy': '近期与较早期代理值对比',
+  'Unexplained movement': '无法解释的变化',
+  'Weekly allowance evidence': '每周限额证据',
+  '5-hour rolling context': '5 小时滚动窗口上下文',
+  'Primary change detector with recent evidence shown first.': '主要变化检测器，优先显示近期证据。',
+  'Secondary context only; rolling-window movement is noisy.': '仅作为辅助上下文；滚动窗口变化包含较多噪声。',
+  'Allowance window': '限额窗口',
+  'Weekly': '每周',
+  '5-hour': '5 小时',
+  'Hypothesis check': '假设检验',
+  'Evaluate a community-style claim using the server detector result.': '使用服务器检测器结果评估社区常见说法。',
+  'Allowance hypothesis': '限额假设',
+  'Allowance decreased': '限额下降',
+  'Behavior stayed stable': '行为保持稳定',
+  'Not evaluated': '尚未评估',
+  'Choose a claim, then test it against the weekly detector': '选择一种说法，然后使用每周检测器进行检验',
+  'The dashboard reports the backend evidence grade; it does not run a separate client-side detector.': '仪表盘展示后端给出的证据等级，不会在客户端另行运行检测器。',
+  'More evidence required': '需要更多证据',
+  'Test weekly claim': '检验每周限额说法',
+  'Evidence grade': '证据等级',
+  'What supports or weakens the current result.': '支持或削弱当前结果的因素。',
+  'Method': '方法',
+  'No candidate split tested': '尚未检验候选分割点',
+  'Effect size': '效应量',
+  'One-sided p-value': '单侧 p 值',
+  '95% median intervals': '95% 中位数区间',
+  'Available for both regimes': '两个区间均可用',
+  'Available for one regime; the other sample is too small': '一个区间可用；另一个区间样本量过小',
+  'Unavailable at the current sample size': '当前样本量下不可用',
+  'Method, readiness, and caveats': '方法、就绪度与注意事项',
+  'Weekly observations are the primary signal. The 5-hour counter is rolling-window context.': '每周观测是主要信号；5 小时计数器仅作为滚动窗口上下文。',
+  'Weekly windows are treated as the primary signal for allowance-change claims.': '涉及限额变化的结论以每周窗口作为主要信号。',
+  'Five-hour windows are rolling counters and are downgraded unless supported by weekly evidence.': '5 小时窗口是滚动计数器；没有每周证据支持时，其证据权重会降低。',
+  'Unexplained movement can mean allowance behavior changed, but it can also mean usage outside these local Codex logs.': '无法解释的变化可能表示限额行为发生改变，也可能来自本地 Codex 日志之外的用量。',
+  'Allowance intelligence uses aggregate token counters and observed usage percentages only.': '限额分析仅使用聚合token计数和观测到的用量百分比。',
+  'Strict privacy output omits prompts, assistant text, tool output, file paths, thread names, and record identifiers.': '严格隐私输出会省略提示词、助手文本、工具输出、文件路径、线程名称和记录标识。',
+  "This project cannot read OpenAI's internal allowance ledger.": '此项目无法读取 OpenAI 内部限额台账。',
+  'Detector summary unavailable.': '检测器摘要不可用。',
+  'Insufficient evidence': '证据不足',
+  'The loaded weekly history cannot test this claim yet': '已加载的每周历史记录尚不足以检验此说法',
+  'More positive weekly spans are required before comparing regimes.': '比较不同区间前，需要更多正向每周区间。',
+  'Not supported': '不支持',
+  'No weekly regime change was detected': '未检测到每周区间变化',
+  'The loaded spans are more consistent with stable local behavior than a lower allowance regime.': '已加载区间更符合本地行为稳定，而不是限额区间下降。',
+  'Inconclusive': '无法确定',
+  'A local shift is plausible, but attribution is unresolved': '本地变化有一定可能，但归因尚未解决',
+  'Usage outside these local Codex logs could explain enough movement that an allowance change is not isolated.': '本地 Codex 日志之外的用量足以解释部分变化，因此无法单独确认限额发生变化。',
+  'Supported locally': '本地证据支持',
+  'Repeated weekly spans support a lower local capacity regime': '重复出现的每周区间支持本地容量区间下降',
+  'The nonparametric detector meets its local sample, effect-size, and p-value thresholds. This remains local evidence, not an internal ledger result.': '非参数检测器已达到本地样本量、效应量和 p 值阈值；这仍是本地证据，并非内部台账结论。',
+  'Possible change': '可能发生变化',
+  'The direction is consistent, but the sample is not claim-ready': '变化方向一致，但样本尚不足以形成可靠结论',
+  'More weekly spans are required on both sides of the candidate split.': '候选分割点两侧都需要更多每周区间。',
+  'Static dashboard fallback; local identifiers omitted.': '静态仪表盘回退数据；已省略本地标识。',
+  'Live allowance diagnostics are required before testing a change claim.': '检验限额变化说法前，需要实时限额诊断。',
+  'Evidence status': '证据状态',
+  'Live allowance detector unavailable in this static snapshot': '此静态快照中无法使用实时限额检测器',
+  'Projected weekly windows remain visible for orientation, but only the localhost detector can compare normalized positive spans and candidate regimes.': '仍显示预测的每周窗口用于参考，但只有本机检测器能比较标准化正向区间和候选区间。',
+  'Descriptive fallback': '描述性回退数据',
+  'Loaded aggregate projections are descriptive fallback data, not detector output.': '已加载的聚合预测仅为描述性回退数据，并非检测器输出。',
+  'Current result': '当前结果',
+  'No weekly regime change detected': '未检测到每周区间变化',
+  'The loaded positive spans remain within one local regime.': '已加载的正向区间仍处于同一本地区间。',
+  'No change detected': '未检测到变化',
+  'The 5-hour counter is behaving like a noisy rolling window': '5 小时计数器表现为噪声较多的滚动窗口',
+  'Use weekly spans as the primary signal before drawing a limit conclusion.': '得出限额结论前，请将每周区间作为主要信号。',
+  'Counter noise likely': '计数器可能存在噪声',
+  'Observed movement is not fully attributable to these local logs': '观测到的变化无法完全归因于这些本地日志',
+  'Outside usage remains plausible, so the detector cannot isolate an allowance change.': '仍可能存在外部用量，因此检测器无法单独确认限额变化。',
+  'Candidate regime change': '候选区间变化',
+  'The direction is consistent, but repeated weekly evidence is still below the public-claim threshold.': '变化方向一致，但重复出现的每周证据仍低于公开结论阈值。',
+  'Local sample, effect-size, and p-value thresholds are met. This is still not an OpenAI ledger result.': '本地样本量、效应量和 p 值均已达到阈值；但这仍不是 OpenAI 台账结论。',
+  'The local shift is strong, but at least one research-readiness requirement remains unmet.': '本地变化信号较强，但至少一项研究就绪要求尚未满足。',
+  'Claim-ready locally': '本地证据已可形成结论',
+  'Strong local evidence': '较强本地证据',
+  'Not enough weekly evidence to test an allowance change': '每周证据不足，无法检验限额变化',
+  'Insufficient data': '数据不足',
+  'Consistent': '一致',
+  'Stable weekly behavior fits the loaded evidence': '稳定的每周行为符合已加载证据',
+  'No candidate split cleared the detector thresholds.': '没有候选分割点达到检测器阈值。',
+  'Stable behavior cannot be isolated either': '同样无法单独确认行为稳定',
+  'Outside usage and unexplained movement weaken both the stable and decreased hypotheses.': '外部用量和无法解释的变化同时削弱了“稳定”和“下降”两种假设。',
+  'A candidate weekly shift conflicts with the stable hypothesis': '候选每周变化与稳定假设冲突',
+  'Review the candidate split and readiness criteria before deciding whether the shift is durable.': '判断变化是否持续前，请检查候选分割点和就绪标准。',
+  'the candidate split': '候选分割点',
+  'Supporting windows': '支撑窗口',
+  'Exact local evidence behind the selected chart. Linked rows open the underlying call.': '所选图表背后的精确本地证据；关联记录可打开底层调用。',
+  'Scrollable allowance evidence table': '可滚动的限额证据表格',
+  'Allowance evidence windows and linked calls': '限额证据窗口与关联调用',
+  'Observed': '观测时间',
+  'Capacity proxy': '容量代理值',
+  'Remaining': '剩余比例',
+  'Movement': '变化',
+  'Est. credits': '估算点数',
+  'Plan': '套餐',
+  'Actions': '操作',
+  'Aggregate': '聚合数据',
+  'No usable evidence rows are available for this window.': '此窗口没有可用的证据记录。',
+  'Load more windows': '加载更多窗口',
+  'Weekly local capacity evidence': '每周本地容量证据',
+  'Observed weekly remaining': '每周剩余比例观测值',
+  'Estimated credits per 100 percentage points of observed weekly movement, with exact median intervals when the sample supports them.': '按每周观测变化的每 100 个百分点估算点数；样本充分时显示精确中位数区间。',
+  'Loaded aggregate weekly projections for orientation. Exact detector intervals require the localhost allowance endpoints.': '已加载的每周聚合预测仅供参考；精确检测器区间需要本机限额接口。',
+  'Observed percentage remaining. The 5-hour view is intentionally secondary because rolling-window movement is noisy.': '观测到的剩余百分比。由于滚动窗口变化噪声较多，5 小时视图仅作为辅助。',
+  'weekly spans': '每周区间',
+  'weekly primary signal': '每周主要信号',
+  'secondary rolling-window context': '辅助滚动窗口上下文',
+  'This is a local capacity proxy, not an official OpenAI allowance or billing ledger.': '这是本地容量代理值，并非 OpenAI 官方限额或计费台账。',
+  'Rolling-window movement, resets, and sparse observations make the 5-hour counter noisy.': '滚动窗口变化、重置和稀疏观测会使 5 小时计数器包含较多噪声。',
+  'Use left and right arrow keys to move through observations. Switch to the table for exact values.': '使用左右方向键浏览观测值；精确数值请切换到表格。',
+  '95% low': '95% 下限',
+  '95% high': '95% 上限',
+  'Observed movement': '观测变化',
+  'Weekly evidence span': '每周证据区间',
+  'Observed time': '观测时间',
+  'Credits per 100% observed movement': '每 100% 观测变化对应点数',
+  'Percent remaining': '剩余百分比',
+  'Local capacity proxy': '本地容量代理值',
+  'Weekly remaining': '每周剩余比例',
+  'Noisy 5-hour remaining': '含噪声的 5 小时剩余比例',
+  'Candidate shift · outside usage possible': '候选变化 · 可能存在外部用量',
+  'Candidate weekly regime shift': '候选每周区间变化',
+  'Observed counter reset or rollback': '观测到计数器重置或回退',
+  'Observation gap': '观测间隔',
+  'weekly span': '每周区间',
+  'observation': '观测值',
+  'strong local evidence': '较强本地证据',
+  'possible regime change': '可能发生区间变化',
+  'inconclusive other usage possible': '无法确定，可能存在其他用量',
+  'no change detected': '未检测到变化',
+  'counter noise likely': '计数器可能存在噪声',
+  'insufficient data': '数据不足',
+
+  // Cache and context workspace.
+  'Cache And Context Lab': '缓存与上下文实验室',
+  'Cache behavior, cold resumes, context pressure, optimization recommendations.': '分析缓存行为、冷恢复、上下文压力和优化建议。',
+  'Full-scope endpoints': '完整范围接口',
+  'Snapshot fallback': '快照回退数据',
+  'Context safe': '上下文安全',
+  'Loading cache and context evidence': '正在加载缓存与上下文证据',
+  'Cache Hit Rate & Context Window Over Time': '缓存命中率与上下文窗口趋势',
+  'Cache reuse and context pressure': '缓存复用与上下文压力',
+  'Percent': '百分比',
+  'Cache Reuse Heatmap': '缓存复用热力图',
+  'No cache heatmap rows': '没有缓存热力图记录',
+  'Scrollable cache reuse heatmap': '可滚动的缓存复用热力图',
+  'Cache reuse heatmap': '缓存复用热力图',
+  'No cache heatmap rows in the current aggregate snapshot.': '当前聚合快照中没有缓存热力图记录。',
+  'Threads Overview': '线程概览',
+  'Cold resume and cache efficiency signals': '冷恢复与缓存效率信号',
+  'Hover previews; rows open latest call': '悬停可预览；单击记录可打开最新调用',
+  'Cache context threads overview': '缓存与上下文线程概览',
+  'Selected Thread Diagnosis': '所选线程诊断',
+  'No grouped thread is available in the current aggregate snapshot.': '当前聚合快照中没有可用的分组线程。',
+  'Efficiency Profile': '效率概况',
+  'Cache hit': '缓存命中率',
+  'Est. cost': '估算成本',
+  'Cost/call': '单次调用成本',
+  'Cache Windows': '缓存窗口',
+  'Weekly reuse': '每周复用',
+  'No heatmap row': '没有热力图记录',
+  'no heatmap row': '没有热力图记录',
+  'No weekly cache heatmap row matches this selected thread.': '没有与所选线程匹配的每周缓存热力图记录。',
+  'No loaded aggregate call rows match this selected thread.': '没有与所选线程匹配的已加载聚合调用记录。',
+  'Diagnosis Basis': '诊断依据',
+  'Suggested Actions': '建议操作',
+  'Summarize before the next work session.': '在下次工作会话前先做摘要。',
+  'Split completed topics or reduce repeated uncached context.': '拆分已完成的主题，或减少重复的未缓存上下文。',
+  'Open a related call and inspect whether model effort was justified.': '打开相关调用，检查模型推理强度是否合理。',
+  'Keep the thread warm and continue monitoring cache reuse.': '保持线程热缓存，并继续监控缓存复用。',
+  'Thread summaries': '线程摘要',
+  'Selected thread calls': '所选线程调用',
+  'Focused evidence': '聚焦证据',
+  'server-side aggregate': '服务器端聚合数据',
+  'review cache reuse': '检查缓存复用',
+  'Window': '窗口',
+};
+
+export const advancedPagesZhHansPatterns: ReadonlyArray<ZhHansPattern> = [
+  // Investigator status, evidence counts, and action labels. Finding titles and patterns are preserved.
+  { pattern: /^Live evidence refreshed · ([\d,.]+) diagnostic modules$/u, replace: '实时证据已刷新 · $1 个诊断模块' },
+  { pattern: /^Refresh failed: (.+)$/u, replace: '刷新失败：$1' },
+  { pattern: /^Live report unavailable: (.+)$/u, replace: '实时报告不可用：$1' },
+  { pattern: /^Investigation report unavailable: (.+)$/u, replace: '调查报告不可用：$1' },
+  { pattern: /^(.+) unavailable: (.+)$/u, replace: '$1不可用：$2' },
+  { pattern: /^Loading diagnostics ([\d,.]+)\/([\d,.]+)$/u, replace: '正在加载诊断模块 $1/$2' },
+  { pattern: /^([\d,.]+) diagnostic modules$/u, replace: '$1 个诊断模块' },
+  { pattern: /^([\d,.]+) ranked findings$/u, replace: '$1 个已排序发现' },
+  { pattern: /^([\d,.]+) signals$/u, replace: '$1 个信号' },
+  { pattern: /^([\d,.]+) rows$/u, replace: '$1 条记录' },
+  { pattern: /^([\d,.]+) linked$/u, replace: '已关联 $1 条' },
+  { pattern: /^([\d,.]+) score$/u, replace: '评分 $1' },
+  { pattern: /^Evidence ledger for (.+)$/u, replace: (_match, finding) => `“${advancedUiTermZhHans(finding)}”的证据台账` },
+  { pattern: /^(.+) · ([\d,.]+) events · ([\d,.]+(?:[KMBT])?) tokens$/iu, replace: '$1 · $2 个事件 · $3 个token' },
+  {
+    pattern: /^history (active|all) · no stored snapshot\. Function calls: ([\d,.]+); Function outputs: ([\d,.]+); Original tokens: ([\d,.]+)\.$/u,
+    replace: (_match, scope, calls, outputs, tokens) =>
+      `历史范围：${scope === 'all' ? '全部历史记录' : '活动会话'} · 没有已存储快照。函数调用：${calls}；函数输出：${outputs}；原始token数：${tokens}。`,
+  },
+  { pattern: /^(Open call|Open thread|No linked record) for (.+)$/u, replace: (_match, action, patternName) => `${investigationActionZhHans(action)}：${patternName}` },
+  { pattern: /^Copy call link for (.+)$/u, replace: '复制以下模式对应的调用链接：$1' },
+  { pattern: /^Open call evidence for (.+)$/u, replace: '打开以下模式的调用证据：$1' },
+  { pattern: /^Open thread evidence for (.+)$/u, replace: '打开以下模式的线程证据：$1' },
+  { pattern: /^([\d,.]+) loaded calls combine weak cache reuse or elevated context pressure\.$/u, replace: '$1 次已加载调用存在缓存复用较弱或上下文压力升高的情况。' },
+  { pattern: /^(.+) is the highest-ranked of ([\d,.]+) findings with ([\d,.]+) supporting rows\.$/u, replace: (_match, finding, count, rows) => `“${advancedUiTermZhHans(finding)}”在 ${count} 个发现中排名最高，并有 ${rows} 条支撑记录。` },
+  { pattern: /^([\d,.]+(?:\.\d+)?)% cache · ([\d,.]+(?:[KMBT])?) output$/iu, replace: '缓存 $1% · 输出 $2 个token' },
+
+  // Compression progress and estimates.
+  { pattern: /^Compression analysis failed: (.+)$/u, replace: '上下文压缩分析失败：$1' },
+  { pattern: /^Profile unavailable: (.+)$/u, replace: '分析档案不可用：$1' },
+  { pattern: /^([\d,.]+) of ([\d,.]+) detectors \/ ([\d,.]+) records examined$/u, replace: '检测器 $1/$2 · 已检查 $3 条记录' },
+  { pattern: /^([\d,.]+(?:[KMBT])?) tokens are the current likely savings estimate$/iu, replace: '当前可能节省量估算为 $1 个token' },
+  { pattern: /^([\d,.]+) to ([\d,.]+) across ([\d,.]+) ranked candidates\. Exposure is measured; avoidability remains an estimate\.$/u, replace: '在 $3 个已排序候选项中，估算范围为 $1 至 $2。暴露量为实测值，可避免程度仍为估算值。' },
+  { pattern: /^([\d,.]+) coverage warnings$/u, replace: '$1 条覆盖度警告' },
+  { pattern: /^([\d,.]+) detector families$/u, replace: '$1 个检测器类别' },
+  { pattern: /^(.+) detector$/u, replace: '$1 检测器' },
+
+  // Allowance research. Plans, dates, and detector errors are preserved verbatim.
+  { pattern: /^Export failed: (.+)$/u, replace: '导出失败：$1' },
+  { pattern: /^Live detector unavailable: (.+)$/u, replace: '实时检测器不可用：$1' },
+  { pattern: /^([\d,.]+) weekly spans · (.+)$/u, replace: '$1 个每周区间 · $2' },
+  { pattern: /^([\d,.]+) resets \/ rollbacks$/u, replace: '$1 次重置/回退' },
+  { pattern: /^([\d,.]+) positive weekly spans are loaded\. More observations are needed before comparing regimes\.$/u, replace: '已加载 $1 个正向每周区间。比较不同区间前还需要更多观测值。' },
+  { pattern: /^Weekly behavior shifted around (.+)$/u, replace: '每周行为在 $1 附近发生变化' },
+  { pattern: /^The recent local capacity proxy is ([\d,.]+)% of the earlier regime after (.+)$/u, replace: '$2 之后，近期本地容量代理值为较早区间的 $1%' },
+  { pattern: /^Span ([\d,.]+)$/u, replace: '区间 $1' },
+  { pattern: /^Observation ([\d,.]+)$/u, replace: '观测 $1' },
+  { pattern: /^Open allowance evidence call observed (.+)$/u, replace: '打开以下观测对应的限额证据调用：$1' },
+  { pattern: /^Copy link to allowance evidence call observed (.+)$/u, replace: '复制以下观测对应的限额证据调用链接：$1' },
+  { pattern: /^At least two (weekly spans|observations) are required for a trend\.$/u, replace: (_match, kind) => `至少需要两个${kind === 'weekly spans' ? '每周区间' : '观测值'}才能显示趋势。` },
+  { pattern: /^(.+) · weekly primary signal$/u, replace: '$1 · 每周主要信号' },
+  { pattern: /^(.+) · secondary rolling-window context$/u, replace: '$1 · 辅助滚动窗口上下文' },
+  { pattern: /^(Weekly local capacity evidence|Observed weekly remaining|5-hour rolling context) evidence$/u, replace: (_match, title) => `${allowanceChartTitleZhHans(title)}证据` },
+  { pattern: /^Only ([\d,.]+) usable weekly span is available\.$/u, replace: '仅有 $1 个可用的每周区间。' },
+  { pattern: /^Only ([\d,.]+) usable observation is available\.$/u, replace: '仅有 $1 个可用的观测值。' },
+  { pattern: /^([\d,.]+) 5-hour observations are shown as noisy rolling-window context, not primary allowance evidence\.$/u, replace: '当前显示 $1 个 5 小时观测值，它们仅作为含噪声的滚动窗口上下文，而非主要限额证据。' },
+
+  // Cache/context counts and labels. Thread names and model names remain unchanged.
+  { pattern: /^([\d,.]+) cache windows$/u, replace: '$1 个缓存窗口' },
+  { pattern: /^Selected (.+): ([\d,.]+(?:\.\d+)?)% cache$/u, replace: '已选择“$1”：缓存 $2%' },
+  { pattern: /^Selected (.+)$/u, replace: '已选择：$1' },
+  { pattern: /^Showing ([\d,.]+) of ([\d,.]+) full-scope thread summaries\.$/u, replace: '显示 $1 / $2 个完整范围线程摘要。' },
+  { pattern: /^([\d,.]+) loaded$/u, replace: '已加载 $1 条' },
+  { pattern: /^([\d,.]+) loaded calls$/u, replace: '已加载 $1 次调用' },
+  { pattern: /^([\d,.]+(?:[KMBT])?) tokens - ([\d,.]+(?:\.\d+)?)% cache$/iu, replace: '$1 个token - 缓存 $2%' },
+  { pattern: /^([\d,.]+(?:[KMBT])?) total tokens$/iu, replace: '共 $1 个token' },
+  { pattern: /^Window ([\d,.]+)$/u, replace: '窗口 $1' },
+  { pattern: /^Cache windows for (.+)$/u, replace: '“$1”的缓存窗口' },
+  { pattern: /^Open investigator for cache thread call (.+)$/u, replace: '在分析器中打开缓存线程调用：$1' },
+  { pattern: /^Copy link for cache thread call (.+)$/u, replace: '复制缓存线程调用链接：$1' },
+  { pattern: /^Risk: (High|Medium|Low) cold-resume score$/u, replace: (_match, risk) => `风险：冷恢复评分${riskZhHans(risk)}` },
+  { pattern: /^(High|Medium|Low) risk$/u, replace: (_match, risk) => `${riskZhHans(risk)}风险` },
+  { pattern: /^Cache: ([\d,.]+(?:\.\d+)?)% hit rate; action threshold below 35%$/u, replace: '缓存：命中率 $1%；操作阈值低于 35%' },
+  { pattern: /^Cost: (.+) per call; inspect threshold above \$1\.00$/u, replace: '成本：每次调用 $1；检查阈值高于 $1.00' },
+  { pattern: /^Evidence: ([\d,.]+) loaded calls, ([\d,.]+) cache windows$/u, replace: '证据：已加载 $1 次调用，包含 $2 个缓存窗口' },
+  { pattern: /^Evidence: ([\d,.]+) loaded calls, no heatmap row$/u, replace: '证据：已加载 $1 次调用，没有热力图记录' },
+];
+
+function investigationActionZhHans(action: string): string {
+  if (action === 'Open call') return '打开调用';
+  if (action === 'Open thread') return '打开线程';
+  return '没有关联记录';
+}
+
+function advancedUiTermZhHans(value: string): string {
+  return advancedPagesZhHansTranslations[value] ?? value;
+}
+
+function allowanceChartTitleZhHans(title: string): string {
+  if (title === 'Weekly local capacity evidence') return '每周本地容量';
+  if (title === 'Observed weekly remaining') return '每周剩余比例观测值';
+  return '5 小时滚动窗口上下文';
+}
+
+function riskZhHans(risk: string): string {
+  if (risk === 'High') return '高';
+  if (risk === 'Medium') return '中';
+  return '低';
+}
diff --git a/frontend/dashboard/src/app/zh-Hans/common.ts b/frontend/dashboard/src/app/zh-Hans/common.ts
new file mode 100644
index 00000000..55783b47
--- /dev/null
+++ b/frontend/dashboard/src/app/zh-Hans/common.ts
@@ -0,0 +1,269 @@
+import type { ZhHansPattern } from './types';
+
+export const commonZhHansTranslations: Readonly<Record<string, string>> = {
+  'Active history': '活动记录',
+  'Active sessions': '活动会话',
+  'Active sessions only': '仅活动会话',
+  'Aggregate fallback': '聚合数据回退',
+  'Aggregate only': '仅聚合数据',
+  'All calls visible': '显示全部调用',
+  'All history selected': '已选择全部历史记录',
+  'All time': '全部时间',
+  'Analysis scope': '分析范围',
+  'Auto refresh': '自动刷新',
+  'Auto refresh paused': '自动刷新已暂停',
+  'Auto refresh pauses on this evidence-heavy view': '此证据密集页面会暂停自动刷新',
+  'Available languages': '可用语言',
+  'Back to top': '返回顶部',
+  'Browse all calls': '浏览全部调用',
+  'Cancel refresh': '取消刷新',
+  'Chart view': '图表视图',
+  'Chart unavailable. Use the synchronized table view.': '图表不可用，请使用同步表格视图。',
+  'Caveats:': '注意事项：',
+  'Choose loaded call window': '选择调用加载范围',
+  'Clear filters': '清除筛选条件',
+  'Clipboard unavailable': '剪贴板不可用',
+  'Columns': '列',
+  'Commands': '命令',
+  'Copy call link': '复制调用链接',
+  'Copy investigator link': '复制分析器链接',
+  'Copy unavailable in browser': '浏览器中无法复制',
+  'Custom': '自定义',
+  'Dashboard filters': '仪表盘筛选器',
+  'Dashboard route could not load': '仪表盘页面无法加载',
+  'Dashboard toolbar': '仪表盘工具栏',
+  'Day': '日期',
+  'Dense': '紧凑',
+  'Daily': '每日',
+  'Density': '显示密度',
+  'Endpoint fallback': '接口回退数据',
+  'Endpoint unavailable.': '接口不可用。',
+  'Export': '导出',
+  'Export overview': '导出概览',
+  'Export SVG': '导出 SVG',
+  'Export visualization as SVG': '将可视化导出为 SVG',
+  'Files': '文件',
+  'FILTERS': '筛选',
+  'Filters': '筛选',
+  'From': '来源',
+  'Global confidence filter': '全局置信度筛选器',
+  'Global effort filter': '全局推理强度筛选器',
+  'Global end date': '全局结束日期',
+  'Global model filter': '全局模型筛选器',
+  'Global start date': '全局开始日期',
+  'Global time filter': '全局时间筛选器',
+  'History scope': '历史记录范围',
+  'Incomplete page evidence': '页面证据不完整',
+  'Lifecycle': '生命周期',
+  'Invalid date range': '日期范围无效',
+  'Last 24h': '过去 24 小时',
+  'Last 7 days': '过去 7 天',
+  'Live API': '实时 API',
+  'Loaded snapshot': '已加载快照',
+  'Loading dashboard': '正在加载仪表盘',
+  'Loading renderer...': '正在加载图表渲染器…',
+  'Local API token present for refresh actions.': '已提供本地 API 令牌，可执行刷新操作。',
+  'Local data only': '仅使用本地数据',
+  'Models': '模型',
+  'More columns': '更多列',
+  'No data': '暂无数据',
+  'No matching evidence': '没有匹配的证据',
+  'No rows match current filters.': '没有符合当前筛选条件的记录。',
+  'Primary': '主导航',
+  'Privacy': '隐私',
+  'Quick Links': '快捷入口',
+  'Recent': '最近记录',
+  'Recent rows': '最近记录',
+  'Refresh data': '刷新数据',
+  'Restore defaults': '恢复默认设置',
+  'Restoring the local usage workspace...': '正在恢复本地用量工作区…',
+  'Retry': '重试',
+  'Roomy': '宽松',
+  'Search': '搜索',
+  'Selected': '已选择',
+  'Show more columns': '显示更多列',
+  'Static embedded snapshot': '静态内嵌快照',
+  'Static embedded snapshot; live refresh is unavailable.': '当前为静态内嵌快照，无法实时刷新。',
+  'Stored snapshot': '已存储的快照',
+  'Stored snapshot loaded just now': '刚刚载入已存储的快照',
+  'Table view': '表格视图',
+  'Table': '表格',
+  'Tokens line chart': 'token折线图',
+  'Tokens history. Recent dates are shown first; scroll left for earlier dates.': 'token历史记录。近期日期优先显示；向左滚动可查看更早日期。',
+  'Cache % line chart': '缓存比例折线图',
+  'Cache % history. Recent dates are shown first; scroll left for earlier dates.': '缓存比例历史记录。近期日期优先显示；向左滚动可查看更早日期。',
+  'Text direction': '文字方向',
+  'Today': '今天',
+  'Unofficial project notice': '非官方项目声明',
+  'Unofficial project.': '非官方项目。',
+  'Updated': '已更新',
+  'Updated unversioned': '更新于未标记版本',
+  'Updating evidence': '正在更新证据',
+  'Updating page evidence': '正在更新页面证据',
+  'Working on full-scope evidence': '正在处理完整范围的证据',
+  'Usage summary ready': '用量摘要已就绪',
+  'Recommendations loading': '建议正在加载',
+  'Recommendations ready': '建议已就绪',
+  '24 hours': '24 小时',
+  '7 days': '7 天',
+  'Aggregate Identity': '聚合记录标识',
+  'Aggregate summary': '聚合摘要',
+  'Auto': '自动',
+  'Cache And Context': '缓存与上下文',
+  'Cache Reuse': '缓存复用率',
+  'Cached': '缓存输入',
+  'Cached %': '缓存比例',
+  'Cached Input': '缓存输入',
+  'Call filters': '调用筛选器',
+  'Compression Lab': '上下文压缩实验室',
+  'Context %': '上下文比例',
+  'Context window': '上下文窗口',
+  'Diagnostics Notebook': '诊断工作台',
+  'Duration': '耗时',
+  'Effort': '推理强度',
+  'Input Tokens': '输入token',
+  'Initiated': '发起方',
+  'Investigate': '调查分析',
+  'Investigation': '调查分析',
+  'Limits': '使用限额',
+  'Loaded usage metrics': '已加载的用量指标',
+  'Loading overview evidence': '正在加载概览证据',
+  'Loading overview evidence modules': '正在加载概览证据模块',
+  'Loaded token accounting': '已加载的token统计',
+  'Local telemetry console': '本地用量分析控制台',
+  'No calls are available for token accounting.': '没有可用于token统计的调用。',
+  'No daily token movement is available.': '没有可用的每日token变化数据。',
+  'No dated aggregate usage is available in this scope.': '当前范围内没有带日期的聚合用量数据。',
+  'No loaded calls match the current search.': '已加载的调用中没有符合当前搜索条件的记录。',
+  'No token accounting is available in this scope.': '当前范围内没有可用的token统计数据。',
+  'Not made by, affiliated with, endorsed by, sponsored by, or supported by OpenAI.': '本项目并非由 OpenAI 制作，也不隶属于 OpenAI，未获其认可、赞助或支持。',
+  'Overview': '概览',
+  'Prev Gap': '与上次间隔',
+  'Pricing configured': '已配置定价',
+  'Project metadata is shown normally.': '项目元数据按正常模式显示。',
+  'Recent token movement': '近期token变化',
+  'Daily input, cached reuse, and output volume in the selected history scope.': '所选历史范围内的每日输入、缓存复用和输出量。',
+  'Daily aggregates describe local records; they do not represent OpenAI billing.': '每日聚合仅描述本地记录，不代表 OpenAI 账单。',
+  'Categories mirror reported fields and may overlap; flow widths are accounting, not causality or billed cost.': '分类与日志报告字段一致，彼此可能重叠；流量宽度仅表示统计量，不代表因果关系或计费成本。',
+  'The four reported token categories across calls currently loaded in the dashboard.': '仪表盘当前已加载调用中的四类token统计。',
+  'The important changes first, with direct paths into supporting evidence.': '优先展示重要变化，并可直接查看支撑证据。',
+  'reported token accounting': '日志报告的token统计',
+  'loaded evidence rows': '已加载的证据记录',
+  'loaded calls only': '仅统计已加载调用',
+  'calls with mapped cost and credit rates': '已匹配成本与点数费率的调用',
+  'Estimated credits': '估算点数',
+  'risk: low cache reuse': '风险：缓存复用率低',
+  'Reasoning': '推理输出',
+  'Reasoning Output': '推理输出',
+  'Reports': '报告',
+  'Settings': '设置',
+  'Signals': '信号',
+  'CACHE': '缓存',
+  'CTX': '上下文',
+  'EST': '估算',
+  'LO': '低输出',
+  'RSN': '推理',
+  'BIG': '长线程',
+  'PRICE': '定价',
+  'SUB': '子智能体',
+  'Sort by Cached %': '按缓存比例排序',
+  'Sort by Cached Input': '按缓存输入排序',
+  'Sort by Codex Credits': '按 Codex 点数排序',
+  'Sort by Context %': '按上下文比例排序',
+  'Sort by Duration': '按耗时排序',
+  'Sort by Effort': '按推理强度排序',
+  'Sort by Est. Cost': '按估算成本排序',
+  'Sort by Initiated': '按发起方排序',
+  'Sort by Input Tokens': '按输入token排序',
+  'Sort by Model': '按模型排序',
+  'Sort by Output Tokens': '按输出token排序',
+  'Sort by Prev Gap': '按与上次间隔排序',
+  'Sort by Reasoning Output': '按推理输出排序',
+  'Sort by Signals': '按信号排序',
+  'Sort by Thread': '按线程排序',
+  'Sort by Time': '按时间排序',
+  'Sort by Total Tokens': '按token总数排序',
+  'Sort by Uncached Input': '按未缓存输入排序',
+  'Total Calls': '调用总数',
+  'Total Tokens': 'token总数',
+  'Total Tokens breakdown': 'token总数明细',
+  'Estimated Cost breakdown': '估算成本明细',
+  'Uncached': '未缓存输入',
+  'Uncached Input': '未缓存输入',
+  'Usage pulse': '用量脉搏',
+  'Visualization contract error': '可视化定义错误',
+  'Visualization view': '可视化视图',
+  'Visualization is loading.': '正在加载可视化。',
+  'Partial evidence': '部分证据',
+  'Evidence unavailable': '证据不可用',
+  'must include at least one series': '必须至少包含一个数据系列',
+  'series': '数据系列',
+  'Recent dates shown. Scroll left for earlier dates.': '当前显示近期日期；向左滚动可查看更早日期。',
+  'Data is ready.': '数据已就绪。',
+  'Live facts': '实时事实',
+  'Live snapshots': '实时快照',
+  'loading': '正在加载',
+  'updating': '正在更新',
+  'unavailable': '不可用',
+  'waiting': '等待中',
+  'Model calls display controls': '模型调用显示控件',
+  'Highest-attention Threads display controls': '关注度最高的对话线程显示控件',
+  'aggregate rows': '聚合记录',
+  'grouped threads': '分组线程',
+  'Percent line chart': '百分比折线图',
+  'Percent history. Recent dates are shown first; scroll left for earlier dates.': '百分比历史记录。近期日期优先显示；向左滚动可查看更早日期。',
+  'Reload Commands diagnostic snapshot': '重新加载命令诊断快照',
+  'Reload Git Interactions diagnostic snapshot': '重新加载 Git 交互诊断快照',
+  'unknown · weekly primary signal': '未知 · 每周主要信号',
+  'Cache hit %': '缓存命中率',
+  'Thread lifecycle': '线程生命周期',
+  'Call': '调用',
+  'Elapsed': '已经过时间',
+  'Context': '上下文',
+  'Continuation': '延续调用',
+  'Initiator': '发起方',
+  'total': '总计',
+  'blank': '未指定',
+  'max': '最大',
+  'ultra': '极高',
+  'xhigh': '超高',
+};
+
+export const commonZhHansPatterns: ReadonlyArray<ZhHansPattern> = [
+  { pattern: /^(.+) table$/u, replace: '$1表格' },
+  { pattern: /^([\d,.]+)m ([\d,.]+)s$/u, replace: '$1 分 $2 秒' },
+  { pattern: /^([\d,.]+)s$/u, replace: '$1 秒' },
+  { pattern: /^Sort by (.+)$/u, replace: (_match, label) => `按${label}排序` },
+  { pattern: /^Showing ([\d,.]+) of ([\d,.]+) table rows$/u, replace: '显示 $1 / $2 条表格记录' },
+  { pattern: /^Show ([\d,.]+) more rows$/u, replace: '再显示 $1 条记录' },
+  { pattern: /^Loaded ([\d,.]+) of ([\d,.]+) available calls$/u, replace: '已加载 $1 / $2 次可用调用' },
+  { pattern: /^([\d,.]+) calls analyzed · ([\d,.]+) detail rows cached$/u, replace: '已分析 $1 次调用 · 已缓存 $2 条详情记录' },
+  { pattern: /^([\d,.]+) calls available in scope$/u, replace: '当前范围内有 $1 次调用' },
+  { pattern: /^([\d,.]+) loaded calls$/u, replace: '已加载 $1 次调用' },
+  { pattern: /^([\d,.]+) evidence rows$/u, replace: '$1 条证据记录' },
+  { pattern: /^Unknown project ([\d,.]+)$/u, replace: '未知项目 $1' },
+  { pattern: /^([\d,.]+) ranked evidence rows$/u, replace: '$1 条已排序证据记录' },
+  { pattern: /^Updated (.+)$/u, replace: '更新于 $1' },
+  { pattern: /^Loading (.+)\.\.\.$/u, replace: '正在加载$1…' },
+  { pattern: /^No (.+) to export$/u, replace: '没有可导出的$1' },
+  { pattern: /^Exported ([\d,.]+) (.+)$/u, replace: '已导出 $1 条$2' },
+  { pattern: /^(.+) endpoint failed with HTTP ([\d]+)\.$/u, replace: '$1接口请求失败（HTTP $2）。' },
+  { pattern: /^Back to (.+)$/u, replace: '返回$1' },
+  { pattern: /^Clear (.+)$/u, replace: '清除$1' },
+  { pattern: /^Incomplete page evidence: (.+)$/u, replace: '页面证据不完整：$1' },
+  { pattern: /^All time analysis uses ([\d,.]+) calls; ([\d,.]+) detail rows cached$/u, replace: '全部时间范围共分析 $1 次调用；已缓存 $2 条详情记录' },
+  { pattern: /^Focused pages analyze all ([\d,.]+) calls in scope; ([\d,.]+) call rows are cached for immediate detail views\.$/u, replace: '聚焦页面会分析范围内全部 $1 次调用；已缓存 $2 条调用记录，可立即查看详情。' },
+  { pattern: /^([\d,.]+) of ([\d,.]+) modules ready$/u, replace: '$1/$2 个模块已就绪' },
+  { pattern: /^([\d,.]+(?:[KMBT])?) cached input tokens$/iu, replace: '$1 个缓存输入token' },
+  { pattern: /^([\d,.]+(?:[KMBT])?) cached input$/iu, replace: '$1 个缓存输入token' },
+  { pattern: /^(.+) · (.+) · ([\d,.]+(?:[KMBT])?) tokens · ([\d,.]+(?:\.\d+)?)% cache$/iu, replace: '$1 · $2 · $3 个token · 缓存 $4%' },
+  { pattern: /^([\d,.]+) matching calls with the same evidence fields as the Calls workspace\.$/u, replace: '$1 次调用符合条件，证据字段与“调用”工作区一致。' },
+  { pattern: /^Load more recent calls$/u, replace: '加载更多近期调用' },
+  { pattern: /^(.+) line chart$/u, replace: '$1折线图' },
+  { pattern: /^(.+) chart$/u, replace: '$1图表' },
+  { pattern: /^(.+) history\. Recent dates are shown first; scroll left for earlier dates\.$/u, replace: '$1历史记录。近期日期优先显示；向左滚动可查看更早日期。' },
+  { pattern: /^Showing ([\d,.]+) of ([\d,.]+) full-scope thread summaries\.$/u, replace: '显示 $1 / $2 个完整范围线程摘要。' },
+  { pattern: /^([\d,.]+) table rows available\.$/u, replace: '可查看 $1 条表格记录。' },
+  { pattern: /^(.+) display controls$/u, replace: '$1显示控件' },
+  { pattern: /^(.+) modules$/u, replace: '$1模块' },
+];
diff --git a/frontend/dashboard/src/app/zh-Hans/corePages.ts b/frontend/dashboard/src/app/zh-Hans/corePages.ts
new file mode 100644
index 00000000..37fc66b6
--- /dev/null
+++ b/frontend/dashboard/src/app/zh-Hans/corePages.ts
@@ -0,0 +1,730 @@
+import type { ZhHansPattern } from './types';
+
+export const corePagesZhHansTranslations: Readonly<Record<string, string>> = {
+  // Application shell, navigation, and shared controls.
+  'High-level telemetry': '全局用量概览',
+  'Root-cause evidence': '根因证据',
+  'Context savings': '上下文节省分析',
+  'Model-call table': '模型调用明细',
+  'Thread efficiency': '线程效率',
+  'Allowance intelligence': '限额分析',
+  'Cache and cold resumes': '缓存与冷恢复',
+  'Technical report': '技术诊断',
+  'Generated analyses': '生成的分析报告',
+  'Local configuration': '本地配置',
+  'Search dashboard': '搜索仪表盘',
+  'Search calls, threads, models, diagnostics...': '搜索调用、线程、模型和诊断…',
+  'Loaded cached dashboard snapshot': '已加载缓存的仪表盘快照',
+  'Refresh cancelled; stored snapshot remains visible': '刷新已取消，仍显示已存储的快照',
+  'Copied current view link': '已复制当前视图链接',
+  'Copied call investigator link': '已复制调用分析器链接',
+  'Copied investigator link': '已复制分析器链接',
+  'Copied Calls view link': '已复制“调用”视图链接',
+  'Copy unavailable in this browser': '此浏览器无法复制',
+  'Investigation preset cleared': '已清除调查预设',
+  'Calls filters cleared': '已清除调用筛选条件',
+  'Thread filters cleared': '已清除线程筛选条件',
+  'Refreshing usage index': '正在刷新用量索引',
+  'All history selected; no archived calls are indexed yet': '已选择全部历史记录，但尚未索引归档调用',
+  'All calls loaded': '已加载全部调用',
+  'Rows to load': '加载记录数',
+  'Rows to load slider': '加载记录数滑块',
+  'Row loading progress': '记录加载进度',
+  'All effort': '全部推理强度',
+  'All confidence': '全部置信度',
+  'All models': '全部模型',
+  'All sources': '全部来源',
+  'Exact cost': '精确成本',
+  'Estimated cost': '估算成本',
+  'Unpriced cost': '未定价成本',
+  'Exact credit': '精确点数',
+  'Estimated credit': '估算点数',
+  'Credit override': '点数费率覆盖值',
+  'Missing credit': '缺少点数费率',
+  'Exact credit rate': '精确点数费率',
+  'Estimated credit mapping': '估算点数映射',
+  'User credit override': '用户点数费率覆盖值',
+  'Missing credit rate': '缺少点数费率',
+  'This week': '本周',
+  'This month': '本月',
+  'Custom range': '自定义范围',
+  'Scope accounting categories': '范围统计分类',
+  'Loaded accounting categories': '已加载数据统计分类',
+  'To': '去向',
+  'Basis': '依据',
+  'More filters': '更多筛选条件',
+  'Project / cwd': '项目 / 工作目录',
+  'Session-linked': '关联会话',
+  'Git metadata': 'Git 元数据',
+  'Source file': '源文件',
+  'Missing source': '缺少来源信息',
+  'Start': '开始日期',
+  'End': '结束日期',
+  'Sort': '排序',
+  'Direction': '方向',
+  'Ascending': '升序',
+  'Descending': '降序',
+  'Loading...': '正在加载…',
+  'Refreshing...': '正在刷新…',
+  'Loading more...': '正在加载更多…',
+  'Loading evidence': '正在加载证据',
+  'Updating focused rows': '正在更新聚焦记录',
+  'Loading focused rows': '正在加载聚焦记录',
+  'Focused paged API': '聚焦分页 API',
+  'Focused endpoints': '聚焦接口',
+  'Partial endpoint evidence': '部分接口证据',
+  'Multiple searches use loaded snapshot': '多个搜索条件将使用已加载的快照',
+  'Preset uses loaded snapshot': '预设将使用已加载的快照',
+  'Source filter uses loaded snapshot': '来源筛选将使用已加载的快照',
+  'Risk filter uses loaded snapshot': '风险筛选将使用已加载的快照',
+  'This sort uses loaded snapshot': '此排序将使用已加载的快照',
+  'Date range invalid': '日期范围无效',
+  'Custom date range': '自定义日期范围',
+  'not available in filtered view': '筛选后的视图中不可用',
+  'not available in payload': '数据中不可用',
+  'filtered aggregate rows': '筛选后的聚合记录',
+  'local pricing config': '本地定价配置',
+  'privacy-safe estimate': '隐私安全估算',
+  'loaded calls matching filters': '符合筛选条件的已加载调用',
+  'legacy shell filters': '旧版全局筛选条件',
+  'active history': '活动记录',
+  'all history': '全部历史记录',
+  'call rows': '调用记录',
+  'settings rows': '设置记录',
+  'complete selected scope': '完整的所选范围',
+  'healthy cache reuse': '缓存复用良好',
+  'cache risk': '缓存风险',
+  'static snapshot': '静态快照',
+  'no cap': '不设上限',
+
+  // Shared components and environment state.
+  'Click opens full investigator. Hover or press Space previews details.': '单击打开完整分析器；悬停或按空格键可预览详情。',
+  'Click to inspect details. Double-click or press Enter open full investigator.': '单击查看详情；双击或按 Enter 键打开完整分析器。',
+  'Click or press Enter open the full investigator.': '单击或按 Enter 键打开完整分析器。',
+  'Local API token present for refresh actions.': '已提供本机 API 令牌，可执行刷新操作。',
+  'Static embedded snapshot; live refresh is unavailable.': '当前为静态内嵌快照，无法实时刷新。',
+  'Codex credit rates': 'Codex 点数费率',
+  'Rate-card error': '费率表错误',
+  'Credit rates loaded': '已加载点数费率',
+  'No local allowance windows are configured.': '尚未配置本地限额窗口。',
+  'cwd redacted': '工作目录已脱敏',
+  'project names redacted': '项目名称已脱敏',
+  'git remote hidden': 'Git 远程地址已隐藏',
+  'relative cwd hidden': '相对工作目录已隐藏',
+  'git branch hidden': 'Git 分支已隐藏',
+  'tags hidden': '标签已隐藏',
+  'Estimated Credits': '估算点数',
+  'Estimated Cost': '估算成本',
+  'Usage Remaining': '剩余用量',
+  'Cache Hit Rate': '缓存命中率',
+  'Cache hit rate': '缓存命中率',
+  'Cache state': '缓存状态',
+  'Cache read': '缓存读取量',
+  'Cache/context': '缓存/上下文',
+  'mostly_codex': '主要由 Codex 发起',
+  'mostly_user': '主要由用户发起',
+  'mixed': '混合发起',
+  'Stop and summarize the failure mode before retrying commands.': '再次尝试命令前，请先停止操作并总结失败模式。',
+
+  // Overview.
+  'Usage summary': '用量摘要',
+  'Recommendations': '建议',
+  'Selected scope usage metrics': '所选范围的用量指标',
+  'No rule-based usage issue stands out': '未发现明显的规则型用量问题',
+  'Load calls to establish a usage baseline': '加载调用以建立用量基线',
+  'The Overview needs aggregate calls before it can rank evidence or build token accounting.': '“概览”需要先获得聚合调用，才能对证据排序并生成token统计。',
+  'Continue monitoring and investigate any workflow that feels unexpectedly expensive.': '继续监控，并调查任何成本异常偏高的工作流。',
+  'Load recent calls or all history.': '加载近期调用或全部历史记录。',
+  'Review the loaded aggregate evidence in Investigate.': '在“调查分析”中查看已加载的聚合证据。',
+  'Focused summary unavailable; showing loaded call rows.': '聚焦摘要不可用，当前显示已加载的调用记录。',
+  'Daily token movement': '每日token变化',
+  'Scope accounting': '范围统计',
+  'Loaded accounting': '已加载数据统计',
+  'calls in selected scope': '所选范围内的调用',
+  'loaded calls': '已加载调用',
+  'Token accounting in scope': '范围内token统计',
+  'The four reported token categories across the complete selected data scope.': '完整所选数据范围内日志报告的四类token统计。',
+  'Reported type': '报告类型',
+  'Input accounting': '输入统计',
+  'Generated accounting': '生成内容统计',
+  'calls in the selected scope': '所选范围内的调用',
+  'One ranked call supports this pattern.': '有 1 次已排序调用支持此模式。',
+  'all-history scope': '全部历史记录范围',
+  'active-history scope': '活动记录范围',
+  'No loaded calls are available for the usage constellation.': '没有可用于用量星图的已加载调用。',
+  'Unassigned thread': '未归属线程',
+  'Other models': '其他模型',
+  'Overview calls': '概览调用',
+  'Overview calls display controls': '概览调用显示控件',
+  'Overview calls ranked list': '概览调用排序列表',
+
+  // Calls and call investigator.
+  'Calls': '调用',
+  'Evidence explorer': '证据浏览器',
+  'Find expensive, cold, or context-heavy calls and move directly into their evidence.': '查找高成本、冷缓存或上下文负载较高的调用，并直接查看相关证据。',
+  'Copy view': '复制视图链接',
+  'Model calls': '模型调用',
+  'Call filters': '调用筛选器',
+  'Search calls': '搜索调用',
+  'Search calls, cwd, projects, models...': '搜索调用、工作目录、项目和模型…',
+  'Confidence': '置信度',
+  'Confidence filter': '置信度筛选器',
+  'Time filter': '时间筛选器',
+  'Source': '来源',
+  'Source filter': '来源筛选器',
+  'Start date': '开始日期',
+  'End date': '结束日期',
+  'Sort calls': '调用排序',
+  'Sort direction': '排序方向',
+  'Newest calls': '最新调用',
+  'Longest duration': '耗时最长',
+  'Longest gap': '间隔最长',
+  'Needs attention': '需要关注',
+  'Thread name': '线程名称',
+  'Usage Over Time': '用量趋势',
+  'Cost by Model': '按模型统计成本',
+  'Estimated USD': '估算美元成本',
+  'Cache Hit Rate Over Time': '缓存命中率趋势',
+  'Cache %': '缓存比例',
+  'Usage patterns': '用量模式',
+  'Raw context gated': '原始上下文受控',
+  'Call Drill-Down': '调用深入分析',
+  'No matching call': '没有匹配的调用',
+  'Not available': '不可用',
+  'Not reported': '未报告',
+  'No aggregate row matches the active filters.': '没有符合当前筛选条件的聚合记录。',
+  'Aggregate only': '仅聚合数据',
+  'Call drill-down sections': '调用深入分析区域',
+  'Total tokens': 'token总数',
+  'fresh billed input': '新增计费输入',
+  'Fresh share': '新增输入占比',
+  'Loaded thread calls': '已加载的线程调用',
+  'Thread tokens': '线程token数',
+  'loaded aggregate rows': '已加载的聚合记录',
+  'Thread cost': '线程成本',
+  'estimated aggregate': '聚合估算',
+  'Avg cache': '平均缓存比例',
+  'Initiated by': '发起方',
+  'Initiator reason': '发起原因',
+  'Previous gap': '与上次调用的间隔',
+  'Project path': '项目路径',
+  'Working directory': '工作目录',
+  'Git remote': 'Git 远程地址',
+  'Git hash': 'Git 哈希',
+  'Token composition': 'token构成',
+  'Cache delta readout': '缓存变化解读',
+  'Accounting Snapshot': '统计快照',
+  'pricing, credits, and cache savings': '定价、点数与缓存节省',
+  'Use this readout to decide whether the aggregate call needs deeper raw-context investigation.': '根据此解读判断是否需要进一步调查该聚合调用的原始上下文。',
+  'Call Narrative': '调用解读',
+  'Call Source': '调用来源',
+  'Direct thread': '直接线程',
+  'No model mix': '没有模型构成数据',
+  'no model mix': '没有模型构成数据',
+  'not reported': '未报告',
+  'no parent session': '没有父会话',
+  'aggregate inference': '聚合推断',
+  'estimated pricing': '估算定价',
+  'configured pricing': '已配置定价',
+  'fast candidate': '可快速处理',
+  'normal throughput': '吞吐量正常',
+  'Investigation Readout': '调查解读',
+  'Aggregate + on-demand evidence': '聚合数据与按需证据',
+  'No aggregate recommendation': '没有聚合建议',
+  'Compared previous call': '已与上一次调用比较',
+  'This call is outside the loaded snapshot. Serve the dashboard with its localhost API token to hydrate it.': '此调用不在已加载的快照中。请使用本机 API 令牌运行仪表盘，以补载其数据。',
+  'Loading call detail from localhost...': '正在从本机服务加载调用详情…',
+  'Selected call is not present in the loaded dashboard rows.': '已加载的仪表盘记录中没有所选调用。',
+  'No aggregate call rows are loaded.': '尚未加载聚合调用记录。',
+  'Hydrated live': '已实时补载',
+  'Hydrated from /api/call': '已从 /api/call 补载',
+  'Record outside loaded snapshot': '记录位于已加载快照之外',
+  'Position: hydrated live record outside loaded snapshot': '位置：已实时补载，记录位于已加载快照之外',
+  'Token Accounting': 'token统计',
+  'Exact aggregate row fields': '精确的聚合记录字段',
+  'Cache Accounting': '缓存统计',
+  'Derived from adjacent aggregate call': '根据相邻聚合调用推导',
+  'Context Attribution': '上下文归因',
+  'Local metadata only': '仅本地元数据',
+  'Thread Context': '线程上下文',
+  'Raw Evidence': '原始证据',
+  'Explicit localhost request only': '仅在明确请求本机服务时加载',
+  'Context mode': '上下文模式',
+  'Context entries': '上下文条目',
+  'Side panel context mode': '侧栏上下文模式',
+  'Side panel context entries': '侧栏上下文条目',
+  'Visible chars': '可见字符数',
+  'redacted local text': '已脱敏的本地文本',
+  'Visible tokens': '可见token数',
+  'Older omitted': '已省略较早条目',
+  'entry budget': '条目预算',
+  'Thread calls': '线程调用数',
+  'Cache risks': '缓存风险',
+  'weak reuse or flagged': '复用较弱或已标记',
+  'Context pressure': '上下文压力',
+  '>=60% context window': '上下文窗口占用不低于 60%',
+  'Models in thread': '线程中的模型',
+  'Effort mix': '推理强度构成',
+  'Enabling localhost context API...': '正在启用本机上下文 API…',
+  'Context API enabled. Load this call when ready.': '上下文 API 已启用，可以加载此调用。',
+  'Context API did not enable.': '未能启用上下文 API。',
+  'Loading selected-turn evidence...': '正在加载所选轮次的证据…',
+  'Loading full turn analysis...': '正在加载完整轮次分析…',
+  'Loading older context...': '正在加载更早的上下文…',
+  'Loading omitted tool output...': '正在加载已省略的工具输出…',
+  'Loading compacted replacement...': '正在加载压缩后的替换内容…',
+  'local evidence': '本地证据',
+  '[no visible text]': '[没有可见文本]',
+  '[no visible replacement text]': '[没有可见的替换文本]',
+  'Raw context is never embedded in the dashboard HTML. This view reads the selected local JSONL turn only after an explicit request.': '原始上下文绝不会嵌入仪表盘 HTML；只有明确请求后，此视图才会读取本地 JSONL 中所选轮次的内容。',
+  'Raw context is read from the local JSONL source only after this explicit action and is not embedded in static dashboard HTML.': '只有执行此明确操作后才会从本地 JSONL 源读取原始上下文，并且不会将其嵌入静态仪表盘 HTML。',
+  'No visible evidence entries returned for this call.': '此调用没有返回可见的证据条目。',
+  'Static file mode cannot read local JSONL context. Use serve-dashboard with the context API enabled.': '静态文件模式无法读取本地 JSONL 上下文。请运行 serve-dashboard 并启用上下文 API。',
+  'Context loading requires the localhost dashboard server API token.': '加载上下文需要本机仪表盘服务器的 API 令牌。',
+  'Context API is available but off. Enable it here before loading selected-turn evidence.': '上下文 API 可用但尚未启用；请先在此启用，再加载所选轮次的证据。',
+  'Context API is enabled. Load selected-turn evidence from the local JSONL source only when needed.': '上下文 API 已启用；仅在需要时从本地 JSONL 源加载所选轮次的证据。',
+  'Local JSONL context loaded on demand.': '已按需加载本地 JSONL 上下文。',
+  'No previous call is loaded in resolved thread, call-to-call deltas unavailable.': '解析出的线程中未加载上一次调用，因此无法计算调用间变化。',
+  'Token accounting broadly stable compared previous call in resolved thread.': '与解析出的线程中上一次调用相比，token统计整体稳定。',
+  'Evidence is not loaded yet. Aggregate token counts are exact, but visible-context attribution needs runtime evidence.': '尚未加载证据。聚合token数是精确值，但可见上下文归因需要运行时证据。',
+  'Fast serialized estimate only; full serialized grouping deferred.': '当前仅提供快速序列化估算；完整的序列化分组尚未执行。',
+  'Compare previous call, then inspect loaded evidence see fresh context was sent after cache miss.': '先与上一次调用比较，再检查已加载证据，确认缓存未命中后发送了哪些新增上下文。',
+  'Inspect most recent evidence entries first; spike is in fresh uncached input, not cached history.': '请先检查最新的证据条目；峰值来自新增的未缓存输入，而不是缓存历史。',
+  'Use delta cards to locate whether change came from cached input, uncached input, or output/reasoning.': '使用变化卡片判断差异来自缓存输入、未缓存输入，还是输出/推理。',
+  'Use loaded evidence if aggregate totals are not enough understand this isolated call.': '如果聚合总量不足以解释此调用，请查看已加载证据。',
+  'visible-token estimate': '可见token估算',
+  'Raw context is gated': '原始上下文受控',
+  'Include compaction history': '包含压缩历史',
+  'Record id': '记录 ID',
+  'Entry tokens': '条目token数',
+  'Session tokens': '会话token数',
+  'Tool output': '工具输出',
+  'Evidence entry metadata': '证据条目元数据',
+  'Elapsed since selected turn start': '自所选轮次开始后的耗时',
+  'Gap since previous evidence entry': '与上一条证据的间隔',
+  'Duration reported by this event': '此事件报告的耗时',
+  'Token usage reported for this evidence entry': '此证据条目报告的token用量',
+  'Cumulative token usage reported by this evidence entry': '此证据条目报告的累计token用量',
+  'Compaction replacement history is available for this entry': '此条目有可用的压缩替换历史',
+  'Tool output omitted until explicitly requested': '工具输出已省略，明确请求后才会加载',
+  'No previous call': '没有上一次调用',
+  'No previous call loaded for delta comparison.': '尚未加载可用于变化对比的上一次调用。',
+  'No previous aggregate call available for cache delta accounting.': '没有可用于缓存变化统计的上一次聚合调用。',
+  'Some prefix reused cache, but a meaningful share of input was fresh or reserialized.': '部分前缀复用了缓存，但仍有相当比例的输入为新增内容或重新序列化内容。',
+  'Cache accounting is stable versus the previous aggregate call.': '与上一次聚合调用相比，缓存统计基本稳定。',
+  'Compare the previous call, then inspect loaded evidence to see what fresh context was sent after the cache miss.': '先与上一次调用比较，再检查已加载证据，确认缓存未命中后发送了哪些新增上下文。',
+  'Use delta cards to locate whether the change came from cached input, uncached input, or output/reasoning.': '使用变化卡片判断差异来自缓存输入、未缓存输入，还是输出/推理。',
+  'Use loaded evidence if aggregate totals are not enough to understand this isolated call.': '如果聚合总量不足以解释此调用，请查看已加载证据。',
+  'Cache Accounting Delta': '缓存统计变化',
+  'Not loaded yet': '尚未加载',
+  'Runtime evidence': '运行时证据',
+  'exact aggregate row': '精确聚合记录',
+  'serialized-breakdown deferred': '序列化明细尚未生成',
+  'uncached input minus visible estimate': '未缓存输入减去可见内容估算值',
+  'serialized upper bound minus visible estimate': '序列化上限减去可见内容估算值',
+  'not covered by serialized upper bound': '序列化上限未覆盖的部分',
+  'No serialized evidence groups returned.': '没有返回序列化证据分组。',
+  'Configure pricing': '配置定价',
+  'Compare fresh input': '比较新增输入',
+  'Inspect thread timeline': '查看线程时间线',
+  'Review reasoning effort': '检查推理强度',
+  'Use aggregate first': '先查看聚合数据',
+  'High reported context use.': '报告的上下文占用较高。',
+  'Reasoning output exceeds visible output.': '推理输出超过可见输出。',
+  'Review cost and credit impact before loading raw context.': '加载原始上下文前，请先检查成本和点数影响。',
+  'No aggregate efficiency flag on this row.': '此记录没有聚合效率标记。',
+  'Call Decision': '调用决策',
+  'cold or weak cache': '缓存未命中或复用较弱',
+  'partial cache reuse': '部分缓存复用',
+  'No related calls': '没有相关调用',
+  'Highest Cost Threads': '成本最高的线程',
+  'Context Bloat': '上下文膨胀',
+  'Cache Misses': '缓存未命中',
+  'Pricing Gaps': '定价缺口',
+  'Reasoning Spike': '推理峰值',
+  'Output Tokens': '输出token',
+  'Est. Cost': '估算成本',
+  'Codex Credits': 'Codex 点数',
+  'Effort Mix': '推理强度构成',
+
+  // Explore workspaces.
+  'Explore workspace': '浏览工作区',
+  'File evidence': '文件证据',
+  'Tool evidence': '工具证据',
+  'File filters': '文件筛选器',
+  'Tool filters': '工具筛选器',
+  'Search file evidence': '搜索文件证据',
+  'Search tool evidence': '搜索工具证据',
+  'Search path labels and exact path hashes...': '搜索路径标签和精确路径哈希…',
+  'Search tools, categories, and actions...': '搜索工具、类别和操作…',
+  'File evidence results': '文件证据结果',
+  'Tool evidence results': '工具证据结果',
+  'File evidence results display controls': '文件证据结果显示控件',
+  'Tool evidence results display controls': '工具证据结果显示控件',
+  'File evidence results ranked list': '文件证据结果排序列表',
+  'Tool evidence results ranked list': '工具证据结果排序列表',
+  'File inspector': '文件检查器',
+  'Tool inspector': '工具检查器',
+  'No evidence selected': '尚未选择证据',
+  'No representative call': '没有代表性调用',
+  'Select a file row to inspect its aggregate activity.': '选择一条文件记录以查看其聚合活动。',
+  'Select a tool row to inspect its aggregate evidence.': '选择一条工具记录以查看其聚合证据。',
+  'Find repeated reads and modifications using local aggregate path labels and stable path hashes.': '利用本地聚合路径标签和稳定路径哈希查找重复读取与修改。',
+  'Rank tool and function activity by associated token pressure, then inspect the calls behind each pattern.': '按关联token压力对工具和函数活动排序，再查看每种模式背后的调用。',
+  'No file evidence is available in the stored diagnostic snapshots.': '已存储的诊断快照中没有文件证据。',
+  'No tool evidence matches the active filters.': '没有符合当前筛选条件的工具证据。',
+  'File evidence requires the localhost dashboard server.': '文件证据需要本机仪表盘服务器。',
+  'Tool evidence requires the localhost dashboard server.': '工具证据需要本机仪表盘服务器。',
+  'Local server required': '需要本机服务器',
+  'Updating file snapshots': '正在更新文件快照',
+  'Loading file snapshots': '正在加载文件快照',
+  'File snapshots unavailable': '文件快照不可用',
+  'Stored diagnostic snapshots': '已存储的诊断快照',
+  'No file snapshots loaded': '尚未加载文件快照',
+  'Updating tool facts': '正在更新工具事实',
+  'Loading tool facts': '正在加载工具事实',
+  'Tool facts unavailable': '工具事实不可用',
+  'Focused diagnostic API': '聚焦诊断 API',
+  'No tool facts loaded': '尚未加载工具事实',
+  'Path Hash': '路径哈希',
+  'Path Label': '路径标签',
+  'Read Events': '读取事件数',
+  'Read Output': '读取输出',
+  'Allocated Read Output Tokens': '分配的读取输出token数',
+  'Modification Events': '修改事件数',
+  'Path hash': '路径哈希',
+  'Read evidence': '读取证据',
+  'Modification evidence': '修改证据',
+  'Read events': '读取事件数',
+  'Read output': '读取输出',
+  'Open evidence call': '打开证据调用',
+  'Path hashes provide stable local identity for repeated rediscovery without placing raw file content in the aggregate response.': '路径哈希可为重复发现提供稳定的本地标识，同时避免在聚合响应中包含原始文件内容。',
+  'Uncached Input Tokens': '未缓存输入token数',
+  'Cache Percent': '缓存比例',
+  'Largest Call': '最大调用',
+  'Associated Calls': '关联调用数',
+  'Associated calls': '关联调用',
+  'Cache reuse': '缓存复用率',
+  'Largest call': '最大调用',
+  'Open largest call': '打开最大调用',
+  'Supporting calls': '支撑调用',
+  'No supporting call rows are loaded for this tool fact.': '尚未加载此工具事实对应的支撑调用记录。',
+  'tool activity': '工具活动',
+  'Unknown path': '未知路径',
+  'Visible columns': '可见列',
+  'No evidence matches the current filters.': '没有符合当前筛选条件的证据。',
+
+  // Threads.
+  'Threads': '线程',
+  'Thread Leaderboard': '线程排行榜',
+  'Thread leaderboard': '线程排行榜',
+  'Compare work units, follow lifecycle pressure, and open supporting calls without leaving the evidence surface.': '比较工作单元、跟踪生命周期压力，并在证据页面中直接打开支撑调用。',
+  'Thread filters': '线程筛选器',
+  'Search threads': '搜索线程',
+  'Search threads, risks, token totals...': '搜索线程、风险和token总量…',
+  'Cold risk': '冷恢复风险',
+  'All risks': '全部风险',
+  'Cache frontier': '缓存效率前沿',
+  'Updating thread calls': '正在更新线程调用',
+  'Updating focused threads': '正在更新聚焦线程',
+  'Loading focused threads': '正在加载聚焦线程',
+  'Reset thread view': '重置线程视图',
+  'Loading thread summaries and selected calls': '正在加载线程摘要和所选调用',
+  'Thread evidence view': '线程证据视图',
+  'Thread evidence': '线程证据',
+  'Thread evidence display controls': '线程证据显示控件',
+  'Thread evidence ranked list': '线程证据排序列表',
+  'Export thread calls': '导出线程调用',
+  'Reset view': '重置视图',
+  'Selected Thread': '所选线程',
+  'No matching thread': '没有匹配的线程',
+  'No grouped thread matches the active filters.': '没有符合当前筛选条件的分组线程。',
+  'Thread Calls': '线程调用',
+  'No loaded calls': '没有已加载的调用',
+  'Loading more calls': '正在加载更多调用',
+  'No loaded aggregate call rows belong to this thread.': '此线程没有已加载的聚合调用记录。',
+  'Turns visible': '可见轮次数',
+  'Total duration': '总耗时',
+  'Average gap': '平均间隔',
+  'Cached / uncached input': '缓存 / 未缓存输入',
+  'Peak context': '上下文峰值',
+  'Risk Mix': '风险构成',
+  'Productivity': '生产效率',
+  'Thread Status': '线程状态',
+  'Pricing status': '定价状态',
+  'Credit status': '点数状态',
+  'Cache ratio': '缓存比例',
+  'Max context use': '最大上下文占用',
+  'Thread Impact': '线程影响',
+  'Codex credits': 'Codex 点数',
+  'Allowance impact': '限额影响',
+  'Attention score': '关注度评分',
+  'Cost per call': '单次调用成本',
+  'Thread Lifecycle': '线程生命周期',
+  'Subagent before spike': '峰值前出现子代理',
+  'Aggregate trend': '聚合趋势',
+  'First expensive turn': '首次高成本轮次',
+  'Largest token jump': '最大token增幅',
+  'Cache trend': '缓存趋势',
+  'Context trend': '上下文趋势',
+  'Relationships': '关系',
+  'Loaded aggregate links': '已加载的聚合关联',
+  'Spawned from': '派生自',
+  'Subagent calls': '子代理调用',
+  'Auto-review calls': '自动审查调用',
+  'Attached calls': '附加调用',
+  'Spawned threads': '派生线程',
+  'Spawned child calls': '派生子调用',
+  'Thread Fields': '线程字段',
+  'Latest activity': '最近活动',
+  'Loaded calls': '已加载调用',
+  'Efficiency signals': '效率信号',
+  'Model mix': '模型构成',
+  'Sort thread calls': '线程调用排序',
+  'Sort thread calls direction': '线程调用排序方向',
+  'Newest': '最新',
+  'Most tokens': 'token最多',
+  'Highest cost': '成本最高',
+  'Lowest cache': '缓存比例最低',
+  'Avg Gap': '平均间隔',
+  'Cost / Call': '单次调用成本',
+  'Cold Resume Risk': '冷恢复风险',
+  'Latest': '最近活动',
+  'Turns': '轮次',
+  'High': '高',
+  'Medium': '中',
+  'Low': '低',
+  'Official match': '官方精确匹配',
+  'Mixed': '混合匹配',
+  'Configured': '已配置',
+  'Estimated mapping': '估算映射',
+  'No mapped rate': '没有匹配的费率',
+  'No price': '无定价',
+  'Cache Drop': '缓存下降',
+  'Cache Risk': '缓存风险',
+  'Context Heavy': '上下文负载高',
+  'Elevated Context': '上下文偏高',
+  'Elevated Context Use': '上下文占用偏高',
+  'Estimated Pricing': '估算定价',
+  'Expensive Low Output Call': '高成本低输出调用',
+  'High Context Use': '上下文占用高',
+  'High Cost': '高成本',
+  'High Estimated Cost': '估算成本高',
+  'High Reasoning Share': '推理占比高',
+  'Large Thread': '大型线程',
+  'Low Cache': '缓存偏低',
+  'Low Cache Reuse': '缓存复用率低',
+  'Low Output': '输出偏低',
+  'Pricing Gap': '定价缺口',
+  'Subagent Attribution': '子智能体归因',
+  'Review context growth': '检查上下文增长',
+  'Check cache drop': '检查缓存下降',
+  'Compare subagent calls': '比较子代理调用',
+  'Review recommendations': '查看建议',
+  'Load thread calls': '加载线程调用',
+  'Cache efficiency frontier': '缓存效率前沿',
+  'Threads further right carry more input; threads lower on the plot reuse less of it.': '越靠右的线程输入量越大；图中位置越低，缓存复用越少。',
+  'No threads match the current scope.': '没有符合当前范围的线程。',
+  'Credits and cost remain estimates when exact rate metadata is unavailable.': '如果没有精确费率元数据，点数和成本仍为估算值。',
+  'Use arrow keys to move between threads; press Enter to synchronize the selected row.': '使用方向键在线程间移动；按 Enter 键同步所选记录。',
+  'Cache efficiency by thread': '各线程缓存效率',
+  '35% review floor': '35% 检查阈值',
+  'Context pressure and cache reuse across the selected thread.': '所选线程的上下文压力与缓存复用情况。',
+  'Context-window evidence is unavailable for this thread.': '此线程没有可用的上下文窗口证据。',
+  'No thread selected': '尚未选择线程',
+  'Lifecycle labels are inferred from aggregate timing, cache, and context fields.': '生命周期标签根据聚合耗时、缓存和上下文字段推断。',
+  'Use left and right arrow keys to move through calls in lifecycle order.': '使用左右方向键按生命周期顺序浏览调用。',
+  'Selected thread lifecycle calls': '所选线程的生命周期调用',
+  'Lifecycle event': '生命周期事件',
+  'Minutes since first call': '距首次调用的分钟数',
+  'Context / cache': '上下文 / 缓存',
+  'No loaded high-token thread falls below the 35 percent cache review floor.': '没有已加载的高token线程低于 35% 的缓存检查阈值。',
+  'the selected thread': '所选线程',
+  'Thread start': '线程开始',
+  'Cold resume': '冷恢复',
+  'Warm continuation': '热缓存延续',
+};
+
+export const corePagesZhHansPatterns: ReadonlyArray<ZhHansPattern> = [
+  { pattern: /^(Today|This week|Last 7 days|This month): (\d{4}-\d{2}-\d{2}) to (\d{4}-\d{2}-\d{2})$/u, replace: (_match, preset, start, end) => `${datePresetZhHans(preset)}：${start} 至 ${end}` },
+  { pattern: /^Custom: (\d{4}-\d{2}-\d{2}) to (\d{4}-\d{2}-\d{2})$/u, replace: '自定义：$1 至 $2' },
+  { pattern: /^Custom: from (\d{4}-\d{2}-\d{2})$/u, replace: '自定义：从 $1 开始' },
+  { pattern: /^Custom: through (\d{4}-\d{2}-\d{2})$/u, replace: '自定义：截至 $1' },
+  // Shell progress and history counts.
+  { pattern: /^Auto refresh every ([\d,.]+)s$/u, replace: '每 $1 秒自动刷新' },
+  { pattern: /^All history includes ([\d,.]+) archived calls$/u, replace: '全部历史记录包含 $1 次归档调用' },
+  { pattern: /^Active sessions only; ([\d,.]+) archived calls hidden$/u, replace: '仅活动会话；已隐藏 $1 次归档调用' },
+  { pattern: /^([\d,.]+) detail rows? cached$/u, replace: '已缓存 $1 条详情记录' },
+  { pattern: /^([\d,.]+) loaded \/ ([\d,.]+) total$/u, replace: '已加载 $1 / 共 $2 条' },
+  { pattern: /^([\d,.]+) of ([\d,.]+) evidence rows loaded$/u, replace: '已加载 $1 / $2 条证据记录' },
+  { pattern: /^([\d,.]+) recent rows$/u, replace: '$1 条近期记录' },
+  { pattern: /^([\d,.]+)% loaded$/u, replace: '已加载 $1%' },
+  { pattern: /^(Loading|Refreshing) (24 hours|7 days|recent rows|all time)\.\.\.$/u, replace: (_match, action, scope) => `${action === 'Refreshing' ? '正在刷新' : '正在加载'}${scopeZhHans(scope)}…` },
+  { pattern: /^Refreshing index for (24 hours|7 days|recent rows|all time)\.\.\.$/u, replace: (_match, scope) => `正在刷新${scopeZhHans(scope)}的索引…` },
+  { pattern: /^(Cache hit; |Refreshed index; )?[Ll]oaded ([\d,.]+) of ([\d,.]+) calls from (24 hours|7 days|recent rows|all time)$/u, replace: (_match, prefix, loaded, total, scope) => `${refreshPrefixZhHans(prefix)}已从${scopeZhHans(scope)}加载 ${loaded} / ${total} 次调用` },
+  { pattern: /^(Cache hit; |Refreshed index; )?(24 hours|7 days|recent rows|all time) analysis ready across ([\d,.]+) calls; ([\d,.]+) detail rows cached$/iu, replace: (_match, prefix, scope, total, cached) => `${refreshPrefixZhHans(prefix)}${scopeZhHans(scope.toLowerCase())}分析已就绪，共 ${total} 次调用；已缓存 ${cached} 条详情记录` },
+  { pattern: /^(.+) Stored snapshot kept at (.+)$/u, replace: '$1 已保留 $2 的存储快照' },
+  { pattern: /^Metadata mode: (.+)$/u, replace: '元数据模式：$1' },
+  { pattern: /^Config error: (.+)$/u, replace: '配置错误：$1' },
+  { pattern: /^Rate-card error: (.+)$/u, replace: '费率表错误：$1' },
+  { pattern: /^Deduped · ([\d,.]+) copied excluded$/u, replace: '已去重 · 排除 $1 条重复记录' },
+  { pattern: /^Billable totals use ([\d,.]+) canonical rows while preserving ([\d,.]+) physical source rows\.$/u, replace: '计费总量使用 $1 条规范记录，同时保留 $2 条物理来源记录。' },
+
+  // Overview summaries and visualization narration.
+  { pattern: /^([\d,.]+) detailed rows available$/u, replace: '有 $1 条详情记录可用' },
+  { pattern: /^([\d,.]+) daily buckets are available, with the visible window favoring the most recent ([\d,.]+)\.$/u, replace: '共有 $1 个每日时间桶，当前视图优先显示最近 $2 个。' },
+  { pattern: /^([\d,.]+) (loaded calls|calls in selected scope|calls in the selected scope)$/u, replace: (_match, count, scope) => `${count} 次${scope === 'loaded calls' ? '已加载调用' : '所选范围内调用'}` },
+  { pattern: /^([\d,.]+) (loaded calls|calls in selected scope|calls in the selected scope) include ([\d,.]+) percent cached input reuse\.$/u, replace: (_match, count, scope, percent) => `${scope === 'loaded calls' ? '已加载的' : '所选范围内的'} ${count} 次调用中，缓存输入复用率为 ${percent}%。` },
+  { pattern: /^([\d,.]+) ranked calls support this pattern\.$/u, replace: '有 $1 次已排序调用支持此模式。' },
+  { pattern: /^((?:low|medium|high|xhigh|ultra|max) x[\d,]+(?:, (?:low|medium|high|xhigh|ultra|max) x[\d,]+)*)$/u, replace: (_match, summary) => effortSummaryZhHans(summary) },
+  { pattern: /^([\d,.]+(?:[KMBT])?) at (.+)$/iu, replace: '$1，发生于 $2' },
+  { pattern: /^(.+) · Call ([\d,.]+)$/u, replace: '$1 · 第 $2 次调用' },
+  { pattern: /^([\d,.]+(?:\.\d+)?) credits \((Official match|Mixed|Configured|Estimated mapping|No mapped rate|No price)\)$/u, replace: (_match, credits, status) => `${credits} 点（${threadStatusZhHans(status)}）` },
+  { pattern: /^([\d,.]+(?:[KMBT])?) tokens - ([\d,.]+(?:\.\d+)?)% cache - (.+)$/iu, replace: '$1 个token - 缓存 $2% - $3' },
+  { pattern: /^([\d,.]+(?:[KMBT])?) tokens - ([\d,.]+(?:\.\d+)?)% cache$/iu, replace: '$1 个token - 缓存 $2%' },
+  { pattern: /^Context ([\d,.]+(?:\.\d+)?)%$/iu, replace: '上下文 $1%' },
+  { pattern: /^Prev ([\d,.]+)m ([\d,.]+)s$/iu, replace: '距上次 $1 分 $2 秒' },
+  { pattern: /^Prev ([\d,.]+)s$/iu, replace: '距上次 $1 秒' },
+  { pattern: /^Prev (.+)$/iu, replace: '距上次 $1' },
+  { pattern: /^(.+) initiated$/iu, replace: '$1 发起' },
+  { pattern: /^(.+) is the clearest current signal$/u, replace: '当前最明确的信号是：$1' },
+  { pattern: /^([\d,.]+) representative calls from ([\d,.]+) loaded calls$/u, replace: '从 $2 次已加载调用中选取 $1 次代表性调用' },
+  { pattern: /^The constellation plots ([\d,.]+) loaded calls\. The largest plotted call used ([\d,.]+) tokens\. The lowest plotted cache reuse was ([\d,.]+) percent\.$/u, replace: '星图展示了 $1 次已加载调用。图中最大调用使用 $2 个token，最低缓存复用率为 $3%。' },
+  { pattern: /^The constellation plots ([\d,.]+) representative calls from ([\d,.]+) loaded calls\. The largest plotted call used ([\d,.]+) tokens\. The lowest plotted cache reuse was ([\d,.]+) percent\.$/u, replace: '星图从 $2 次已加载调用中展示 $1 次代表性调用。图中最大调用使用 $3 个token，最低缓存复用率为 $4%。' },
+
+  // Calls, evidence, and context counts. Captured labels and identifiers are preserved verbatim.
+  { pattern: /^Showing ([\d,.]+) of ([\d,.]+) aggregate rows$/u, replace: '显示 $1 / $2 条聚合记录' },
+  { pattern: /^([\d,.]+) project\/cwd rows$/u, replace: '$1 条项目/工作目录记录' },
+  { pattern: /^([\d,.]+) session-linked rows$/u, replace: '$1 条会话关联记录' },
+  { pattern: /^([\d,.]+) git rows$/u, replace: '$1 条 Git 记录' },
+  { pattern: /^([\d,.]+) source-file rows$/u, replace: '$1 条源文件记录' },
+  { pattern: /^([\d,.]+) rows missing source$/u, replace: '$1 条缺少来源信息的记录' },
+  { pattern: /^([\d,.]+) project, ([\d,.]+) session, ([\d,.]+) git$/u, replace: '项目 $1 条，会话 $2 条，Git $3 条' },
+  { pattern: /^Preset: (Highest Cost Threads|Context Bloat|Cache Misses|Pricing Gaps|Codex Credits|Reasoning Spike)$/u, replace: (_match, preset) => `预设：${presetZhHans(preset)}` },
+  { pattern: /^Exported ([\d,.]+) calls$/u, replace: '已导出 $1 次调用' },
+  { pattern: /^Exported ([\d,.]+) loaded calls$/u, replace: '已导出 $1 次已加载调用' },
+  { pattern: /^([\d,.]+) of ([\d,.]+) loaded calls$/u, replace: '第 $1 次，共 $2 次已加载调用' },
+  { pattern: /^([\d,.]+) loaded related calls$/u, replace: '已加载 $1 次相关调用' },
+  { pattern: /^selected ([\d,.]+) of ([\d,.]+)$/u, replace: '已选择第 $1 个，共 $2 个' },
+  { pattern: /^Call ([\d,.]+) of ([\d,.]+)$/u, replace: '调用 $1 / $2' },
+  { pattern: /^Entry ([\d,.]+)$/u, replace: '条目 $1' },
+  { pattern: /^line ([\d,.]+)$/u, replace: '第 $1 行' },
+  { pattern: /^Show first ([\d,.]+) entries$/u, replace: '显示前 $1 个条目' },
+  { pattern: /^Show all ([\d,.]+) returned entries$/u, replace: '显示返回的全部 $1 个条目' },
+  { pattern: /^Replacement item ([\d,.]+)$/u, replace: '替换项 $1' },
+  { pattern: /^([\d,.]+) replacement entries$/u, replace: '$1 个替换条目' },
+  { pattern: /^([\d,.]+(?:[KMBT])?) total · ([\d,.]+(?:[KMBT])?) uncached$/iu, replace: '共 $1 个 · 未缓存 $2 个' },
+  { pattern: /^([\d,.]+) older entries omitted\.$/u, replace: '已省略 $1 个较早条目。' },
+  { pattern: /^([\d,.]+) chars over budget omitted\.$/u, replace: '已省略超出预算的 $1 个字符。' },
+  { pattern: /^Source: (.+)\.$/u, replace: '来源：$1。' },
+  { pattern: /^Evidence request failed: (.+)$/u, replace: '证据请求失败：$1' },
+  { pattern: /^Evidence analyzed: ([\d,.]+) selected-turn entries, ([\d,.]+) visible redacted chars, ([\d,.]+) visible tokens\.(.*)$/u, replace: '已分析证据：所选轮次包含 $1 个条目、$2 个可见脱敏字符和 $3 个可见token。$4' },
+  { pattern: /^Serialized local upper bound: ([\d,.]+) tokens\.$/u, replace: '本地序列化上限：$1 个token。' },
+  { pattern: /^Position: (.+)$/u, replace: '位置：$1' },
+  { pattern: /^([\d,.]+) analyzed chars$/u, replace: '已分析 $1 个字符' },
+  { pattern: /^([\d,.]+) raw JSON chars$/u, replace: '$1 个原始 JSON 字符' },
+  { pattern: /^([\d,.]+) raw lines$/u, replace: '$1 行原始内容' },
+  { pattern: /^([\d,.]+) credits counted$/u, replace: '计入 $1 点' },
+  { pattern: /^([\d,.]+) credits$/u, replace: '$1 点' },
+  { pattern: /^([\d,.]+(?:[KMBT])?) uncached input with weak cache reuse\.$/iu, replace: '$1 个未缓存输入token，缓存复用较弱。' },
+  { pattern: /^Fresh input rose by ([\d,.]+) while cached input fell by ([\d,.]+); classic cache-drop profile\.$/u, replace: '新增输入增加 $1，而缓存输入减少 $2；这是典型的缓存下降特征。' },
+  { pattern: /^Fresh input increased by ([\d,.]+) from previous call; inspect evidence new files, tool results, or rewritten context\.$/u, replace: '与上一次调用相比，新增输入增加 $1；请检查证据中的新文件、工具结果或重写的上下文。' },
+  { pattern: /^Fresh input fell by ([\d,.]+) while cached input increased, so this call reused context more efficiently previous one\.$/u, replace: '新增输入减少 $1，同时缓存输入增加，因此此调用比上一次更高效地复用了上下文。' },
+  { pattern: /^Cache reuse is healthy; focus on ([\d,.]+) uncached tokens (?:were|that were) still billed as fresh input\.$/u, replace: '缓存复用良好；但仍有 $1 个未缓存token按新增输入计费，建议重点检查。' },
+  { pattern: /^Uncached input: ([+\-\d,.]+)\. Cached input: ([+\-\d,.]+)\. Cache ratio: ([+\-\d,.]+pp)\.$/u, replace: '未缓存输入：$1。缓存输入：$2。缓存比例：$3。' },
+  { pattern: /^Uncached input rose by ([\d,.]+) while cached input fell by ([\d,.]+)\.$/u, replace: '未缓存输入增加 $1，同时缓存输入减少 $2。' },
+  { pattern: /^Uncached input increased by ([\d,.]+) versus the previous aggregate call\.$/u, replace: '与上一次聚合调用相比，未缓存输入增加 $1。' },
+  { pattern: /^Uncached input decreased by ([\d,.]+) while cached input increased\.$/u, replace: '未缓存输入减少 $1，同时缓存输入增加。' },
+  { pattern: /^Signals: (.+)$/u, replace: '信号：$1' },
+  { pattern: /^Open call row in investigator for (.+)$/u, replace: '在分析器中打开调用记录：$1' },
+  { pattern: /^Open investigator for latest call in (.+)$/u, replace: '在分析器中打开该线程的最新调用：$1' },
+  { pattern: /^Copy link for latest call in (.+)$/u, replace: '复制该线程最新调用的链接：$1' },
+  { pattern: /^No loaded call available for (.+)$/u, replace: '没有可用于以下对象的已加载调用：$1' },
+  { pattern: /^Open investigator for thread call (.+)$/u, replace: '在分析器中打开线程调用：$1' },
+  { pattern: /^Copy link for thread call (.+)$/u, replace: '复制线程调用链接：$1' },
+  { pattern: /^Context use (.+)$/u, replace: '上下文占用：$1' },
+
+  // Explore actions preserve tool names and path labels exactly.
+  { pattern: /^([\d,.]+) reads · ([\d,.]+(?:[KMBT])?) output · ([\d,.]+) modifications$/iu, replace: '读取 $1 次 · 输出 $2 个token · 修改 $3 次' },
+  { pattern: /^([\d,.]+(?:[KMBT])?) uncached · ([\d,.]+) calls · ([\d,.]+)% cache$/iu, replace: '未缓存输入 $1 · 调用 $2 次 · 缓存 $3%' },
+  { pattern: /^([\d,.]+) loaded$/u, replace: '已加载 $1 条' },
+  { pattern: /^Load ([\d,.]+) more$/u, replace: '再加载 $1 条' },
+  { pattern: /^Inspect (.+) file evidence$/u, replace: '检查文件证据：$1' },
+  { pattern: /^Inspect (.+) tool evidence$/u, replace: '检查工具证据：$1' },
+  { pattern: /^Open evidence call for (.+)$/u, replace: '打开以下对象的证据调用：$1' },
+  { pattern: /^Copy evidence call link for (.+)$/u, replace: '复制以下对象的证据调用链接：$1' },
+  { pattern: /^Open largest call for (.+)$/u, replace: '打开以下对象的最大调用：$1' },
+  { pattern: /^Copy largest call link for (.+)$/u, replace: '复制以下对象的最大调用链接：$1' },
+
+  // Thread totals and lifecycle narration preserve thread names verbatim.
+  { pattern: /^Showing ([\d,.]+) of ([\d,.]+) grouped threads$/u, replace: '显示 $1 / $2 个分组线程' },
+  { pattern: /^([\d,.]+) selected calls$/u, replace: '已选择 $1 次调用' },
+  { pattern: /^([\d,.]+) calls · ([\d,.]+(?:[KMBT])?) tokens · ([\d,.]+)% cache$/iu, replace: '$1 次调用 · $2 个token · 缓存 $3%' },
+  { pattern: /^([\d,.]+) of ([\d,.]+) loaded$/u, replace: '已加载 $1 / $2 次' },
+  { pattern: /^Show ([\d,.]+) more calls$/u, replace: '再显示 $1 次调用' },
+  { pattern: /^Show first ([\d,.]+)$/u, replace: '显示前 $1 条' },
+  { pattern: /^([\d,.]+) more available$/u, replace: '还有 $1 条可用' },
+  { pattern: /^([\d,.]+) spawned$/u, replace: '已派生 $1 个' },
+  { pattern: /^([\d,.]+) signals$/u, replace: '$1 个信号' },
+  { pattern: /^Call ([\d,.]+)$/u, replace: '调用 $1' },
+  { pattern: /^([\d,.]+) loaded threads$/u, replace: '已加载 $1 个线程' },
+  { pattern: /^([\d,.]+) loaded threads combine at least 50,000 tokens with less than 35 percent cache reuse\.$/u, replace: '有 $1 个已加载线程的token数不低于 50,000，且缓存复用率低于 35%。' },
+  { pattern: /^No loaded calls are available for (.+)\.$/u, replace: (_match, threadName) => `没有可用于${threadName === 'the selected thread' ? '所选线程' : `“${threadName}”`}的已加载调用。` },
+  { pattern: /^([\d,.]+) calls are available for (.+); peak observed context use is ([\d,.]+) percent\.$/u, replace: '“$2”有 $1 次调用可用；观察到的上下文占用峰值为 $3%。' },
+];
+
+function scopeZhHans(scope: string): string {
+  if (scope === '24 hours') return '过去 24 小时';
+  if (scope === '7 days') return '过去 7 天';
+  if (scope === 'recent rows') return '近期记录';
+  return '全部时间范围';
+}
+
+function refreshPrefixZhHans(prefix: string): string {
+  if (prefix === 'Cache hit; ') return '命中缓存；';
+  if (prefix === 'Refreshed index; ') return '索引已刷新；';
+  return '';
+}
+
+function presetZhHans(preset: string): string {
+  if (preset === 'Highest Cost Threads') return '成本最高的线程';
+  if (preset === 'Context Bloat') return '上下文膨胀';
+  if (preset === 'Cache Misses') return '缓存未命中';
+  if (preset === 'Pricing Gaps') return '定价缺口';
+  if (preset === 'Codex Credits') return 'Codex 点数';
+  return '推理峰值';
+}
+
+function datePresetZhHans(preset: string): string {
+  if (preset === 'Today') return '今天';
+  if (preset === 'This week') return '本周';
+  if (preset === 'Last 7 days') return '过去 7 天';
+  return '本月';
+}
+
+function effortSummaryZhHans(summary: string): string {
+  const labels: Readonly<Record<string, string>> = {
+    low: '低',
+    medium: '中',
+    high: '高',
+    xhigh: '超高',
+    ultra: '极高',
+    max: '最大',
+  };
+  return summary
+    .split(', ')
+    .map(part => part.replace(/^(low|medium|high|xhigh|ultra|max) x([\d,]+)$/u, (_match, effort, count) => `${labels[String(effort)]} ×${count}`))
+    .join('、');
+}
+
+function threadStatusZhHans(status: string): string {
+  const labels: Readonly<Record<string, string>> = {
+    'Official match': '官方精确匹配',
+    Mixed: '混合匹配',
+    Configured: '已配置',
+    'Estimated mapping': '估算映射',
+    'No mapped rate': '没有匹配的费率',
+    'No price': '无定价',
+  };
+  return labels[status] ?? status;
+}
diff --git a/frontend/dashboard/src/app/zh-Hans/diagnosticsReports.ts b/frontend/dashboard/src/app/zh-Hans/diagnosticsReports.ts
new file mode 100644
index 00000000..2afce313
--- /dev/null
+++ b/frontend/dashboard/src/app/zh-Hans/diagnosticsReports.ts
@@ -0,0 +1,773 @@
+import type { ZhHansPattern } from './types';
+
+export const diagnosticsReportsZhHansTranslations: Readonly<Record<string, string>> = {
+  // Shared diagnostics and report labels.
+  Action: '操作',
+  Ascending: '升序',
+  Blocked: '受阻',
+  Cached: '已缓存',
+  'Cached %': '缓存占比',
+  Calls: '调用',
+  Category: '类别',
+  Copy: '复制',
+  Credits: '点数',
+  Descending: '降序',
+  Effort: '推理强度',
+  Evidence: '证据',
+  Fallback: '回退数据',
+  Finding: '发现',
+  High: '高',
+  Input: '输入',
+  Largest: '最大调用',
+  Latest: '最近时间',
+  Loading: '正在加载',
+  Low: '低',
+  Medium: '中',
+  Model: '模型',
+  Occurrences: '出现次数',
+  Open: '打开',
+  Output: '输出',
+  Planned: '计划中',
+  Ready: '就绪',
+  Reasoning: '推理',
+  Reports: '报告',
+  Stale: '已过期',
+  Static: '静态',
+  Thread: '线程',
+  Threads: '线程',
+  Time: '时间',
+  Total: '总计',
+  Uncached: '未缓存',
+  Unknown: '未知',
+  fallback: '回退数据',
+  high: '高',
+  low: '低',
+  medium: '中',
+  missing: '缺失',
+  ready: '就绪',
+  review: '需复核',
+  snapshots: '快照',
+  facts: '事实',
+  Showing: '已显示',
+  Show: '再显示',
+  of: '/',
+  more: '条',
+  loaded: '条已加载',
+  'loaded facts': '条已加载事实',
+  matched: '条匹配',
+  'evidence rows': '条证据记录',
+  'calls -': '次调用 ·',
+  'tokens -': 'token ·',
+  'cache -': '缓存 ·',
+  'Dashboard rows:': '仪表盘记录：',
+
+  // Diagnostics notebook.
+  'Diagnostics Notebook': '诊断工作台',
+  'Technical report system behavior usage patterns.': '关于系统行为与用量模式的技术报告。',
+  'Local Only': '仅限本地',
+  'Loading diagnostic fact sources': '正在加载诊断事实来源',
+  'Executive Findings': '核心发现',
+  'Top observations aggregate telemetry': '基于聚合遥测数据的主要观察结果',
+  'Notebook Index': '笔记本目录',
+  'Jump to section': '跳转到章节',
+  'Evidence Calls': '证据调用',
+  'No matching calls': '没有匹配的调用',
+  'No loaded aggregate call rows match diagnostic section.': '已加载的聚合调用中，没有记录与此诊断章节匹配。',
+  'Static fallback facts': '静态回退事实',
+  'Static aggregate fallback': '静态聚合回退数据',
+  'Diagnostic fact type and name are required.': '必须提供诊断事实的类型和名称。',
+  'Diagnostic facts require localhost dashboard server.': '诊断事实需要本机仪表盘服务器。',
+  'Diagnostic facts require localhost dashboard API token.': '诊断事实需要本机仪表盘 API 令牌。',
+  'Diagnostic snapshot refresh': '诊断快照刷新',
+  'Diagnostic refresh status': '诊断刷新状态',
+  'Structured Diagnostic Facts': '结构化诊断事实',
+  'Top Diagnostic Facts': '主要诊断事实',
+  'top diagnostic facts': '主要诊断事实',
+  'Top Facts': '主要事实',
+  'Tool and Function Activity': '工具与函数活动',
+  'Compaction Activity': '上下文压缩活动',
+  Compactions: '上下文压缩',
+  compactions: '上下文压缩',
+  Tools: '工具',
+  tools: '工具',
+  'Diagnostic fact modules': '诊断事实模块',
+  'Sort facts': '事实排序',
+  'Sort diagnostic facts': '诊断事实排序',
+  'Sort diagnostic facts ascending': '按升序排列诊断事实',
+  'Sort diagnostic facts descending': '按降序排列诊断事实',
+  'Uncached input': '未缓存输入',
+  'Total tokens': '总token数',
+  'Cached input': '缓存输入',
+  'Output tokens': '输出token数',
+  'Largest call': '最大调用',
+  'Associated calls': '关联调用',
+  'Cache %': '缓存占比',
+  'Latest time': '最近时间',
+  'Fact name': '事实名称',
+  'uncached input': '未缓存输入',
+  'total tokens': '总token数',
+  'cached input': '缓存输入',
+  'output tokens': '输出token数',
+  'largest call': '最大调用',
+  'associated calls': '关联调用',
+  'cache %': '缓存占比',
+  'latest time': '最近时间',
+  occurrences: '出现次数',
+  'fact name': '事实名称',
+  uncached: '未缓存',
+  cache: '缓存',
+  fact: '事实',
+  unknown: '未知',
+  uncategorized: '未分类',
+  'No diagnostic facts matched the current aggregate data.': '当前聚合数据中没有匹配的诊断事实。',
+  'Loading more facts...': '正在加载更多事实…',
+  'Load more live facts': '加载更多实时事实',
+  'Diagnostic Fact Calls': '诊断事实关联调用',
+  'Diagnostic fact calls': '诊断事实关联调用',
+  'No fact selected': '尚未选择事实',
+  'No loaded rows': '没有已加载记录',
+  'Sort calls': '调用排序',
+  'Sort diagnostic fact calls': '诊断事实关联调用排序',
+  'Sort diagnostic fact calls ascending': '按升序排列诊断事实关联调用',
+  'Sort diagnostic fact calls descending': '按降序排列诊断事实关联调用',
+  'Input tokens': '输入token数',
+  'Reasoning tokens': '推理token数',
+  'Loading fact calls...': '正在加载事实关联调用…',
+  'Load more fact calls': '加载更多事实关联调用',
+  'Loading rows...': '正在加载记录…',
+  'Load more dashboard rows': '加载更多仪表盘记录',
+  'Load all dashboard rows': '加载全部仪表盘记录',
+  'No aggregate calls are associated with the selected diagnostic fact.': '没有聚合调用与所选诊断事实关联。',
+  'Static aggregate fact calls': '静态聚合事实关联调用',
+  'Waiting for live diagnostics': '正在等待实时诊断数据',
+  'Loading calls for selected fact...': '正在加载所选事实的关联调用…',
+  'Select a diagnostic fact': '请选择一项诊断事实',
+  'Open associated aggregate calls in the full Call Investigator.': '在完整的调用分析器中打开关联的聚合调用。',
+
+  // Diagnostic snapshot matrix.
+  'Diagnostics Snapshot Matrix': '诊断快照矩阵',
+  'Refreshing diagnostic snapshots': '正在刷新诊断快照',
+  'Loading diagnostic snapshots': '正在加载诊断快照',
+  'Refreshing diagnostic snapshots...': '正在刷新诊断快照…',
+  'Loading diagnostic snapshots...': '正在加载诊断快照…',
+  'Refresh snapshots': '刷新快照',
+  Refreshing: '正在刷新',
+  Reload: '重新加载',
+  Reloading: '正在重新加载',
+  'Static fallback snapshots': '静态回退快照',
+  'Live diagnostic snapshots unavailable:': '实时诊断快照不可用：',
+  'No aggregate rows in this snapshot.': '此快照中没有聚合记录。',
+  'Show fewer': '收起',
+  Overview: '概览',
+  'Tool Output': '工具输出',
+  'Git Interactions': 'Git 交互',
+  'File Reads': '文件读取',
+  'File Modifications': '文件修改',
+  'Read Productivity': '读取成效',
+  Concentration: '集中度',
+  'What Is Driving Usage?': '是什么在推高用量？',
+  'Usage Drain': '用量消耗',
+  'Usage rows': '用量记录',
+  'Cache ratio': '缓存比率',
+  'Distinct aggregate thread labels': '聚合数据中的不同线程标签数',
+  'Distinct model labels': '不同模型标签数',
+  'Function calls': '函数调用',
+  'Function outputs': '函数输出',
+  'Original tokens': '原始token数',
+  'Shell calls': 'Shell 调用',
+  Roots: '根命令数',
+  'Missing root': '缺失根命令',
+  'No child commands': '没有子命令',
+  'Git calls': 'Git 调用',
+  'Git commands': 'Git 命令',
+  'GitHub CLI': 'GitHub CLI',
+  'Read events': '读取事件',
+  Readers: '读取工具数',
+  Events: '事件数',
+  'Unique paths': '唯一路径数',
+  'Largest event': '最大事件',
+  'Modification events': '修改事件',
+  'Modified later': '后续被修改',
+  Rate: '比率',
+  'Top thread share': '头部线程占比',
+  Groups: '分组数',
+  'largest impact': '影响最大',
+  'Estimated cost': '预估成本',
+  'Usage credits': '点数',
+  'Computed unknown time': '计算时间未知',
+  'Aggregate fallback module': '聚合回退模块',
+
+  // Reports workspace and live report pack.
+  'Report pack': '报告包',
+  'Reports pack': '报告包',
+  'Database error while building report pack': '构建报告包时发生数据库错误',
+  'Live report pack requires the localhost dashboard server.': '实时报告包需要本机仪表盘服务器。',
+  'Live report pack requires localhost dashboard API token.': '实时报告包需要本机仪表盘 API 令牌。',
+  'Reports pack returned an unsupported schema.': '报告包返回了不受支持的数据结构。',
+  'Live localhost report pack': '本机实时报告包',
+  'Loaded dashboard aggregates': '已加载的仪表盘聚合数据',
+  'Server timestamp unavailable': '服务器时间戳不可用',
+  'Current dashboard snapshot': '当前仪表盘快照',
+  'Refreshing selected report…': '正在刷新所选报告…',
+  'Selected report refreshed': '所选报告已刷新',
+  'Focused local research snapshots with their methods, limits, and investigator-linked evidence.': '聚焦本地数据的研究快照，附带分析方法、适用限制和可跳转至调用分析器的证据。',
+  'Export selected': '导出所选报告',
+  'Live report refresh requires the localhost server.': '实时刷新报告需要本机服务器。',
+  'Refresh report': '刷新报告',
+  'Live refresh unavailable': '实时刷新不可用',
+  'Loading full-scope report pack': '正在加载完整范围的报告包',
+  'Live report pack': '实时报告包',
+  'No report available': '暂无可用报告',
+  'No owner': '无负责人',
+  'Select report': '选择报告',
+  'Report evidence': '报告证据',
+  'Report Evidence Calls': '报告证据调用',
+  'Investigator linked': '已关联调用分析器',
+  'Research Notes': '研究说明',
+  'Interpretation boundary': '解读边界',
+  Method: '方法',
+  Caveat: '限制说明',
+  'Evidence privacy': '证据隐私',
+  'Raw context is not included here; inspect an explicitly linked call in Call Investigator.': '此处不包含原始上下文；如需查看，请在调用分析器中打开明确关联的调用。',
+  'Generation Metadata': '生成元数据',
+  'Provenance for this view': '此视图的数据来源',
+  Source: '来源',
+  Generated: '生成时间',
+  Schema: '数据结构',
+  Matched: '匹配记录',
+  'dashboard aggregate model': '仪表盘聚合模型',
+  'Static mode: using the loaded aggregate snapshot.': '静态模式：正在使用已加载的聚合快照。',
+  'Loading live report pack…': '正在加载实时报告包…',
+  'Refreshing live report pack…': '正在刷新实时报告包…',
+  'Cached live report pack is stale; refresh is available.': '缓存的实时报告包已过期，可以刷新。',
+  'Live report pack ready.': '实时报告包已就绪。',
+  'No loaded aggregate calls match this selected report.': '已加载的聚合调用中，没有记录与所选报告匹配。',
+  'Selected report evidence calls': '所选报告的证据调用',
+  'loaded rows': '条已加载记录',
+  'Est. Cost': '预估成本',
+  'Speed proxy': '速度代理指标',
+  'Filter fast-tagged and low-effort calls, then order by shortest duration and credit impact.': '筛选带有快速标签或低推理强度的调用，再按耗时从短到长及点数影响排序。',
+  'Aggregate timing cannot distinguish model latency from tool, network, or queue time.': '聚合耗时无法区分模型延迟、工具耗时、网络耗时或排队时间。',
+  'Fast/low-effort candidates · shortest duration first · top 8': '快速/低推理强度候选 · 耗时最短优先 · 前 8 项',
+  'Cost concentration': '成本集中度',
+  'Rank aggregate calls by estimated cost, breaking ties with total token volume.': '按预估成本对聚合调用排序，成本相同时以token总量决定顺序。',
+  'Estimated local cost may differ from billing and excludes costs not represented in loaded rows.': '本地预估成本可能与实际账单不同，且不包含已加载记录未覆盖的费用。',
+  'Highest estimated cost · token volume tie-break · top 8': '预估成本最高优先 · token量决定同分顺序 · 前 8 项',
+  'Usage trajectory': '用量走势',
+  'Rank aggregate calls by estimated Codex credit impact and compare the selected time series.': '按预估的 Codex 点数影响对聚合调用排序，并对比所选时间序列。',
+  'Allowance and credit projections are local observations, not universal account limits.': '额度和点数预测仅基于本地观察，并非适用于所有账户的统一上限。',
+  'Highest credit impact · token volume tie-break · top 8': '点数影响最高优先 · token量决定同分顺序 · 前 8 项',
+  Percent: '百分比',
+  'Under 5s': '5 秒以内',
+  '5-15s': '5–15 秒',
+  '15-30s': '15–30 秒',
+  '30s+': '30 秒以上',
+  'Selected report': '所选报告',
+  'selected report': '所选报告',
+  'Speed proxy evidence': '速度代理指标证据',
+  'Cost concentration evidence': '成本集中度证据',
+  'Usage trajectory evidence': '用量走势证据',
+  'Raw context is available only through an explicitly linked Call Investigator record.': '只有通过明确关联的调用分析器记录才能查看原始上下文。',
+  'Use left and right arrow keys to inspect chart values, or switch to the table for exact values.': '使用左右方向键查看图表数值，或切换到表格查看精确值。',
+  'Observed period': '观察周期',
+  'Weekly remaining': '每周剩余用量',
+  'Observed drain': '观察到的消耗',
+  'Predicted baseline': '预测基线',
+  'Usage remaining': '剩余用量',
+  'Allowance guide': '额度参考线',
+  'Loaded-row baseline': '已加载记录基线',
+  'Projected weekly credits': '预计每周点数',
+  'Loaded-row credits': '已加载记录点数',
+  'Cost Curves': '成本曲线',
+  'Usage Drain Model': '用量消耗模型',
+  'Fast Mode Proxy': '快速模式代理指标',
+  'Weekly Credits': '每周点数',
+  'Usage Remaining': '剩余用量',
+  'Allowance Change': '额度变化',
+  'Estimated cost concentration by loaded aggregate thread.': '按已加载聚合线程统计的预估成本集中度。',
+  'Highest estimated credit-impact calls from loaded aggregate rows.': '已加载聚合记录中，预估点数影响最高的调用。',
+  'Low-effort and fast-call candidates inferred from aggregate rows.': '根据聚合记录推断出的低推理强度和快速调用候选。',
+
+  // Fallback findings and report copy used by the React aggregate model.
+  'Cache Misses (Large Inputs)': '缓存未命中（大输入）',
+  'High Model Effort': '高模型推理强度',
+  'Tool Output Volume': '工具输出量',
+  'Cache Behavior': '缓存行为',
+  'Thread Efficiency': '线程效率',
+  'Tool And Command Activity': '工具与命令活动',
+  'Projected weekly credits declined from the baseline and partially recovered in the latest window.': '预计每周点数较基线下降，并在最近一个窗口中部分回升。',
+  'Cache hit rate is healthy overall, with spikes aligned to large cache misses and cold resumes.': '总体缓存命中率良好，波动峰值与大规模缓存未命中及冷恢复相吻合。',
+  'Long threads account for most estimated cost and are the clearest optimization target.': '长线程占据大部分预估成本，是最明确的优化目标。',
+  'Command volume is stable with a slight upward trend; read and shell commands dominate.': '命令量总体稳定但略有上升，其中读取命令和 Shell 命令占主导。',
+  'Plan-specific weekly credits, trend lines, and confidence intervals.': '按套餐展示每周点数、趋势线和置信区间。',
+  'Observed remaining usage over time with reset handling.': '展示经过重置处理的剩余用量时间变化。',
+  'Cumulative estimated cost by thread and concentration metrics.': '按线程统计累计预估成本及集中度指标。',
+  'Actual-vs-predicted drain and feature group comparisons.': '实际与预测用量消耗及特征分组对比。',
+  'Candidate detection, speedup histogram, and confidence breakdowns.': '候选检测、加速幅度直方图和置信度明细。',
+  'Week-to-week allowance estimate changes with careful language.': '以审慎表述展示逐周额度估算变化。',
+
+  // Settings.
+  'Local configuration': '本地配置',
+  Settings: '设置',
+  'Inspect dashboard behavior and configuration truth without changing server-owned settings.': '查看仪表盘行为和实际配置状态，不会修改由服务器管理的设置。',
+  'Live API available': '实时 API 可用',
+  'Static snapshot': '静态快照',
+  'Content access enabled': '内容访问已启用',
+  'Content access gated': '内容访问受限',
+  'Settings sections': '设置分类',
+  Data: '数据',
+  'Loaded history and local runtime state.': '已加载的历史记录和本地运行状态。',
+  Estimates: '估算',
+  'Pricing and allowance inputs used for local estimates.': '用于本地估算的定价与额度输入。',
+  'Content Access': '内容访问',
+  'Privacy boundaries and explicit raw-context gates.': '隐私边界与显式原始上下文访问门控。',
+  Application: '应用',
+  'Dashboard refresh, API, and language visibility.': '仪表盘刷新、API 与语言显示状态。',
+  'Source Health': '数据源健康状态',
+  'Configuration and parser diagnostics.': '配置与解析器诊断。',
+  'Loaded Data': '已加载数据',
+  'Served shell payload': '服务器提供的外壳载荷',
+  'Embedded payload': '内嵌载荷',
+  'Data window': '数据窗口',
+  'Evidence rows': '证据记录',
+  'Session scope': '会话范围',
+  'Include archived': '包含已归档会话',
+  'Usage index': '用量索引',
+  'served shell': '服务器外壳数据',
+  'embedded payload': '内嵌载荷',
+  'Estimate Inputs': '估算输入',
+  'Read-only local configuration': '只读本地配置',
+  Pricing: '定价',
+  Allowance: '额度',
+  'Rate card': '费率表',
+  Loaded: '已加载',
+  'Not loaded': '未加载',
+  'local pricing config': '本地定价配置',
+  'local allowance config': '本地额度配置',
+  'Allowance Windows': '额度窗口',
+  'Allowance config': '额度配置',
+  Usage: '用量',
+  Window: '窗口',
+  'No allowance windows configured': '尚未配置额度窗口',
+  'Observed usage available': '可用观察用量数据',
+  'Configured allowance window': '已配置的额度窗口',
+  'Manual allowance windows and live observed usage': '手动额度窗口与实时观察用量',
+  'Privacy Boundary': '隐私边界',
+  'Payload mode': '载荷模式',
+  'Project metadata': '项目元数据',
+  'Raw context': '原始上下文',
+  'Explicit localhost request, selected call only': '仅通过本机显式请求访问所选调用',
+  'Disabled until context API is enabled': '启用上下文 API 前保持禁用',
+  'Live requests': '实时请求',
+  'Local API token present': '已提供本地 API 令牌',
+  'Content Access Rules': '内容访问规则',
+  'Local and explicit': '仅限本地且必须显式触发',
+  'Aggregate payloads avoid prompts, assistant text, and raw tool output.': '聚合载荷不包含提示词、助手文本和原始工具输出。',
+  'Raw context actions remain gated behind explicit Call Investigator controls.': '原始上下文操作仍须通过调用分析器中的显式控件触发。',
+  'Live refresh and context requests stay local and require the dashboard API token.': '实时刷新和上下文请求仅在本机进行，并且需要仪表盘 API 令牌。',
+  'Dashboard Runtime': '仪表盘运行状态',
+  'Data connection': '数据连接',
+  Enabled: '已启用',
+  Paused: '已暂停',
+  'Interface language': '界面语言',
+  'English (en)': '英语（en）',
+  'Configuration Checks': '配置检查',
+  'Configuration and ingestion facts': '配置与数据导入状态',
+  'Pricing snapshot': '定价快照',
+  Configured: '已配置',
+  'Not configured': '未配置',
+  'Parser diagnostics': '解析器诊断',
+  'No parser warnings': '没有解析器警告',
+  'Usage deduplication': '用量去重',
+  'Normal metadata': '普通元数据',
+  'aggregate-only snapshot': '仅聚合数据快照',
+  'Last 24 hours': '过去 24 小时',
+
+  // Guided aggregate diagnostics.
+  'Thread concentration': '线程集中度',
+  'Review whether this thread still needs its full accumulated context.': '检查此线程是否仍需要保留全部累积上下文。',
+  'Model mix': '模型构成',
+  'Compare model choice against the actual work in the heaviest calls.': '对照最重调用的实际任务，检查模型选择是否合适。',
+  'Low cache reuse': '缓存复用率低',
+  'Look for repeated file reads, cold resumes, or broad context restatement.': '检查是否存在重复读取文件、冷恢复或大范围重述上下文。',
+  'Reasoning-heavy output': '推理输出占比较高',
+  'Check whether effort settings match task complexity.': '检查推理强度设置是否与任务复杂度匹配。',
+  'Subagent activity': '子代理活动',
+  'Separate direct work from delegated work when explaining usage growth.': '解释用量增长时，应区分直接执行与委派给子代理的工作。',
+  'Context pressure': '上下文压力',
+  'Inspect high-context threads before deciding whether to split work.': '决定是否拆分任务前，先检查上下文占用较高的线程。',
+  'Command activity': '命令活动',
+  'Use the Commands panel to see whether repetitive tooling is driving usage.': '使用“命令”面板检查重复工具操作是否在推高用量。',
+  'Tool output volume': '工具输出量',
+  'Trim noisy command output or use narrower file reads where possible.': '尽量精简冗长的命令输出，或缩小文件读取范围。',
+  'Visible usage movement': '可见用量变化',
+  'Use Usage Drain for allowance projection caveats and trend context.': '在“用量消耗”中查看额度预测的限制说明和趋势背景。',
+  'Top thread by tokens': 'token量最高的线程',
+  'Compare this thread against newer handoff threads before changing workflow.': '调整工作流前，将此线程与较新的交接线程进行比较。',
+  'Top model bucket': 'token量最高的模型分组',
+  'Check whether the model choice matches the work that dominates usage.': '检查模型选择是否与占用量最大的工作相匹配。',
+  'Top effort bucket': 'token量最高的推理强度分组',
+  'Compare effort mix with task complexity before changing defaults.': '更改默认值前，对照任务复杂度检查推理强度构成。',
+  'Uncached input share': '未缓存输入占比',
+  'High uncached share is a good place to look for repeated context loading.': '未缓存占比较高时，应优先排查重复加载上下文。',
+  'Top review signal': '首要复核信号',
+  'unknown thread': '未知线程',
+
+  // Agentic findings, actions, caveats, and user-facing reasons.
+  'Large calls produced little output': '大型调用的输出很少',
+  'Large input/context usage with low output is a strong candidate for cold resumes, stale thread continuation, or low-value continuation.': '输入或上下文用量很大但输出很少，通常提示冷恢复、继续使用陈旧线程或低价值续接。',
+  'Open the top calls, check whether a smaller fresh thread or preserved handoff would avoid resending large context.': '打开排名靠前的调用，检查改用较小的新线程或保留交接摘要能否避免重复发送大量上下文。',
+  'Aggregate token/activity counts only; no raw fragments or command output.': '仅包含聚合token数和活动计数，不含原始片段或命令输出。',
+  'The aggregate report cannot prove why output was low without a thread trace or explicit raw-context inspection.': '缺少线程轨迹或显式原始上下文检查时，聚合报告无法证明输出偏低的具体原因。',
+  'Repeated shell command churn': 'Shell 命令反复空转',
+  'Repeated shell roots, failures, or adjacent retries can waste turns and inflate tool-output/context pressure.': '反复使用相同 Shell 根命令、持续失败或相邻重试会浪费轮次，并加剧工具输出和上下文压力。',
+  'Turn repeated probes into a small script, narrower command, or targeted test command.': '将重复探测整理成小型脚本、范围更窄的命令或有针对性的测试命令。',
+  'Command roots and bounded labels only; raw command output is omitted.': '仅包含根命令和受限标签，省略原始命令输出。',
+  'Strict aggregate evidence cannot always recover the exact shell intent or full command arguments.': '严格聚合证据不一定能还原确切的 Shell 意图或完整命令参数。',
+  'Repeated file rediscovery': '重复查找同一文件',
+  'Repeated safe file identities can indicate the agent keeps rediscovering the same context instead of using a durable summary or targeted helper.': '反复出现相同的安全文件标识，可能说明代理一直在重新查找同一上下文，而没有使用持久摘要或专用辅助工具。',
+  'Summarize stable facts into project docs or build a small helper command for recurring lookups.': '将稳定信息整理到项目文档中，或为重复查询构建小型辅助命令。',
+  'Safe path hashes, basenames, and aggregates only; full paths are omitted.': '仅包含安全的路径哈希、文件基本名和聚合数据，省略完整路径。',
+  'The report can rank repeated safe file identities, but cannot tell whether each reread was necessary without task intent.': '报告可以对重复的安全文件标识排序，但缺少任务意图时无法判断每次重读是否必要。',
+  'Ranked aggregate usage recommendations': '已排序的聚合用量建议',
+  'Existing recommendation scoring combines aggregate cost, cache, context, and pricing signals.': '现有建议评分综合了聚合成本、缓存、上下文和定价信号。',
+  'Start with the highest recommendation score, then verify with the specific diagnostic tool.': '从评分最高的建议开始，再使用相应诊断工具进行验证。',
+  'Aggregate recommendations only; no prompt or tool-output text.': '仅包含聚合建议，不含提示词或工具输出文本。',
+  'Recommendation scores do not know whether an expensive call produced high-value work.': '建议评分无法判断高成本调用是否产出了高价值结果。',
+  'Local Codex logs only; this is not an official OpenAI usage ledger.': '仅基于本地 Codex 日志，并非 OpenAI 官方用量账本。',
+  'Archived sessions are excluded unless include_archived is true.': '除非 include_archived 为 true，否则不包含已归档会话。',
+  'Run weekly evidence-graded allowance diagnostics before interpreting 5-hour noise.': '解读 5 小时窗口的噪声前，先运行带证据等级的每周额度诊断。',
+  'Create strict local evidence bundle when the user wants to share allowance-change evidence.': '用户需要分享额度变化证据时，创建严格隐私模式的本地证据包。',
+  'Weekly allowance evidence is the primary signal; 5-hour counters are rolling-window context.': '每周额度证据是主要信号；5 小时计数器仅提供滚动窗口背景。',
+  'Confirm index freshness and row counts.': '确认索引新鲜度和记录数。',
+  "Rank projects, threads, models, or dates depending on the user's next question.": '根据用户接下来的问题，对项目、线程、模型或日期进行排序。',
+  'Open dashboard-shaped evidence cards for top aggregate drivers.': '打开与仪表盘一致的证据卡片，查看主要聚合驱动因素。',
+  'No strong local signal at default thresholds': '默认阈值下没有明显的本地信号',
+  'The current aggregate diagnostics did not find a clear candidate at the default threshold.': '当前聚合诊断在默认阈值下没有发现明确候选。',
+  'Lower thresholds, widen the time window, include archived sessions, or inspect top aggregate calls.': '降低阈值、扩大时间窗口、纳入已归档会话，或检查排名靠前的聚合调用。',
+  'No raw context needed for this follow-up.': '此后续检查无需原始上下文。',
+  'No supported aggregate signal was found at the selected thresholds.': '所选阈值下未发现受支持的聚合信号。',
+};
+
+export const diagnosticsReportsZhHansPatterns: ReadonlyArray<ZhHansPattern> = [
+  // Diagnostics counts, sort descriptions, states, and controls.
+  {
+    pattern: /^Live (.+): ([\d,.]+)$/u,
+    replace: (_match, noun, count) => `实时${translateEmbeddedUiText(noun)}：${count}`,
+  },
+  {
+    pattern: /^Live (.+) unavailable: (.+)$/u,
+    replace: (_match, noun, error) => `实时${translateEmbeddedUiText(noun)}不可用：${error}`,
+  },
+  {
+    pattern: /^(.+) module - ([\d,.]+) loaded \/ ([\d,.]+) matched - (.+)$/u,
+    replace: (_match, title, loaded, matched, sort) =>
+      `${translateEmbeddedUiText(title)}模块 · 已加载 ${loaded} / 匹配 ${matched} · ${translateSortDescription(sort)}`,
+  },
+  {
+    pattern: /^(.+) module - ([\d,.]+) matched - (.+)$/u,
+    replace: (_match, title, matched, sort) =>
+      `${translateEmbeddedUiText(title)}模块 · 匹配 ${matched} 条 · ${translateSortDescription(sort)}`,
+  },
+  {
+    pattern: /^sorted by (.+) (descending|ascending)$/u,
+    replace: (_match, label, direction) =>
+      `按${translateEmbeddedUiText(label)}${direction === 'descending' ? '降序' : '升序'}排列`,
+  },
+  { pattern: /^([\d,.]+) loaded \/ ([\d,.]+) matched$/u, replace: '已加载 $1 / 匹配 $2' },
+  { pattern: /^([\d,.]+) matched$/u, replace: '匹配 $1 条' },
+  { pattern: /^\/ ([\d,.]+) matched$/u, replace: '· 共匹配 $1 条' },
+  {
+    pattern: /^(High|Medium|Low) confidence$/u,
+    replace: (_match, confidence) => `${translateEmbeddedUiText(confidence)}置信度`,
+  },
+  { pattern: /^([\d,.]+) calls - ([\d.]+%) cache$/u, replace: '$1 次调用 · 缓存占比 $2' },
+  { pattern: /^([\d,.]+) of ([\d,.]+) live fact calls$/u, replace: '已加载 $1 / $2 次实时事实关联调用' },
+  { pattern: /^([\d,.]+) fallback aggregate calls$/u, replace: '$1 次回退聚合调用' },
+  {
+    pattern: /^Showing ([\d,.]+) of ([\d,.]+) calls - (.+)$/u,
+    replace: (_match, shown, total, sort) => `已显示 ${shown} / ${total} 次调用 · ${translateSortDescription(sort)}`,
+  },
+  { pattern: /^Showing ([\d,.]+) of ([\d,.]+) calls$/u, replace: '已显示 $1 / $2 次调用' },
+  { pattern: /^Showing ([\d,.]+) of ([\d,.]+) loaded facts$/u, replace: '已显示 $1 / $2 条已加载事实' },
+  { pattern: /^Showing ([\d,.]+) of ([\d,.]+) loaded facts \/ ([\d,.]+) matched$/u, replace: '已显示 $1 / $2 条已加载事实 · 共匹配 $3 条' },
+  { pattern: /^Show ([\d,.]+) more$/u, replace: '再显示 $1 条' },
+  { pattern: /^Dashboard rows: ([\d,.]+) of ([\d,.]+) loaded$/u, replace: '仪表盘记录：已加载 $1 / $2 条' },
+  { pattern: /^([\d,.]+) aggregate rows$/u, replace: '$1 条聚合记录' },
+  { pattern: /^([\d,.]+(?:[KMBT])?) tokens$/iu, replace: '$1 个token' },
+  { pattern: /^([\d,.]+(?:[KMBT])?) uncached$/iu, replace: '$1 个未缓存token' },
+  { pattern: /^([\d,.]+) calls$/u, replace: '$1 次调用' },
+  { pattern: /^([\d,.]+) reads$/u, replace: '$1 次读取' },
+  { pattern: /^([\d,.]+) modified later$/u, replace: '$1 次后续被修改' },
+  { pattern: /^([\d,.]+) child commands$/u, replace: '$1 个子命令' },
+  { pattern: /^Show ([\d,.]+) child command$/u, replace: '显示 $1 个子命令' },
+  { pattern: /^Show ([\d,.]+) child commands$/u, replace: '显示 $1 个子命令' },
+  { pattern: /^Showing all ([\d,.]+) rows$/u, replace: '正在显示全部 $1 条记录' },
+  { pattern: /^Showing ([\d,.]+) of ([\d,.]+) rows$/u, replace: '正在显示 $1 / $2 条记录' },
+  { pattern: /^Live snapshots: ([\d,.]+)$/u, replace: '实时快照：$1 个' },
+  { pattern: /^Snapshot refresh failed: (.+)$/u, replace: '快照刷新失败：$1' },
+  { pattern: /^Live diagnostic snapshots unavailable: (.+)$/u, replace: '实时诊断快照不可用：$1' },
+  {
+    pattern: /^(.+) request failed with HTTP ([\d]+)$/u,
+    replace: (_match, title, status) => `${translateEmbeddedUiText(title)}请求失败（HTTP ${status}）`,
+  },
+  {
+    pattern: /^(.+) failed with HTTP ([\d]+)$/u,
+    replace: (_match, title, status) => `${translateEmbeddedUiText(title)}失败（HTTP ${status}）`,
+  },
+  { pattern: /^Diagnostic refresh failed: (.+)$/u, replace: '诊断刷新失败：$1' },
+  { pattern: /^Unknown diagnostic snapshot: (.+)$/u, replace: '未知诊断快照：$1' },
+  { pattern: /^(.+) unavailable: (.+)$/u, replace: (_match, title, error) => `${translateEmbeddedUiText(title)}不可用：${error}` },
+  {
+    pattern: /^Reload (.+) diagnostic snapshot$/u,
+    replace: (_match, title) => `重新加载${translateEmbeddedUiText(title)}诊断快照`,
+  },
+  {
+    pattern: /^Open investigator for diagnostic snapshot (.+?) (.+)$/u,
+    replace: (_match, title, label) => `在调用分析器中打开${translateEmbeddedUiText(title)}诊断快照：${label}`,
+  },
+  {
+    pattern: /^Copy link for diagnostic snapshot (.+?) (.+)$/u,
+    replace: (_match, title, label) => `复制${translateEmbeddedUiText(title)}诊断快照链接：${label}`,
+  },
+  { pattern: /^Open investigator for diagnostic call (.+)$/u, replace: '在调用分析器中打开诊断调用：$1' },
+  { pattern: /^Copy link for diagnostic call (.+)$/u, replace: '复制诊断调用链接：$1' },
+  { pattern: /^Open investigator diagnostic fact call (.+)$/u, replace: '在调用分析器中打开诊断事实关联调用：$1' },
+  { pattern: /^Copy link for diagnostic fact call (.+)$/u, replace: '复制诊断事实关联调用链接：$1' },
+  { pattern: /^Open investigator largest diagnostic fact call (.+)$/u, replace: '在调用分析器中打开最大诊断事实关联调用：$1' },
+  { pattern: /^Copy link for largest diagnostic fact call (.+)$/u, replace: '复制最大诊断事实关联调用链接：$1' },
+  { pattern: /^Open call row in investigator for report side evidence call (.+)$/u, replace: '在调用分析器中打开报告证据调用：$1' },
+  { pattern: /^Copy link for report side evidence call (.+)$/u, replace: '复制报告证据调用链接：$1' },
+  {
+    pattern: /^Computed unknown time · history (.+?) · logs scanned (.+?) · rows scanned (.+)$/u,
+    replace: (_match, scope, logs, rows) =>
+      `计算时间未知 · 历史范围：${translateHistoryScope(scope)} · 已扫描 ${logs} 个日志 · ${rows} 条记录`,
+  },
+  {
+    pattern: /^Computed unknown time · history (.+?) · logs scanned (.+)$/u,
+    replace: (_match, scope, logs) =>
+      `计算时间未知 · 历史范围：${translateHistoryScope(scope)} · 已扫描 ${logs} 个日志`,
+  },
+  {
+    pattern: /^Computed (.+?) · history (.+?) · logs scanned (.+?) · rows scanned (.+)$/u,
+    replace: (_match, computed, scope, logs, rows) =>
+      `计算于 ${translateShortTimestamp(computed)} · 历史范围：${translateHistoryScope(scope)} · 已扫描 ${logs} 个日志 · ${rows} 条记录`,
+  },
+  {
+    pattern: /^Computed (.+?) · history (.+?) · logs scanned (.+)$/u,
+    replace: (_match, computed, scope, logs) =>
+      `计算于 ${translateShortTimestamp(computed)} · 历史范围：${translateHistoryScope(scope)} · 已扫描 ${logs} 个日志`,
+  },
+  { pattern: /^Computed (.+)$/u, replace: (_match, computed) => `计算于 ${translateShortTimestamp(computed)}` },
+  {
+    pattern: /^history (.+) · logs scanned ([\d,.]+) · rows scanned ([\d,.]+)$/u,
+    replace: (_match, scope, logs, rows) =>
+      `历史范围：${translateHistoryScope(scope)} · 已扫描 ${logs} 个日志 · ${rows} 条记录`,
+  },
+  {
+    pattern: /^history (.+) · logs scanned ([\d,.]+)$/u,
+    replace: (_match, scope, logs) => `历史范围：${translateHistoryScope(scope)} · 已扫描 ${logs} 个日志`,
+  },
+  {
+    pattern: /^history (.+) · no stored snapshot$/u,
+    replace: (_match, scope) => `历史范围：${translateHistoryScope(scope)} · 没有已存储快照`,
+  },
+  {
+    pattern: /^(Jan|Feb|Mar|Apr|May|Jun|Jul|Aug|Sep|Oct|Nov|Dec) ([\d]{1,2}), ([\d]{1,2}):([\d]{2}) (AM|PM)$/u,
+    replace: match => translateShortTimestamp(match),
+  },
+
+  // Reports, evidence, and visualization copy.
+  { pattern: /^Refresh failed: (.+)\. Showing cached live report pack\.$/u, replace: '刷新失败：$1。正在显示缓存的实时报告包。' },
+  { pattern: /^Report pack unavailable: (.+)$/u, replace: '报告包不可用：$1' },
+  { pattern: /^Live report pack unavailable: (.+)\. Using loaded aggregate fallback\.$/u, replace: '实时报告包不可用：$1。正在使用已加载的聚合回退数据。' },
+  { pattern: /^Exported (.+)$/u, replace: (_match, title) => `已导出${translateEmbeddedUiText(title)}` },
+  { pattern: /^(.+) selected$/u, replace: (_match, title) => `已选择${translateEmbeddedUiText(title)}` },
+  {
+    pattern: /^(Live localhost report pack|Loaded dashboard aggregates) · (.+)$/u,
+    replace: (_match, source, selection) =>
+      `${translateEmbeddedUiText(source)} · ${translateEmbeddedUiText(selection)}`,
+  },
+  { pattern: /^([\d,.]+) evidence rows$/u, replace: '$1 条证据记录' },
+  { pattern: /^([\d,.]+) aggregate rows · select a row to open Call Investigator$/u, replace: '$1 条聚合记录 · 选择记录可在调用分析器中打开' },
+  { pattern: /^([\d,.]+) loaded rows$/u, replace: '$1 条已加载记录' },
+  {
+    pattern: /^([\d,.]+) loaded calls are fast-tagged or low effort\. Duration is a proxy, not a quality score\.$/u,
+    replace: '$1 次已加载调用带有快速标签或采用低推理强度。耗时只是代理指标，并非质量评分。',
+  },
+  {
+    pattern: /^([\d,.]+) highest-cost loaded calls anchor this report\. Estimates use the local pricing model\.$/u,
+    replace: '此报告以成本最高的 $1 次已加载调用为核心，估算采用本地定价模型。',
+  },
+  {
+    pattern: /^([\d,.]+) highest credit-impact loaded calls support the selected usage report\.$/u,
+    replace: '点数影响最高的 $1 次已加载调用为所选用量报告提供证据。',
+  },
+  {
+    pattern: /^No loaded aggregate data is available for (.+)\.$/u,
+    replace: (_match, title) => `${translateEmbeddedUiText(title)}暂无已加载的聚合数据。`,
+  },
+  {
+    pattern: /^(.+) contains ([\d,.]+) plotted rows\. (.+)$/u,
+    replace: (_match, title, rows, finding) => `${translateEmbeddedUiText(title)}包含 ${rows} 条绘图记录。${translateEmbeddedUiText(finding)}`,
+  },
+  {
+    pattern: /^No plotted rows are available for (.+)\.$/u,
+    replace: (_match, title) => `${translateEmbeddedUiText(title)}没有可绘制的记录。`,
+  },
+  {
+    pattern: /^(.+) report data$/u,
+    replace: (_match, title) => `${translateEmbeddedUiText(title)}报告数据`,
+  },
+  { pattern: /^([A-Za-z][A-Za-z0-9 ._-]*) observed$/u, replace: '$1 观测值' },
+  { pattern: /^([A-Za-z][A-Za-z0-9 ._-]*) trend$/u, replace: '$1 趋势' },
+  { pattern: /^Point ([\d,.]+)$/u, replace: '数据点 $1' },
+  { pattern: /^(.+) low$/u, replace: (_match, label) => `${translateEmbeddedUiText(label)}下限` },
+  { pattern: /^(.+) high$/u, replace: (_match, label) => `${translateEmbeddedUiText(label)}上限` },
+  { pattern: /^Long Thread: (.+)$/u, replace: '长线程：$1' },
+  { pattern: /^([\d,.]+) loaded calls and ([\d,.]+) tokens in this thread\.$/u, replace: '此线程包含 $1 次已加载调用和 $2 个token。' },
+  { pattern: /^([\d,.]+) loaded calls show low cache reuse or large uncached input\.$/u, replace: '$1 次已加载调用存在缓存复用率低或未缓存输入量大的情况。' },
+  { pattern: /^([\d,.]+) loaded calls use high effort or report reasoning output\.$/u, replace: '$1 次已加载调用采用高推理强度或记录了推理输出。' },
+  { pattern: /^([\d,.]+) loaded calls have high output volume or file-heavy\/subagent tags\.$/u, replace: '$1 次已加载调用的输出量较高，或带有文件密集/子代理标签。' },
+
+  // Settings values and diagnostics.
+  { pattern: /^Most recent ([\d,.]+)$/u, replace: '最近 $1 条记录' },
+  { pattern: /^([\d,.]+) of ([\d,.]+)$/u, replace: '$1 / $2' },
+  {
+    pattern: /^Observed (.+)$/u,
+    replace: (_match, label) => `观察值：${translateEmbeddedUiText(label)}`,
+  },
+  {
+    pattern: /^Configured (.+)$/u,
+    replace: (_match, label) => `已配置：${translateEmbeddedUiText(label)}`,
+  },
+  { pattern: /^([\d.]+%) remaining$/u, replace: '剩余 $1' },
+  { pattern: /^([\d.]+%) used$/u, replace: '已用 $1' },
+  { pattern: /^([\d,.]+) cr left$/u, replace: '剩余 $1 点' },
+  { pattern: /^([\d,.]+) cr total$/u, replace: '总计 $1 点' },
+  { pattern: /^resets (.+)$/u, replace: '重置于 $1' },
+  {
+    pattern: /^(?:[\d.]+% (?:remaining|used)|[\d,.]+ cr (?:left|total)|resets .+)(?: · (?:[\d.]+% (?:remaining|used)|[\d,.]+ cr (?:left|total)|resets .+))*$/u,
+    replace: match => translateAllowanceWindowValue(match),
+  },
+  {
+    pattern: /^.+(?: · (?:plan|limit|observed) .+)+$/u,
+    replace: match => translateAllowanceMetadata(match),
+  },
+  { pattern: /^Config error: (.+)$/u, replace: '配置错误：$1' },
+  { pattern: /^Rate-card error: (.+)$/u, replace: '费率表错误：$1' },
+  { pattern: /^([\d,.]+) copied rows excluded; ([\d,.]+) physical rows preserved$/u, replace: '已排除 $1 条复制记录；保留 $2 条物理记录' },
+  { pattern: /^([\d,.]+) parser diagnostics: (.+)$/u, replace: '$1 项解析器诊断：$2' },
+  {
+    pattern: /^([^:]+): (cwd redacted|project names redacted|git remote hidden|relative cwd hidden|git branch hidden|tags hidden|aliases preserved)(?:, .+)*$/u,
+    replace: match => translatePrivacyMetadata(match),
+  },
+
+  // Guided-signal findings retain thread/model labels and numerical evidence.
+  { pattern: /^(.+) accounts for ([\d.]+%) of tokens\.$/u, replace: '$1 占token总量的 $2。' },
+  { pattern: /^(.+) is the largest model bucket by tokens\.$/u, replace: '$1 是token量最大的模型分组。' },
+  { pattern: /^Overall cache ratio is ([\d.]+%)\.$/u, replace: '总体缓存比率为 $1。' },
+  { pattern: /^Reasoning output is ([\d.]+%) of total tokens\.$/u, replace: '推理输出占token总量的 $1。' },
+  { pattern: /^Subagent-linked rows are ([\d.]+%) of calls\.$/u, replace: '子代理关联记录占全部调用的 $1。' },
+  { pattern: /^([\d.]+%) of calls used at least 60% of context\.$/u, replace: '$1 的调用使用了至少 60% 的上下文窗口。' },
+  { pattern: /^([\d,.]+) shell calls across ([\d,.]+) command roots\.$/u, replace: '$1 次 Shell 调用，涉及 $2 个根命令。' },
+  { pattern: /^Terminal\/tool outputs account for ([\d,.]+) parsed output tokens\.$/u, replace: '终端/工具输出共占 $1 个已解析输出token。' },
+  { pattern: /^([\d,.]+) positive visible-usage spans are available\.$/u, replace: '现有 $1 个可见用量正向变化区间。' },
+];
+
+function translateEmbeddedUiText(value: string): string {
+  const exact = diagnosticsReportsZhHansTranslations[value];
+  if (exact) return exact;
+  let match = value.match(/^([\d,.]+) loaded calls are fast-tagged or low effort\. Duration is a proxy, not a quality score\.$/u);
+  if (match) return `${match[1]} 次已加载调用带有快速标签或采用低推理强度。耗时只是代理指标，并非质量评分。`;
+  match = value.match(/^([\d,.]+) highest-cost loaded calls anchor this report\. Estimates use the local pricing model\.$/u);
+  if (match) return `此报告以成本最高的 ${match[1]} 次已加载调用为核心，估算采用本地定价模型。`;
+  match = value.match(/^([\d,.]+) highest credit-impact loaded calls support the selected usage report\.$/u);
+  if (match) return `点数影响最高的 ${match[1]} 次已加载调用为所选用量报告提供证据。`;
+  match = value.match(/^([A-Za-z][A-Za-z0-9 ._-]*) observed$/u);
+  if (match) return `${match[1]} 观测值`;
+  match = value.match(/^([A-Za-z][A-Za-z0-9 ._-]*) trend$/u);
+  if (match) return `${match[1]} 趋势`;
+  return value;
+}
+
+function translateSortDescription(value: string): string {
+  const match = value.match(/^sorted by (.+) (descending|ascending)$/u);
+  if (!match) return translateEmbeddedUiText(value);
+  return `按${translateEmbeddedUiText(match[1])}${match[2] === 'descending' ? '降序' : '升序'}排列`;
+}
+
+function translateHistoryScope(value: string): string {
+  if (value === 'active') return '活动会话';
+  if (value === 'all') return '全部历史记录';
+  return value;
+}
+
+function translateShortTimestamp(value: string): string {
+  const match = value.match(/^(Jan|Feb|Mar|Apr|May|Jun|Jul|Aug|Sep|Oct|Nov|Dec) ([\d]{1,2}), ([\d]{1,2}):([\d]{2}) (AM|PM)$/u);
+  if (!match) return value;
+  const months: Readonly<Record<string, number>> = {
+    Jan: 1,
+    Feb: 2,
+    Mar: 3,
+    Apr: 4,
+    May: 5,
+    Jun: 6,
+    Jul: 7,
+    Aug: 8,
+    Sep: 9,
+    Oct: 10,
+    Nov: 11,
+    Dec: 12,
+  };
+  const hour12 = Number(match[3]);
+  const hour24 = match[5] === 'PM' ? (hour12 % 12) + 12 : hour12 % 12;
+  return `${months[match[1]]}月${Number(match[2])}日 ${String(hour24).padStart(2, '0')}:${match[4]}`;
+}
+
+function translateAllowanceMetadata(value: string): string {
+  return value
+    .split(' · ')
+    .map(part => {
+      if (part.startsWith('plan ')) return `套餐 ${part.slice(5)}`;
+      if (part.startsWith('limit ')) return `限制 ${part.slice(6)}`;
+      if (part.startsWith('observed ')) return `观察于 ${part.slice(9)}`;
+      return part;
+    })
+    .join(' · ');
+}
+
+function translateAllowanceWindowValue(value: string): string {
+  return value
+    .split(' · ')
+    .map(part => {
+      const percent = part.match(/^([\d.]+%) (remaining|used)$/u);
+      if (percent) return percent[2] === 'remaining' ? `剩余 ${percent[1]}` : `已用 ${percent[1]}`;
+      const credits = part.match(/^([\d,.]+) cr (left|total)$/u);
+      if (credits) return credits[2] === 'left' ? `剩余 ${credits[1]} 点` : `总计 ${credits[1]} 点`;
+      if (part.startsWith('resets ')) return `重置于 ${part.slice(7)}`;
+      return part;
+    })
+    .join(' · ');
+}
+
+function translatePrivacyMetadata(value: string): string {
+  const separator = value.indexOf(': ');
+  if (separator < 0) return value;
+  const mode = value.slice(0, separator);
+  const flagTranslations: Readonly<Record<string, string>> = {
+    'cwd redacted': '工作目录已脱敏',
+    'project names redacted': '项目名称已脱敏',
+    'git remote hidden': 'Git 远程信息已隐藏',
+    'relative cwd hidden': '相对工作目录已隐藏',
+    'git branch hidden': 'Git 分支已隐藏',
+    'tags hidden': '标签已隐藏',
+    'aliases preserved': '已保留别名',
+  };
+  const flags = value
+    .slice(separator + 2)
+    .split(', ')
+    .map(flag => flagTranslations[flag] ?? flag)
+    .join('、');
+  return `${mode}：${flags}`;
+}
diff --git a/frontend/dashboard/src/app/zh-Hans/translate.test.ts b/frontend/dashboard/src/app/zh-Hans/translate.test.ts
new file mode 100644
index 00000000..0103f186
--- /dev/null
+++ b/frontend/dashboard/src/app/zh-Hans/translate.test.ts
@@ -0,0 +1,95 @@
+import { describe, expect, it } from 'vitest';
+
+import { translateZhHansUiText, type CatalogTemplateTranslation } from './translate';
+
+describe('Simplified Chinese React fallback translations', () => {
+  it('uses the supplemental catalog for React-only interface text', () => {
+    expect(translateZhHansUiText('Diagnostics Notebook')).toBe('诊断工作台');
+    expect(translateZhHansUiText('The important changes first, with direct paths into supporting evidence.'))
+      .toBe('优先展示重要变化，并可直接查看支撑证据。');
+  });
+
+  it('reuses translations from the canonical dashboard catalog', () => {
+    const catalog = new Map([['Calls', '调用']]);
+    expect(translateZhHansUiText('Calls', catalog)).toBe('调用');
+  });
+
+  it('formats dynamic React messages without changing their values', () => {
+    expect(translateZhHansUiText('Loaded 250 of 1,000 available calls'))
+      .toBe('已加载 250 / 1,000 次可用调用');
+    expect(translateZhHansUiText('12 calls analyzed · 8 detail rows cached'))
+      .toBe('已分析 12 次调用 · 已缓存 8 条详情记录');
+    expect(translateZhHansUiText('All time analysis ready across 3,302 calls; 3,302 detail rows cached'))
+      .toBe('全部时间范围分析已就绪，共 3,302 次调用；已缓存 3,302 条详情记录');
+    expect(translateZhHansUiText('347.29M cached input tokens'))
+      .toBe('347.29M 个缓存输入token');
+    expect(translateZhHansUiText('3302 calls in the selected scope include 95 percent cached input reuse.'))
+      .toBe('所选范围内的 3302 次调用中，缓存输入复用率为 95%。');
+  });
+
+  it('localizes compact visualization and signal labels', () => {
+    expect(translateZhHansUiText('Day')).toBe('日期');
+    expect(translateZhHansUiText('From')).toBe('来源');
+    expect(translateZhHansUiText('FILTERS')).toBe('筛选');
+    expect(translateZhHansUiText('Filters')).toBe('筛选');
+    expect(translateZhHansUiText('PRICE')).toBe('定价');
+    expect(translateZhHansUiText('CTX')).toBe('上下文');
+    expect(translateZhHansUiText('blank')).toBe('未指定');
+    expect(translateZhHansUiText('xhigh')).toBe('超高');
+    expect(translateZhHansUiText('Jul 15, 10:19 PM · Call 1'))
+      .toBe('7月15日 22:19 · 第 1 次调用');
+    expect(translateZhHansUiText('234.45K at Jul 15, 10:30 PM'))
+      .toBe('234.45K，发生于 7月15日 22:30');
+    expect(translateZhHansUiText('xhigh x285, high x59')).toBe('超高 ×285、高 ×59');
+    expect(translateZhHansUiText('1,485.81 credits (Official match)'))
+      .toBe('1,485.81 点（官方精确匹配）');
+    expect(translateZhHansUiText('Prev 25s')).toBe('距上次 25 秒');
+    expect(translateZhHansUiText('Today: 2026-07-15 to 2026-07-15'))
+      .toBe('今天：2026-07-15 至 2026-07-15');
+    expect(translateZhHansUiText('Cache Risk')).toBe('缓存风险');
+    expect(translateZhHansUiText('Pro observed')).toBe('Pro 观测值');
+  });
+
+  it('translates nested report findings', () => {
+    expect(translateZhHansUiText('Cost Curves contains 10 plotted rows. 8 highest-cost loaded calls anchor this report. Estimates use the local pricing model.'))
+      .toBe('成本曲线包含 10 条绘图记录。此报告以成本最高的 8 次已加载调用为核心，估算采用本地定价模型。');
+  });
+
+  it('covers the advanced investigation, limits, and cache workspaces', () => {
+    expect(translateZhHansUiText('Root-cause workspace')).toBe('根因分析工作区');
+    expect(translateZhHansUiText('Cache And Context Lab')).toBe('缓存与上下文实验室');
+    expect(translateZhHansUiText('Weekly evidence first, rolling-window context second, and no claim beyond the loaded local data.'))
+      .toBe('以每周证据为主、滚动窗口上下文为辅，结论不超出已加载的本地数据。');
+  });
+
+  it('localizes chart accessibility labels and contract errors', () => {
+    expect(translateZhHansUiText('Tokens line chart')).toBe('token折线图');
+    expect(translateZhHansUiText('Visualization contract error')).toBe('可视化定义错误');
+    expect(translateZhHansUiText('must include at least one series')).toBe('必须至少包含一个数据系列');
+  });
+
+  it('hydrates canonical placeholder templates', () => {
+    const templates: CatalogTemplateTranslation[] = [{
+      pattern: /^Loaded (.+?) of (.+?) calls$/u,
+      placeholders: ['loaded', 'total'],
+      translatedTemplate: '已加载 {loaded}/{total} 次调用',
+    }];
+    expect(translateZhHansUiText('Loaded 3 of 9 calls', new Map(), templates))
+      .toBe('已加载 3/9 次调用');
+  });
+
+  it('prefers precise React patterns over broad catalog templates', () => {
+    const templates: CatalogTemplateTranslation[] = [{
+      pattern: /^Showing (.+?) of (.+?) (.+)$/u,
+      placeholders: ['shown', 'total', 'kind'],
+      translatedTemplate: '{kind}：已显示 {shown}/{total}',
+    }];
+    expect(translateZhHansUiText('Showing 2 of 3 aggregate rows', new Map(), templates))
+      .toBe('显示 2 / 3 条聚合记录');
+  });
+
+  it('leaves unknown data values unchanged', () => {
+    expect(translateZhHansUiText('gpt-5.4')).toBe('gpt-5.4');
+    expect(translateZhHansUiText('/Users/example/project')).toBe('/Users/example/project');
+  });
+});
diff --git a/frontend/dashboard/src/app/zh-Hans/translate.ts b/frontend/dashboard/src/app/zh-Hans/translate.ts
new file mode 100644
index 00000000..ecc4edd1
--- /dev/null
+++ b/frontend/dashboard/src/app/zh-Hans/translate.ts
@@ -0,0 +1,86 @@
+import { advancedPagesZhHansPatterns, advancedPagesZhHansTranslations } from './advancedPages';
+import { commonZhHansPatterns, commonZhHansTranslations } from './common';
+import { corePagesZhHansPatterns, corePagesZhHansTranslations } from './corePages';
+import {
+  diagnosticsReportsZhHansPatterns,
+  diagnosticsReportsZhHansTranslations,
+} from './diagnosticsReports';
+import type { ZhHansPattern } from './types';
+
+const supplementalTranslations: Readonly<Record<string, string>> = {
+  ...commonZhHansTranslations,
+  ...corePagesZhHansTranslations,
+  ...diagnosticsReportsZhHansTranslations,
+  ...advancedPagesZhHansTranslations,
+};
+
+const supplementalPatterns: ReadonlyArray<ZhHansPattern> = [
+  ...corePagesZhHansPatterns,
+  ...diagnosticsReportsZhHansPatterns,
+  ...advancedPagesZhHansPatterns,
+  ...commonZhHansPatterns,
+];
+
+export type CatalogTemplateTranslation = {
+  pattern: RegExp;
+  placeholders: string[];
+  translatedTemplate: string;
+};
+
+export function translateZhHansUiText(
+  value: string,
+  catalogTranslations: ReadonlyMap<string, string> = new Map(),
+  catalogTemplates: ReadonlyArray<CatalogTemplateTranslation> = [],
+): string {
+  if (!value || !/[A-Za-z]/u.test(value)) return value;
+
+  const exact = supplementalTranslations[value] ?? catalogTranslations.get(value);
+  if (exact) return localizeEmbeddedZhHansFragments(exact);
+
+  for (const { pattern, replace } of supplementalPatterns) {
+    if (!pattern.test(value)) continue;
+    pattern.lastIndex = 0;
+    const translated = typeof replace === 'string'
+      ? value.replace(pattern, replace)
+      : value.replace(pattern, (...matches) => replace(...matches.map(String)));
+    return localizeEmbeddedZhHansFragments(translated);
+  }
+
+  for (const template of catalogTemplates) {
+    const match = value.match(template.pattern);
+    if (!match) continue;
+    const values = new Map<string, string>();
+    template.placeholders.forEach((placeholder, index) => values.set(placeholder, match[index + 1]));
+    return localizeEmbeddedZhHansFragments(template.translatedTemplate.replace(/\{([A-Za-z][A-Za-z0-9_]*)\}/gu, (_token, placeholder) => (
+      values.get(String(placeholder)) ?? String(_token)
+    )));
+  }
+  return localizeEmbeddedZhHansFragments(value);
+}
+
+const monthNumberByEnglishShortName: Readonly<Record<string, number>> = {
+  Jan: 1,
+  Feb: 2,
+  Mar: 3,
+  Apr: 4,
+  May: 5,
+  Jun: 6,
+  Jul: 7,
+  Aug: 8,
+  Sep: 9,
+  Oct: 10,
+  Nov: 11,
+  Dec: 12,
+};
+
+function localizeEmbeddedZhHansFragments(value: string): string {
+  return value.replace(
+    /\b(Jan|Feb|Mar|Apr|May|Jun|Jul|Aug|Sep|Oct|Nov|Dec) (\d{1,2})(?:, (\d{4}))?(?:,? (\d{1,2}):(\d{2}) (AM|PM))?\b/gu,
+    (_match, monthName, day, year, hour, minute, period) => {
+      const date = `${year ? `${year}年` : ''}${monthNumberByEnglishShortName[String(monthName)]}月${day}日`;
+      if (!hour || !minute || !period) return date;
+      const hourValue = Number(hour) % 12 + (period === 'PM' ? 12 : 0);
+      return `${date} ${String(hourValue).padStart(2, '0')}:${minute}`;
+    },
+  );
+}
diff --git a/frontend/dashboard/src/app/zh-Hans/types.ts b/frontend/dashboard/src/app/zh-Hans/types.ts
new file mode 100644
index 00000000..b2acc17a
--- /dev/null
+++ b/frontend/dashboard/src/app/zh-Hans/types.ts
@@ -0,0 +1,4 @@
+export type ZhHansPattern = {
+  pattern: RegExp;
+  replace: string | ((...matches: string[]) => string);
+};
diff --git a/frontend/dashboard/src/charts/LineChart.tsx b/frontend/dashboard/src/charts/LineChart.tsx
index ae71ed7e..0737d0a0 100644
--- a/frontend/dashboard/src/charts/LineChart.tsx
+++ b/frontend/dashboard/src/charts/LineChart.tsx
@@ -4,6 +4,7 @@ import { line } from 'd3-shape';
 import { useLayoutEffect, useRef, useState } from 'react';
 
 import type { Series } from '../api/types';
+import { useShellI18n } from '../app/i18nContext';
 
 type LineChartProps = {
   series: Series[];
@@ -15,6 +16,7 @@ type LineChartProps = {
 const dateLabelWidth = 38;
 
 export function LineChart({ series, yLabel, valueFormatter = defaultFormatter, height = 280 }: LineChartProps) {
+  const i18n = useShellI18n();
   const scrollRef = useRef<HTMLDivElement>(null);
   const [viewportWidth, setViewportWidth] = useState(0);
   const labels = series[0]?.points.map(point => point.label) ?? [];
@@ -87,15 +89,15 @@ export function LineChart({ series, yLabel, valueFormatter = defaultFormatter, h
   }, [labels.length, width]);
 
   return (
-    <div className="line-chart-frame" role="img" aria-label={`${yLabel} line chart`}>
-      {hasScrollableHistory ? <div className="chart-scroll-cue">Recent dates shown. Scroll left for earlier dates.</div> : null}
+    <div className="line-chart-frame" role="img" aria-label={i18n.translateText(`${yLabel} line chart`)}>
+      {hasScrollableHistory ? <div className="chart-scroll-cue">{i18n.translateText('Recent dates shown. Scroll left for earlier dates.')}</div> : null}
       <div className="chart-scroll-shell">
         <div
           className="chart-scroll"
           ref={scrollRef}
           role="region"
           tabIndex={hasScrollableHistory ? 0 : undefined}
-          aria-label={`${yLabel} history. Recent dates are shown first; scroll left for earlier dates.`}
+          aria-label={i18n.translateText(`${yLabel} history. Recent dates are shown first; scroll left for earlier dates.`)}
         >
           <svg className="chart" viewBox={`0 0 ${width} ${height}`} width={width} height={height}>
             {ticks.map(tick => (
diff --git a/frontend/dashboard/src/components/DataTable.tsx b/frontend/dashboard/src/components/DataTable.tsx
index 2a382f30..09dd9d78 100644
--- a/frontend/dashboard/src/components/DataTable.tsx
+++ b/frontend/dashboard/src/components/DataTable.tsx
@@ -4,12 +4,15 @@ import {
   getSortedRowModel,
   useReactTable,
   type ColumnDef,
+  type ColumnDefTemplate,
+  type HeaderContext,
   type OnChangeFn,
   type SortingState,
   type VisibilityState,
 } from '@tanstack/react-table';
 import { ArrowDown, ArrowUp, ChevronsUpDown } from 'lucide-react';
 import { useState } from 'react';
+import { useShellI18n } from '../app/i18nContext';
 
 type DataTableProps<T> = {
   columns: Array<ColumnDef<T>>;
@@ -37,6 +40,20 @@ type DataTableProps<T> = {
 
 const defaultVisibleRows = 250;
 const defaultVisibleRowsIncrement = 250;
+const userDataColumnIds = new Set([
+  'branch',
+  'command',
+  'cwd',
+  'file',
+  'model',
+  'name',
+  'path',
+  'project',
+  'record_id',
+  'remote',
+  'session',
+  'thread',
+]);
 
 export function DataTable<T>({
   columns,
@@ -61,6 +78,7 @@ export function DataTable<T>({
   visibleRowCount,
   onVisibleRowCountChange,
 }: DataTableProps<T>) {
+const i18n = useShellI18n();
 const [internalSorting, setInternalSorting] = useState<SortingState>([]);
 const [internalVisibleRowCount, setInternalVisibleRowCount] = useState(initialVisibleRows);
 const tableSorting = sorting ?? internalSorting;
@@ -94,7 +112,10 @@ setInternalVisibleRowCount(nextVisibleRowCount);
   return (
     <div className="table-window">
       <div className="table-scroll">
-        <table className={compact ? 'data-table compact' : 'data-table'} aria-label={ariaLabel}>
+        <table
+          className={compact ? 'data-table compact' : 'data-table'}
+          aria-label={ariaLabel ? i18n.translateText(ariaLabel) : undefined}
+        >
           <thead>
             {table.getHeaderGroups().map(headerGroup => (
               <tr key={headerGroup.id}>
@@ -111,13 +132,13 @@ setInternalVisibleRowCount(nextVisibleRowCount);
                           className="sort-header"
                           type="button"
                           onClick={header.column.getToggleSortingHandler()}
-                          aria-label={`Sort by ${headerLabel(header.column.columnDef.header)}`}
+                          aria-label={i18n.translateText(`Sort by ${i18n.translateText(headerLabel(header.column.columnDef.header))}`)}
                         >
-                          {flexRender(header.column.columnDef.header, header.getContext())}
+                          {localizedHeader(header.column.columnDef.header, header.getContext(), i18n.translateText)}
                           {sorted === 'asc' ? <ArrowUp size={13} /> : sorted === 'desc' ? <ArrowDown size={13} /> : <ChevronsUpDown size={13} />}
                         </button>
                       ) : (
-                        flexRender(header.column.columnDef.header, header.getContext())
+                        localizedHeader(header.column.columnDef.header, header.getContext(), i18n.translateText)
                       )}
                     </th>
                   );
@@ -162,9 +183,9 @@ setInternalVisibleRowCount(nextVisibleRowCount);
                       (onRowActivate
                         ? onRowSelect
                           ? activateOnClick
-                            ? 'Click opens full investigator. Hover or press Space previews details.'
-                            : 'Click to inspect details. Double-click or press Enter open full investigator.'
-                          : 'Click or press Enter open the full investigator.'
+                            ? i18n.translateText('Click opens full investigator. Hover or press Space previews details.')
+                            : i18n.translateText('Click to inspect details. Double-click or press Enter open full investigator.')
+                          : i18n.translateText('Click or press Enter open the full investigator.')
                         : undefined)
                     }
                     onClick={isInteractive ? clickRow : undefined}
@@ -190,7 +211,11 @@ setInternalVisibleRowCount(nextVisibleRowCount);
                     }
                   >
                 {row.getVisibleCells().map(cell => (
-                  <td key={cell.id} className={stickyColumnClass(cell.column.id)}>
+                  <td
+                    key={cell.id}
+                    className={stickyColumnClass(cell.column.id)}
+                    data-localization-skip={isUserDataColumn(cell.column.id) ? 'true' : undefined}
+                  >
                     {flexRender(cell.column.columnDef.cell, cell.getContext())}
                   </td>
                 ))}
@@ -200,7 +225,7 @@ setInternalVisibleRowCount(nextVisibleRowCount);
             ) : (
               <tr>
                 <td colSpan={Math.max(table.getVisibleLeafColumns().length, 1)} className="empty-cell">
-                  {emptyLabel}
+                  {i18n.translateText(emptyLabel)}
                 </td>
               </tr>
             )}
@@ -210,10 +235,10 @@ setInternalVisibleRowCount(nextVisibleRowCount);
       {hiddenRowCount ? (
         <div className="table-window-footer">
           <span>
-            Showing {visibleRows.length.toLocaleString()} of {rows.length.toLocaleString()} table rows
+            {i18n.translateText(`Showing ${visibleRows.length.toLocaleString()} of ${rows.length.toLocaleString()} table rows`)}
           </span>
           <button type="button" className="inline-button" onClick={showMoreRows}>
-            Show {Math.min(visibleRowsIncrement, hiddenRowCount).toLocaleString()} more rows
+            {i18n.translateText(`Show ${Math.min(visibleRowsIncrement, hiddenRowCount).toLocaleString()} more rows`)}
           </button>
         </div>
       ) : null}
@@ -225,6 +250,19 @@ function headerLabel(header: unknown): string {
   return typeof header === 'string' ? header : 'column';
 }
 
+function localizedHeader<TData, TValue>(
+  header: ColumnDefTemplate<HeaderContext<TData, TValue>> | undefined,
+  context: HeaderContext<TData, TValue>,
+  translate: (value: string) => string,
+) {
+  if (typeof header === 'string') return translate(header);
+  return header ? flexRender(header, context) : null;
+}
+
+function isUserDataColumn(columnId: string): boolean {
+  return userDataColumnIds.has(columnId);
+}
+
 function stickyColumnClass(columnId: string): string | undefined {
   return columnId === 'thread' || columnId === 'name' ? 'sticky-column' : undefined;
 }
diff --git a/frontend/dashboard/src/components/MetricCard.tsx b/frontend/dashboard/src/components/MetricCard.tsx
index 8de66d6b..91cbc3fd 100644
--- a/frontend/dashboard/src/components/MetricCard.tsx
+++ b/frontend/dashboard/src/components/MetricCard.tsx
@@ -1,6 +1,7 @@
 import { Activity, CircleDollarSign, Database, Gauge, PhoneCall, type LucideIcon } from 'lucide-react';
 
 import type { MetricCard as MetricCardModel } from '../api/types';
+import { useShellI18n } from '../app/i18nContext';
 
 const iconByLabel: Record<string, LucideIcon> = {
   'Cache Hit Rate': Database,
@@ -13,6 +14,7 @@ const iconByLabel: Record<string, LucideIcon> = {
 };
 
 export function MetricCard({ card }: { card: MetricCardModel }) {
+  const i18n = useShellI18n();
   const Icon = iconByLabel[card.label] ?? Activity;
   const trendTone = card.trend.startsWith('down') || card.trend.includes('risk') ? 'negative' : 'positive';
 
@@ -22,20 +24,20 @@ export function MetricCard({ card }: { card: MetricCardModel }) {
         <Icon size={22} />
       </div>
       <div className="metric-copy">
-        <p>{card.label}</p>
+        <p>{i18n.translateText(card.label)}</p>
         <strong>{card.value}</strong>
         {card.breakdown?.length ? (
-          <dl className="metric-breakdown" aria-label={`${card.label} breakdown`}>
+          <dl className="metric-breakdown" aria-label={i18n.translateText(`${card.label} breakdown`)}>
             {card.breakdown.map(item => (
               <div key={item.label}>
-                <dt>{item.label}</dt>
+                <dt>{i18n.translateText(item.label)}</dt>
                 <dd>{item.value}</dd>
               </div>
             ))}
           </dl>
         ) : null}
-        <span className={`trend ${trendTone}`}>{card.trend}</span>
-        <small>{card.detail}</small>
+        <span className={`trend ${trendTone}`}>{i18n.translateText(card.trend)}</span>
+        <small>{i18n.translateText(card.detail)}</small>
       </div>
     </article>
   );
diff --git a/frontend/dashboard/src/components/Panel.tsx b/frontend/dashboard/src/components/Panel.tsx
index ab18b93c..a410c344 100644
--- a/frontend/dashboard/src/components/Panel.tsx
+++ b/frontend/dashboard/src/components/Panel.tsx
@@ -1,4 +1,5 @@
 import type { ReactNode } from 'react';
+import { useShellI18n } from '../app/i18nContext';
 
 type PanelProps = {
   title: string;
@@ -9,12 +10,13 @@ type PanelProps = {
 };
 
 export function Panel({ title, subtitle, action, children, className = '' }: PanelProps) {
+  const i18n = useShellI18n();
   return (
     <section className={`panel ${className}`.trim()}>
       <div className="panel-header">
         <div>
-          <h2>{title}</h2>
-          {subtitle ? <p>{subtitle}</p> : null}
+          <h2>{i18n.translateText(title)}</h2>
+          {subtitle ? <p>{i18n.translateText(subtitle)}</p> : null}
         </div>
         {action ? <div className="panel-action">{action}</div> : null}
       </div>
diff --git a/frontend/dashboard/src/components/StatusBadge.tsx b/frontend/dashboard/src/components/StatusBadge.tsx
index 165b3be4..f544bffe 100644
--- a/frontend/dashboard/src/components/StatusBadge.tsx
+++ b/frontend/dashboard/src/components/StatusBadge.tsx
@@ -1,4 +1,5 @@
 import type { MetricTone } from '../api/types';
+import { useShellI18n } from '../app/i18nContext';
 
 type StatusBadgeProps = {
   label: string;
@@ -6,5 +7,6 @@ type StatusBadgeProps = {
 };
 
 export function StatusBadge({ label, tone = 'neutral' }: StatusBadgeProps) {
-  return <span className={`status-badge ${tone}`}>{label}</span>;
+  const i18n = useShellI18n();
+  return <span className={`status-badge ${tone}`}>{i18n.translateText(label)}</span>;
 }
diff --git a/frontend/dashboard/src/design/PageLoadProgress.tsx b/frontend/dashboard/src/design/PageLoadProgress.tsx
index 1fdbe2c9..93b46f05 100644
--- a/frontend/dashboard/src/design/PageLoadProgress.tsx
+++ b/frontend/dashboard/src/design/PageLoadProgress.tsx
@@ -1,4 +1,5 @@
 import type { DashboardModuleState } from '../data/dashboardQueryRegistry';
+import { useShellI18n } from '../app/i18nContext';
 import styles from './PageLoadProgress.module.css';
 
 export type PageLoadProgressProps = {
@@ -25,9 +26,14 @@ export function PageLoadProgress({
   modules,
   updating = false,
 }: PageLoadProgressProps) {
+  const i18n = useShellI18n();
   if (!active && !error) return null;
   if (!active && error) {
-    return <div className={styles.error} role="alert">Incomplete page evidence: {error}</div>;
+    return (
+      <div className={styles.error} role="alert">
+        {i18n.translateText(`Incomplete page evidence: ${error}`)}
+      </div>
+    );
   }
 
   const determinate = typeof total === 'number' && total > 0;
@@ -37,13 +43,15 @@ export function PageLoadProgress({
   return (
     <section className={styles.root} aria-live="polite">
       <div className={styles.copy}>
-        <strong>{updating ? 'Updating page evidence' : label}</strong>
-        {determinate ? <span>{safeCompleted} of {total} modules ready</span> : <span>Working on full-scope evidence</span>}
+        <strong>{i18n.translateText(updating ? 'Updating page evidence' : label)}</strong>
+        {determinate
+          ? <span>{i18n.translateText(`${safeCompleted} of ${total} modules ready`)}</span>
+          : <span>{i18n.translateText('Working on full-scope evidence')}</span>}
       </div>
       <div
         className={`${styles.track} ${modules?.length ? styles.segmentedTrack : ''}`}
         role="progressbar"
-        aria-label={label}
+        aria-label={i18n.translateText(label)}
         aria-valuemin={determinate ? 0 : undefined}
         aria-valuemax={determinate ? total : undefined}
         aria-valuenow={determinate ? safeCompleted : undefined}
@@ -61,15 +69,15 @@ export function PageLoadProgress({
             />}
       </div>
       {modules?.length ? (
-        <div className={styles.modules} aria-label={`${label} modules`}>
+        <div className={styles.modules} aria-label={i18n.translateText(`${i18n.translateText(label)} modules`)}>
           {modules.map(module => (
             <span className={styles.module} key={module.label}>
-              {module.label} {moduleStatusLabel(module.status)}
+              {i18n.translateText(module.label)} {i18n.translateText(moduleStatusLabel(module.status))}
             </span>
           ))}
         </div>
       ) : null}
-      {error ? <div className={styles.inlineError} role="alert">{error}</div> : null}
+      {error ? <div className={styles.inlineError} role="alert">{i18n.translateText(error)}</div> : null}
     </section>
   );
 }
diff --git a/frontend/dashboard/src/design/primitives/Primitives.tsx b/frontend/dashboard/src/design/primitives/Primitives.tsx
index f5ee68ed..e7079850 100644
--- a/frontend/dashboard/src/design/primitives/Primitives.tsx
+++ b/frontend/dashboard/src/design/primitives/Primitives.tsx
@@ -5,6 +5,7 @@ import type {
   ReactNode,
 } from 'react';
 
+import { useShellI18n } from '../../app/i18nContext';
 import styles from './primitives.module.css';
 
 function classes(...values: Array<string | false | undefined>) {
@@ -18,10 +19,15 @@ interface ButtonProps extends ButtonHTMLAttributes<HTMLButtonElement> {
 }
 
 export const Button = forwardRef<HTMLButtonElement, ButtonProps>(function Button(
-  { className, type = 'button', variant = 'secondary', ...props },
+  { children, className, type = 'button', variant = 'secondary', ...props },
   ref,
 ) {
-  return <button ref={ref} type={type} className={classes(styles.button, styles[variant], className)} {...props} />;
+  const i18n = useShellI18n();
+  return (
+    <button ref={ref} type={type} className={classes(styles.button, styles[variant], className)} {...props}>
+      {localizedNode(children, i18n.translateText)}
+    </button>
+  );
 });
 
 interface IconButtonProps extends ButtonHTMLAttributes<HTMLButtonElement> {
@@ -29,10 +35,20 @@ interface IconButtonProps extends ButtonHTMLAttributes<HTMLButtonElement> {
 }
 
 export const IconButton = forwardRef<HTMLButtonElement, IconButtonProps>(function IconButton(
-  { className, type = 'button', ...props },
+  { 'aria-label': ariaLabel, className, title, type = 'button', ...props },
   ref,
 ) {
-  return <button ref={ref} type={type} className={classes(styles.iconButton, className)} {...props} />;
+  const i18n = useShellI18n();
+  return (
+    <button
+      ref={ref}
+      type={type}
+      aria-label={i18n.translateText(ariaLabel)}
+      title={typeof title === 'string' ? i18n.translateText(title) : title}
+      className={classes(styles.iconButton, className)}
+      {...props}
+    />
+  );
 });
 
 type StatusTone = 'neutral' | 'positive' | 'caution' | 'risk' | 'context';
@@ -42,10 +58,15 @@ interface StatusBadgeProps extends HTMLAttributes<HTMLSpanElement> {
 }
 
 export const StatusBadge = forwardRef<HTMLSpanElement, StatusBadgeProps>(function StatusBadge(
-  { className, tone = 'neutral', ...props },
+  { children, className, tone = 'neutral', ...props },
   ref,
 ) {
-  return <span ref={ref} className={classes(styles.badge, styles[tone], className)} {...props} />;
+  const i18n = useShellI18n();
+  return (
+    <span ref={ref} className={classes(styles.badge, styles[tone], className)} {...props}>
+      {localizedNode(children, i18n.translateText)}
+    </span>
+  );
 });
 
 interface SurfaceProps extends HTMLAttributes<HTMLDivElement> {
@@ -69,11 +90,12 @@ export const MetricReadout = forwardRef<HTMLDivElement, MetricReadoutProps>(func
   { className, detail, label, value, ...props },
   ref,
 ) {
+  const i18n = useShellI18n();
   return (
     <div ref={ref} className={classes(styles.metric, className)} {...props}>
-      <span className={styles.metricLabel}>{label}</span>
+      <span className={styles.metricLabel}>{localizedNode(label, i18n.translateText)}</span>
       <strong className={styles.metricValue}>{value}</strong>
-      {detail ? <span className={styles.metricDetail}>{detail}</span> : null}
+      {detail ? <span className={styles.metricDetail}>{localizedNode(detail, i18n.translateText)}</span> : null}
     </div>
   );
 });
@@ -100,8 +122,9 @@ export function SegmentedControl<T extends string>({
   value,
   ...props
 }: SegmentedControlProps<T>) {
+  const i18n = useShellI18n();
   return (
-    <div role="group" aria-label={label} className={classes(styles.segments, className)} {...props}>
+    <div role="group" aria-label={i18n.translateText(label)} className={classes(styles.segments, className)} {...props}>
       {options.map((option) => (
         <button
           key={option.value}
@@ -111,7 +134,7 @@ export function SegmentedControl<T extends string>({
           disabled={option.disabled}
           onClick={() => onValueChange(option.value)}
         >
-          {option.label}
+          {localizedNode(option.label, i18n.translateText)}
         </button>
       ))}
     </div>
@@ -129,6 +152,7 @@ export const ProgressBar = forwardRef<HTMLDivElement, ProgressBarProps>(function
   { className, label, max = 100, showValue = true, value, ...props },
   ref,
 ) {
+  const i18n = useShellI18n();
   const labelId = useId();
   const safeMax = max > 0 ? max : 100;
   const safeValue = Math.min(Math.max(value, 0), safeMax);
@@ -137,7 +161,7 @@ export const ProgressBar = forwardRef<HTMLDivElement, ProgressBarProps>(function
   return (
     <div ref={ref} className={classes(styles.progress, className)} {...props}>
       <div className={styles.progressHeader}>
-        <span id={labelId}>{label}</span>
+        <span id={labelId}>{localizedNode(label, i18n.translateText)}</span>
         {showValue ? <span aria-hidden="true">{percent}%</span> : null}
       </div>
       <div
@@ -153,3 +177,7 @@ export const ProgressBar = forwardRef<HTMLDivElement, ProgressBarProps>(function
     </div>
   );
 });
+
+function localizedNode(node: ReactNode, translate: (value: string) => string): ReactNode {
+  return typeof node === 'string' ? translate(node) : node;
+}
diff --git a/frontend/dashboard/src/features/cache-context/CacheContextPage.tsx b/frontend/dashboard/src/features/cache-context/CacheContextPage.tsx
index b4c1d895..88be5f54 100644
--- a/frontend/dashboard/src/features/cache-context/CacheContextPage.tsx
+++ b/frontend/dashboard/src/features/cache-context/CacheContextPage.tsx
@@ -2,6 +2,7 @@ import { Copy, Search } from 'lucide-react';
 import { useMemo, useState, type CSSProperties } from 'react';
 
 import type { CallRow, ContextRuntime, DashboardModel, HeatmapRow, ThreadRow } from '../../api/types';
+import { useShellI18n } from '../../app/i18nContext';
 import { LineChart } from '../../charts/LineChart';
 import { DataTable } from '../../components/DataTable';
 import { MetricCard } from '../../components/MetricCard';
@@ -41,6 +42,7 @@ export function CacheContextPage({
   onOpenInvestigator,
   onCopyCallLink,
 }: CacheContextPageProps) {
+  const i18n = useShellI18n();
   const [selectedThreadName, setSelectedThreadName] = useState<string | null>(cacheThreadParam);
   const evidence = useCacheContextEvidence({
     model,
@@ -160,7 +162,7 @@ activateOnClick
 selectOnHover
 ariaLabel="Cache context threads overview"
 />
-        <p className="table-caption">Showing {formatNumber(evidence.threads.length)} of {formatNumber(evidence.totalThreads)} full-scope thread summaries.</p>
+        <p className="table-caption">{i18n.translateText(`Showing ${formatNumber(evidence.threads.length)} of ${formatNumber(evidence.totalThreads)} full-scope thread summaries.`)}</p>
       </Panel>
 
 <SelectedCacheThreadPanel
@@ -190,6 +192,7 @@ heatmapWindowLabels,
   onOpenInvestigator: (recordId: string) => void;
   onCopyCallLink: (recordId: string) => void;
 }) {
+  const i18n = useShellI18n();
   if (!selectedThread) {
     return (
       <aside className="side-panel">
@@ -206,7 +209,7 @@ heatmapWindowLabels,
         <div className="finding-module">
           <div className="section-heading compact">
             <h3>Efficiency Profile</h3>
-            <span>{selectedThread.coldResumeRisk} risk</span>
+            <span>{i18n.translateText(`${selectedThread.coldResumeRisk} risk`)}</span>
           </div>
           <div className="evidence-list">
             <span>
@@ -314,10 +317,10 @@ return (
       <div className="finding-module">
         <h3>Diagnosis Basis</h3>
         <ul className="compact-list">
-          <li>Risk: {selectedThread.coldResumeRisk} cold-resume score</li>
-          <li>Cache: {pct(selectedThread.cachePct)} hit rate; action threshold below 35%</li>
-          <li>Cost: {money(selectedThread.costPerCall)} per call; inspect threshold above $1.00</li>
-          <li>Evidence: {calls.length} loaded calls, {heatmap ? `${heatmap.values.length} cache windows` : 'no heatmap row'}</li>
+          <li>{i18n.translateText(`Risk: ${selectedThread.coldResumeRisk} cold-resume score`)}</li>
+          <li>{i18n.translateText(`Cache: ${pct(selectedThread.cachePct)} hit rate; action threshold below 35%`)}</li>
+          <li>{i18n.translateText(`Cost: ${money(selectedThread.costPerCall)} per call; inspect threshold above $1.00`)}</li>
+          <li>{i18n.translateText(`Evidence: ${calls.length} loaded calls, ${heatmap ? `${heatmap.values.length} cache windows` : 'no heatmap row'}`)}</li>
         </ul>
       </div>
 
diff --git a/frontend/dashboard/src/features/call-investigator/callInvestigatorReadout.test.ts b/frontend/dashboard/src/features/call-investigator/callInvestigatorReadout.test.ts
index ab40f56e..09e46518 100644
--- a/frontend/dashboard/src/features/call-investigator/callInvestigatorReadout.test.ts
+++ b/frontend/dashboard/src/features/call-investigator/callInvestigatorReadout.test.ts
@@ -17,6 +17,7 @@ const shellI18n: ShellI18n = {
   direction: 'ltr',
   languages: [],
   t: (key, fallback) => fallback ?? key,
+  translateText: value => value,
   navLabel: (_view, fallback) => fallback,
 };
 
diff --git a/frontend/dashboard/src/features/calls/CallsExplorerView.tsx b/frontend/dashboard/src/features/calls/CallsExplorerView.tsx
index ad16ea43..83843977 100644
--- a/frontend/dashboard/src/features/calls/CallsExplorerView.tsx
+++ b/frontend/dashboard/src/features/calls/CallsExplorerView.tsx
@@ -107,7 +107,7 @@ export function CallsExplorerView({ model, header, filters, table, inspector }:
             getRowId={call => call.id}
             mobile={{
               primary: call => call.thread,
-              secondary: call => `${call.time} · ${call.model} · ${formatCompact(call.totalTokens)} tokens · ${pct(call.cachedPct)} cache`,
+              secondary: call => shellI18n.translateText(`${call.time} · ${call.model} · ${formatCompact(call.totalTokens)} tokens · ${pct(call.cachedPct)} cache`),
               actionLabel: call => callInvestigatorRowLabel(call),
             }}
             sorting={table.sorting}
@@ -127,7 +127,7 @@ export function CallsExplorerView({ model, header, filters, table, inspector }:
             emptyLabel="No rows match current filters."
           />
           <div className={styles.gridFooter} aria-live="polite">
-            <span>{table.calls.length.toLocaleString()} loaded / {table.totalMatchedCalls.toLocaleString()} matched</span>
+            <span>{shellI18n.translateText(`${table.calls.length.toLocaleString()} loaded / ${table.totalMatchedCalls.toLocaleString()} matched`)}</span>
             {table.focused && table.hasNextPage ? (
               <button
                 className="toolbar-button"
@@ -159,7 +159,7 @@ export function CallsExplorerView({ model, header, filters, table, inspector }:
           <Panel title="Cost by Model" subtitle="Estimated USD">
             <BarChart data={model.modelCosts} valueLabel={money} />
           </Panel>
-          <Panel title="Cache Hit Rate Over Time" subtitle="Daily">
+          <Panel title="Cache Hit Rate Over Time" subtitle={shellI18n.translateText('Daily')}>
             <LineChart
               series={model.cacheSeries}
               yLabel="Cache %"
diff --git a/frontend/dashboard/src/features/diagnostics/DiagnosticSnapshotMatrix.tsx b/frontend/dashboard/src/features/diagnostics/DiagnosticSnapshotMatrix.tsx
index df69d418..557839a5 100644
--- a/frontend/dashboard/src/features/diagnostics/DiagnosticSnapshotMatrix.tsx
+++ b/frontend/dashboard/src/features/diagnostics/DiagnosticSnapshotMatrix.tsx
@@ -7,6 +7,7 @@ import {
   diagnosticSnapshotDefinitions,
 } from '../../api/diagnostics';
 import type { ContextRuntime, DashboardModel } from '../../api/types';
+import { useShellI18n } from '../../app/i18nContext';
 import { Panel } from '../../components/Panel';
 import { StatusBadge } from '../../components/StatusBadge';
 import { PageLoadProgress } from '../../design';
@@ -187,6 +188,7 @@ function SnapshotCardView({
  onOpenInvestigator: (recordId: string) => void;
  onCopyCallLink: (recordId: string) => void;
 }) {
+ const i18n = useShellI18n();
  const reloading = refreshStatus === 'refreshing';
  const reloadLabel = reloading ? 'Reloading' : refreshStatus === 'error' ? 'Retry' : 'Reload';
  const visibleRows = expanded ? card.rows : card.rows.slice(0, compactSnapshotRowCount);
@@ -196,8 +198,8 @@ function SnapshotCardView({
     <article className="diagnostics-snapshot-card">
       <div className="diagnostics-snapshot-card-head">
         <div>
-          <h3>{card.title}</h3>
-          <p>{card.subtitle}</p>
+          <h3>{i18n.translateText(card.title)}</h3>
+          <p>{i18n.translateText(card.subtitle)}</p>
         </div>
         <div className="diagnostics-snapshot-card-actions">
           <StatusBadge label={card.status} tone={card.status === 'ready' ? 'green' : card.status === 'fallback' ? 'blue' : 'orange'} />
@@ -217,8 +219,8 @@ function SnapshotCardView({
       <div className="diagnostics-snapshot-metrics">
         {card.metrics.map(metric => (
           <span key={`${card.title}-${metric.label}`}>
-            <small>{metric.label}</small>
-            <strong>{metric.value}</strong>
+            <small>{i18n.translateText(metric.label)}</small>
+            <strong>{i18n.translateText(metric.value)}</strong>
           </span>
         ))}
       </div>
diff --git a/frontend/dashboard/src/features/explore/EvidenceGrid.tsx b/frontend/dashboard/src/features/explore/EvidenceGrid.tsx
index ee819010..eb1037c8 100644
--- a/frontend/dashboard/src/features/explore/EvidenceGrid.tsx
+++ b/frontend/dashboard/src/features/explore/EvidenceGrid.tsx
@@ -12,6 +12,7 @@ import { useVirtualizer } from '@tanstack/react-virtual';
 import { ChevronsRight } from 'lucide-react';
 import { useEffect, useRef, useState, type CSSProperties, type ReactNode } from 'react';
 
+import { useShellI18n } from '../../app/i18nContext';
 import styles from './EvidenceGrid.module.css';
 import type { EvidenceGridDensity } from './useEvidenceGridPreferences';
 
@@ -97,6 +98,9 @@ export function EvidenceGrid<TData>({
   mobileBreakpoint = '(max-width: 700px)',
   manualSorting = false,
 }: EvidenceGridProps<TData>) {
+  const i18n = useShellI18n();
+  const localizedAriaLabel = i18n.translateText(ariaLabel);
+  const localizedEmptyLabel = i18n.translateText(emptyLabel);
   const isMobile = useMediaQuery(mobileBreakpoint);
   const scrollRef = useRef<HTMLDivElement>(null);
   const columnChooserRef = useRef<HTMLDivElement>(null);
@@ -205,7 +209,7 @@ export function EvidenceGrid<TData>({
   }
 
   const toolbar = (
-    <div className={styles.toolbar} aria-label={`${ariaLabel} display controls`}>
+    <div className={styles.toolbar} aria-label={i18n.translateText(`${localizedAriaLabel} display controls`)}>
       <div className={styles.densityControl} role="group" aria-label="Density">
         <button type="button" aria-pressed={density === 'compact'} onClick={() => onDensityChange('compact')}>Dense</button>
         <button type="button" aria-pressed={density === 'comfortable'} onClick={() => onDensityChange('comfortable')}>Roomy</button>
@@ -239,16 +243,16 @@ export function EvidenceGrid<TData>({
 
   if (!rows.length && isMobile) {
     return (
-      <section className={styles.grid} aria-label={ariaLabel}>
+      <section className={styles.grid} aria-label={localizedAriaLabel}>
         {toolbar}
-        <p className={styles.empty} role="status">{emptyLabel}</p>
+        <p className={styles.empty} role="status">{localizedEmptyLabel}</p>
       </section>
     );
   }
 
   if (isMobile) {
     return (
-      <section className={styles.grid} aria-label={ariaLabel}>
+      <section className={styles.grid} aria-label={localizedAriaLabel}>
         {toolbar}
         <div
           ref={scrollRef}
@@ -258,7 +262,7 @@ export function EvidenceGrid<TData>({
           data-virtualized="true"
           data-virtual-row-count={virtualRows.length}
         >
-        <ol className={styles.mobileList} aria-label={`${ariaLabel} ranked list`} style={{ height: virtualizer.getTotalSize() }}>
+        <ol className={styles.mobileList} aria-label={i18n.translateText(`${ariaLabel} ranked list`)} style={{ height: virtualizer.getTotalSize() }}>
           {virtualRows.map(virtualRow => {
             const row = rows[virtualRow.index];
             if (!row) return null;
@@ -288,7 +292,7 @@ export function EvidenceGrid<TData>({
           })}
         </ol>
         </div>
-        <p className={styles.rowCount}>{rows.length.toLocaleString()} ranked evidence rows</p>
+        <p className={styles.rowCount}>{i18n.translateText(`${rows.length.toLocaleString()} ranked evidence rows`)}</p>
       </section>
     );
   }
@@ -296,7 +300,7 @@ export function EvidenceGrid<TData>({
   const tableWidth = Math.max(table.getTotalSize(), 720);
 
   return (
-    <section className={styles.grid} aria-label={ariaLabel}>
+    <section className={styles.grid} aria-label={localizedAriaLabel}>
       {toolbar}
       {canScrollRight ? (
         <button
@@ -317,14 +321,14 @@ export function EvidenceGrid<TData>({
         data-virtualized="true"
         data-virtual-row-count={virtualRows.length}
       >
-        <table className={styles.table} aria-label={ariaLabel} aria-rowcount={rows.length + 1} style={{ width: tableWidth }}>
+        <table className={styles.table} aria-label={localizedAriaLabel} aria-rowcount={rows.length + 1} style={{ width: tableWidth }}>
           <thead>
             {table.getHeaderGroups().map(headerGroup => (
               <tr key={headerGroup.id}>
                 {headerGroup.headers.map(header => {
                   const sorted = header.column.getIsSorted();
                   const frozen = header.column.id === identityColumnId;
-                  const label = headerText(header.column.columnDef.header, header.column.id);
+                  const label = i18n.translateText(headerText(header.column.columnDef.header, header.column.id));
                   return (
                     <th
                       key={header.id}
@@ -336,7 +340,7 @@ export function EvidenceGrid<TData>({
                       {header.isPlaceholder ? null : header.column.getCanSort() ? (
                         <button
                           type="button"
-                          aria-label={`Sort by ${label}`}
+                          aria-label={i18n.translateText(`Sort by ${label}`)}
                           onClick={header.column.getToggleSortingHandler()}
                         >
                           <span>{flexRender(header.column.columnDef.header, header.getContext())}</span>
@@ -387,8 +391,8 @@ export function EvidenceGrid<TData>({
           </tbody>
         </table>
       </div>
-      {!rows.length ? <p className={styles.empty} role="status">{emptyLabel}</p> : null}
-      <p className={styles.rowCount}>{rows.length.toLocaleString()} ranked evidence rows</p>
+      {!rows.length ? <p className={styles.empty} role="status">{localizedEmptyLabel}</p> : null}
+      <p className={styles.rowCount}>{i18n.translateText(`${rows.length.toLocaleString()} ranked evidence rows`)}</p>
     </section>
   );
 }
diff --git a/frontend/dashboard/src/features/investigator/InvestigatorPage.tsx b/frontend/dashboard/src/features/investigator/InvestigatorPage.tsx
index e2b826e6..e635c311 100644
--- a/frontend/dashboard/src/features/investigator/InvestigatorPage.tsx
+++ b/frontend/dashboard/src/features/investigator/InvestigatorPage.tsx
@@ -17,6 +17,7 @@ import {
   type InvestigationWalkBranch,
 } from '../../api/investigations';
 import type { CallRow, ContextRuntime, DashboardModel } from '../../api/types';
+import { useShellI18n } from '../../app/i18nContext';
 import {
   investigatorWalkQueryOptions,
 } from '../../data/investigatorQueries';
@@ -68,6 +69,7 @@ export function InvestigatorPage({
   onCopyCallLink,
   onNavigateView,
 }: InvestigatorPageProps) {
+  const i18n = useShellI18n();
   const canUseLive = Boolean(contextRuntime.apiToken) && !contextRuntime.fileMode;
   const fallbackSnapshots = useMemo(() => fallbackDiagnosticSnapshots(model), [model]);
   const evidence = useInvestigatorEvidence({
@@ -211,11 +213,11 @@ export function InvestigatorPage({
       <section className={answerStyles.answerBand} data-tone={selected.tone} aria-labelledby="investigation-answer-title">
         <div className={answerStyles.answerCopy}>
           <span>Selected finding</span>
-          <h2 id="investigation-answer-title">{selected.title}</h2>
-          <p>{selected.summary}</p>
+          <h2 id="investigation-answer-title">{i18n.translateText(selected.title)}</h2>
+          <p>{i18n.translateText(selected.summary)}</p>
         </div>
         <div className={answerStyles.answerMetrics}>
-          <MetricReadout label="Confidence" value={selected.confidence} detail={selected.source} />
+          <MetricReadout label="Confidence" value={i18n.translateText(selected.confidence)} detail={i18n.translateText(selected.source)} />
           <MetricReadout label="Evidence" value={selected.evidenceCount.toLocaleString()} detail="Linked rows" />
           <MetricReadout label="Impact signal" value={formatCompact(selected.impactScore)} detail="Ranking score" />
         </div>
@@ -225,7 +227,7 @@ export function InvestigatorPage({
         <Surface className={styles.findingsPanel}>
           <div className={styles.panelHeader}>
             <div><h2>Ranked findings</h2><p>Confidence, scope, and evidence stay visible while comparing.</p></div>
-            <StatusBadge tone="context">{workspace.findings.length} signals</StatusBadge>
+            <StatusBadge tone="context">{i18n.translateText(`${workspace.findings.length} signals`)}</StatusBadge>
           </div>
           <div className={styles.findingList}>
             {workspace.findings.map(finding => (
@@ -237,7 +239,7 @@ export function InvestigatorPage({
                 onClick={() => selectFinding(finding)}
               >
                 <i className={styles.findingSignal} data-tone={finding.tone} aria-hidden="true" />
-                <span className={styles.findingCopy}><strong>{finding.title}</strong><span>{finding.category}</span></span>
+                <span className={styles.findingCopy}><strong>{i18n.translateText(finding.title)}</strong><span>{i18n.translateText(finding.category)}</span></span>
                 <span className={styles.findingEvidence}>{finding.evidenceCount} rows</span>
                 <ArrowRight aria-hidden="true" />
               </button>
@@ -250,11 +252,11 @@ export function InvestigatorPage({
             <div><h2>Recommended change</h2><p>Deterministic action from the selected evidence family.</p></div>
             <StatusBadge tone={toneToBadge(selected.tone)}>{selected.confidence}</StatusBadge>
           </div>
-          <p className={styles.recommendation}>{selected.action}</p>
+          <p className={styles.recommendation}>{i18n.translateText(selected.action)}</p>
           <dl className={styles.methodList}>
             <div><dt>Verify with</dt><dd>{selected.verification.join(', ') || 'linked evidence rows'}</dd></div>
-            <div><dt>Missing access</dt><dd>{selected.missingAccess}</dd></div>
-            <div><dt>Privacy</dt><dd>{selected.privacyNote}</dd></div>
+            <div><dt>Missing access</dt><dd>{i18n.translateText(selected.missingAccess)}</dd></div>
+            <div><dt>Privacy</dt><dd>{i18n.translateText(selected.privacyNote)}</dd></div>
           </dl>
           <Button variant="primary" onClick={() => selected.evidence[0]?.recordId && onOpenInvestigator(selected.evidence[0].recordId)} disabled={!selected.evidence.some(row => row.recordId)}>
             <Search />Verify in call
@@ -277,10 +279,10 @@ export function InvestigatorPage({
       <section className={styles.ledgerSection}>
         <div className={styles.panelHeader}>
           <div><h2>Evidence ledger</h2><p>Each supported row opens the underlying call or thread.</p></div>
-          <StatusBadge tone="positive">{selected.evidence.length} linked</StatusBadge>
+          <StatusBadge tone="positive">{i18n.translateText(`${selected.evidence.length} linked`)}</StatusBadge>
         </div>
         <InvestigationEvidenceLedger
-          findingTitle={selected.title}
+          findingTitle={i18n.translateText(selected.title)}
           rows={selected.evidence}
           onOpenCall={onOpenInvestigator}
           onCopyCallLink={onCopyCallLink}
diff --git a/frontend/dashboard/src/features/limits/LimitsPage.tsx b/frontend/dashboard/src/features/limits/LimitsPage.tsx
index 283ddb4b..097a72e5 100644
--- a/frontend/dashboard/src/features/limits/LimitsPage.tsx
+++ b/frontend/dashboard/src/features/limits/LimitsPage.tsx
@@ -9,6 +9,7 @@ import {
   type AllowanceWindowKind,
 } from '../../api/allowance';
 import type { ContextRuntime, DashboardModel } from '../../api/types';
+import { useShellI18n } from '../../app/i18nContext';
 import { Button, MetricReadout, PageLoadProgress, SegmentedControl, StatusBadge, Surface } from '../../design';
 import { Visualization } from '../../visualization';
 import { csvDateStamp } from '../shared/exportCsv';
@@ -43,6 +44,7 @@ export function LimitsPage({
   onOpenInvestigator,
   onCopyCallLink,
 }: LimitsPageProps) {
+  const i18n = useShellI18n();
   const initialState = readLimitState();
   const [windowKind, setWindowKind] = useState<AllowanceWindowKind>(initialState.windowKind);
   const [hypothesis, setHypothesis] = useState<AllowanceHypothesis>(initialState.hypothesis);
@@ -165,7 +167,7 @@ export function LimitsPage({
         </div>
         <div className={styles.answerMeta}>
           <StatusBadge tone={workspace.answer.tone}>{workspace.answer.badge}</StatusBadge>
-          <span>{workspace.weekly.positiveSpanCount} weekly spans · {workspace.readiness.detector_version}</span>
+          <span>{i18n.translateText(`${workspace.weekly.positiveSpanCount} weekly spans · ${workspace.readiness.detector_version}`)}</span>
         </div>
       </section>
 
diff --git a/frontend/dashboard/src/features/overview/OverviewRecentCalls.tsx b/frontend/dashboard/src/features/overview/OverviewRecentCalls.tsx
index b0aebdb4..8e7269cd 100644
--- a/frontend/dashboard/src/features/overview/OverviewRecentCalls.tsx
+++ b/frontend/dashboard/src/features/overview/OverviewRecentCalls.tsx
@@ -47,7 +47,7 @@ export function OverviewRecentCalls(props: OverviewRecentCallsProps) {
 
   function exportCalls() {
     downloadCsv(`codex-overview-calls-${csvDateStamp()}.csv`, rowsToCsv(visibleCalls, callCsvColumns));
-    setExportStatus(`Exported ${formatNumber(visibleCalls.length)} loaded calls`);
+    setExportStatus(shellI18n.translateText(`Exported ${formatNumber(visibleCalls.length)} loaded calls`));
   }
 
   return (
@@ -55,7 +55,7 @@ export function OverviewRecentCalls(props: OverviewRecentCallsProps) {
       <div className={styles.header}>
         <div>
           <h2 id="overview-recent-calls-title">Calls</h2>
-          <p>{formatNumber(visibleCalls.length)} matching calls with the same evidence fields as the Calls workspace.</p>
+          <p>{shellI18n.translateText(`${formatNumber(visibleCalls.length)} matching calls with the same evidence fields as the Calls workspace.`)}</p>
         </div>
         <div className={styles.actions}>
           {exportStatus ? <StatusBadge tone="positive" role="status">{exportStatus}</StatusBadge> : null}
@@ -73,7 +73,7 @@ export function OverviewRecentCalls(props: OverviewRecentCallsProps) {
           getRowId={call => call.id}
           mobile={{
             primary: call => call.thread,
-            secondary: call => `${call.time} · ${call.model} · ${formatCompact(call.totalTokens)} tokens · ${pct(call.cachedPct)} cache`,
+            secondary: call => shellI18n.translateText(`${call.time} · ${call.model} · ${formatCompact(call.totalTokens)} tokens · ${pct(call.cachedPct)} cache`),
             actionLabel: call => callInvestigatorRowLabel(call),
           }}
           sorting={sorting}
@@ -89,7 +89,7 @@ export function OverviewRecentCalls(props: OverviewRecentCallsProps) {
           emptyLabel="No loaded calls match the current search."
         />
         <footer className={styles.footer}>
-          <span>Loaded {formatNumber(props.loadedRowCount)} of {formatNumber(props.totalAvailableRows)} available calls</span>
+          <span>{shellI18n.translateText(`Loaded ${formatNumber(props.loadedRowCount)} of ${formatNumber(props.totalAvailableRows)} available calls`)}</span>
           <div className={styles.actions}>
             <Button aria-label="Load more recent calls" onClick={props.onLoadMoreRows} disabled={!props.canLoadMoreRows || props.refreshing}>{props.refreshing ? 'Loading...' : loadMoreLabel}</Button>
             <Button onClick={props.onBrowseCalls}>Browse all calls</Button>
diff --git a/frontend/dashboard/src/features/reports/ReportsPage.tsx b/frontend/dashboard/src/features/reports/ReportsPage.tsx
index b42db796..a7984de7 100644
--- a/frontend/dashboard/src/features/reports/ReportsPage.tsx
+++ b/frontend/dashboard/src/features/reports/ReportsPage.tsx
@@ -3,6 +3,7 @@ import { Download, RefreshCw } from 'lucide-react';
 import { useMemo, useState } from 'react';
 
 import type { CallRow, DashboardModel } from '../../api/types';
+import { useShellI18n } from '../../app/i18nContext';
 import type { LoadWindow } from '../../data/dataScope';
 import {
   dashboardModuleProgress,
@@ -53,6 +54,7 @@ export function ReportsPage({
   onOpenInvestigator,
   onCopyCallLink,
 }: ReportsPageProps) {
+  const i18n = useShellI18n();
   const [selectedKey, setSelectedKey] = useState(() => reportKey(reportFromUrl(model.reports) ?? model.reports[0]));
   const [actionStatus, setActionStatus] = useState('');
   const canUseLive = Boolean(model.contextRuntime.apiToken) && !model.contextRuntime.fileMode;
@@ -201,7 +203,7 @@ export function ReportsPage({
           <Visualization spec={visualizationSpec} height={320} />
           <Panel
             title="Report Evidence Calls"
-            subtitle={`${evidenceCalls.length} aggregate rows · select a row to open Call Investigator`}
+            subtitle={i18n.translateText(`${evidenceCalls.length} aggregate rows · select a row to open Call Investigator`)}
             action={<StatusBadge label="Investigator linked" tone="green" />}
           >
             <ReportEvidenceTable
diff --git a/frontend/dashboard/src/features/shared/tables.tsx b/frontend/dashboard/src/features/shared/tables.tsx
index f8dfca7f..0508aeed 100644
--- a/frontend/dashboard/src/features/shared/tables.tsx
+++ b/frontend/dashboard/src/features/shared/tables.tsx
@@ -163,22 +163,25 @@ export function callSignalPucks(call: CallRow, maxVisible = 3): { visible: CallS
 }
 
 export function CallSignalPucks({ call }: { call: CallRow }) {
+  const i18n = useShellI18n();
   const { visible, hidden } = callSignalPucks(call);
   if (!visible.length) {
     return <span className="muted">None</span>;
   }
 
-  const hiddenLabel = hidden.map(puck => puck.label).join(', ');
+  const localizedPucks = visible.map(puck => ({ ...puck, label: i18n.translateText(puck.label), shortLabel: i18n.translateText(puck.shortLabel) }));
+  const localizedHidden = hidden.map(puck => ({ ...puck, label: i18n.translateText(puck.label), shortLabel: i18n.translateText(puck.shortLabel) }));
+  const hiddenLabel = localizedHidden.map(puck => puck.label).join('、');
   return (
-    <span className="flags compact-flags" aria-label={`Signals: ${[...visible, ...hidden].map(puck => puck.label).join(', ')}`}>
-      {visible.map(puck => (
+    <span className="flags compact-flags" aria-label={i18n.language === 'zh-Hans' ? `信号：${[...localizedPucks, ...localizedHidden].map(puck => puck.label).join('、')}` : `Signals: ${[...visible, ...hidden].map(puck => puck.label).join(', ')}`}>
+      {localizedPucks.map(puck => (
         <span key={puck.key} className="flag signal-puck" title={puck.label}>
           {puck.shortLabel}
         </span>
       ))}
-      {hidden.length ? (
+      {localizedHidden.length ? (
         <span className="flag signal-puck more" title={hiddenLabel}>
-          +{hidden.length}
+          +{localizedHidden.length}
         </span>
       ) : null}
     </span>
@@ -261,6 +264,7 @@ export function callActionColumn({
   return {
     id: 'investigate',
     header: 'Investigate',
+    size: 260,
     enableSorting: false,
     cell: info => (
       <CallActionCell
@@ -426,6 +430,7 @@ export function threadActionColumn({ onOpenInvestigator, onCopyCallLink }: Threa
   return {
     id: 'investigate',
     header: 'Investigate',
+    size: 260,
     enableSorting: false,
     cell: info => {
       const thread = info.row.original;
diff --git a/frontend/dashboard/src/features/threads/ThreadInspector.tsx b/frontend/dashboard/src/features/threads/ThreadInspector.tsx
index 0d5219a6..485d540b 100644
--- a/frontend/dashboard/src/features/threads/ThreadInspector.tsx
+++ b/frontend/dashboard/src/features/threads/ThreadInspector.tsx
@@ -164,7 +164,7 @@ export function ThreadInspector({
           <span><strong>{selected.averageGap}</strong>Average gap</span>
           <span><strong>{selected.initiatorSummary}</strong>Initiated by</span>
           <span><strong>{selected.modelSummary}</strong>Models</span>
-          <span><strong>{selected.effortSummary}</strong>Effort mix</span>
+          <span><strong>{shellI18n.translateText(selected.effortSummary)}</strong>Effort mix</span>
           <span>
             <strong>{formatCompact(selected.cachedInput)} / {formatCompact(selected.uncachedInput)}</strong>
             Cached / uncached input
@@ -226,7 +226,7 @@ export function ThreadInspector({
             <span>
               <strong>
                 {lifecycle.firstExpensive
-                  ? `${lifecycle.firstExpensive.call.time} · Call ${lifecycle.firstExpensive.index + 1}`
+                  ? shellI18n.translateText(`${lifecycle.firstExpensive.call.time} · Call ${lifecycle.firstExpensive.index + 1}`)
                   : 'None'}
               </strong>
               First expensive turn
@@ -234,7 +234,7 @@ export function ThreadInspector({
             <span>
               <strong>
                 {lifecycle.largestJump
-                  ? `${formatCompact(lifecycle.largestJump.tokens)} at ${lifecycle.largestJump.call.time}`
+                  ? shellI18n.translateText(`${formatCompact(lifecycle.largestJump.tokens)} at ${lifecycle.largestJump.call.time}`)
                   : 'None'}
               </strong>
               Largest token jump
@@ -267,12 +267,12 @@ export function ThreadInspector({
             <span>{efficiencySignalCount ? `${efficiencySignalCount} signals` : 'Aggregate summary'}</span>
           </div>
           <div className="secondary-thread-grid">
-            <span><strong>{selected.latestActivity}</strong>Latest activity</span>
+            <span><strong>{shellI18n.translateText(selected.latestActivity)}</strong>Latest activity</span>
             <span><strong>{formatCompact(selected.totalTokens)}</strong>Total tokens</span>
             <span><strong>{calls.length}</strong>Loaded calls</span>
             <span><strong>{efficiencySignalCount}</strong>Efficiency signals</span>
             <span><strong>{selected.modelSummary}</strong>Model mix</span>
-            <span><strong>{selected.effortSummary}</strong>Effort mix</span>
+            <span><strong>{shellI18n.translateText(selected.effortSummary)}</strong>Effort mix</span>
           </div>
         </div>
       </Panel>
@@ -337,6 +337,7 @@ function ThreadCallRow({
   onOpenInvestigator(recordId: string): void;
   onCopyCallLink(recordId: string): void;
 }) {
+  const i18n = useShellI18n();
   const openLabel = `Open investigator for thread call ${call.thread} ${call.model}`;
   const copyLabel = `Copy link for thread call ${call.thread} ${call.model}`;
   return (
@@ -352,21 +353,21 @@ function ThreadCallRow({
         }
       }}
     >
-      <span>{call.time}</span>
-      <strong>{call.model} / {call.effort}</strong>
-      <em>{formatCompact(call.totalTokens)} tokens - {pct(call.cachedPct)} cache - {money(call.cost)}</em>
+      <span>{i18n.translateText(call.time)}</span>
+      <strong>{call.model} / {i18n.translateText(call.effort)}</strong>
+      <em>{i18n.translateText(`${formatCompact(call.totalTokens)} tokens - ${pct(call.cachedPct)} cache - ${money(call.cost)}`)}</em>
       <div className="thread-call-flags">
         <CallSignalPucks call={call} />
-        <span>Context {formatCallContextUse(call)}</span>
-        <span>{callPricingStatusText(call)}</span>
+        <span>{i18n.translateText(`Context ${formatCallContextUse(call)}`)}</span>
+        <span>{i18n.translateText(callPricingStatusText(call))}</span>
       </div>
       <div className="thread-call-meta">
         <span>{call.duration}</span>
-        <span>Prev {call.previousCallGap}</span>
-        <span>{call.initiator || 'unknown'} initiated</span>
-        <span>{formatCredits(call.credits)}</span>
+        <span>{i18n.translateText(`Prev ${call.previousCallGap}`)}</span>
+        <span>{i18n.translateText(`${call.initiator || 'unknown'} initiated`)}</span>
+        <span>{i18n.translateText(formatCredits(call.credits))}</span>
       </div>
-      {call.recommendation ? <p className="thread-call-recommendation">{call.recommendation}</p> : null}
+      {call.recommendation ? <p className="thread-call-recommendation">{i18n.translateText(call.recommendation)}</p> : null}
       <div className="thread-context-bar" role="img" aria-label={`Context use ${formatCallContextUse(call)}`}>
         <span
           className={timelineSeverityClass(call.contextWindowPct)}
diff --git a/frontend/dashboard/src/features/threads/ThreadsExplorerView.tsx b/frontend/dashboard/src/features/threads/ThreadsExplorerView.tsx
index 2fa335e9..d1dc5028 100644
--- a/frontend/dashboard/src/features/threads/ThreadsExplorerView.tsx
+++ b/frontend/dashboard/src/features/threads/ThreadsExplorerView.tsx
@@ -2,6 +2,7 @@ import type { ColumnDef, OnChangeFn, SortingState } from '@tanstack/react-table'
 import { Download, RotateCcw, Search } from 'lucide-react';
 import type { Dispatch, ReactNode, SetStateAction } from 'react';
 import type { CallRow, ThreadRow } from '../../api/types';
+import { useShellI18n } from '../../app/i18nContext';
 import { StatusBadge } from '../../components/StatusBadge';
 import { PageLoadProgress, SegmentedControl } from '../../design';
 import { Visualization, type VisualizationSpecV1 } from '../../visualization';
@@ -112,6 +113,7 @@ export function ThreadsExplorerView({
   onOpenInvestigator,
   onCopyCallLink,
 }: ThreadsExplorerViewProps) {
+  const i18n = useShellI18n();
   return (
     <div className={`${styles.page} page-grid`}>
       <header className={styles.pageHeader}>
@@ -174,9 +176,9 @@ export function ThreadsExplorerView({
             value={viewMode}
             onValueChange={onViewModeChange}
             options={[
-              { value: 'table', label: 'Table' },
+              { value: 'table', label: i18n.translateText('Table') },
               { value: 'frontier', label: 'Cache frontier' },
-              { value: 'lifecycle', label: 'Lifecycle' },
+              { value: 'lifecycle', label: i18n.translateText('Lifecycle') },
             ]}
           />
           <StatusBadge
@@ -208,7 +210,7 @@ export function ThreadsExplorerView({
                 getRowId={thread => thread.name}
                 mobile={{
                   primary: thread => thread.name,
-                  secondary: thread => `${thread.turns} calls · ${formatCompact(thread.totalTokens)} tokens · ${pct(thread.cachePct)} cache`,
+                  secondary: thread => i18n.translateText(`${thread.turns} calls · ${formatCompact(thread.totalTokens)} tokens · ${pct(thread.cachePct)} cache`),
                   actionLabel: thread => threadInvestigatorRowLabel(thread),
                 }}
                 sorting={sorting}
@@ -226,7 +228,7 @@ export function ThreadsExplorerView({
               />
               <div className={styles.gridFooter} aria-live="polite">
                 <span>
-                  {displayedThreads.length.toLocaleString()} loaded / {totalMatchedThreads.toLocaleString()} matched
+                  {i18n.translateText(`${displayedThreads.length.toLocaleString()} loaded / ${totalMatchedThreads.toLocaleString()} matched`)}
                 </span>
                 {canLoadMoreThreads ? (
                   <button
diff --git a/frontend/dashboard/src/visualization/react/Visualization.tsx b/frontend/dashboard/src/visualization/react/Visualization.tsx
index c4805fc0..16d2de12 100644
--- a/frontend/dashboard/src/visualization/react/Visualization.tsx
+++ b/frontend/dashboard/src/visualization/react/Visualization.tsx
@@ -1,6 +1,7 @@
 import { BarChart3, Download, Table2 } from 'lucide-react';
 import { useEffect, useMemo, useRef, useState, type KeyboardEvent } from 'react';
 
+import { useShellI18n } from '../../app/i18nContext';
 import {
   tableRowsForVisualization,
   validateVisualizationSpec,
@@ -11,6 +12,7 @@ import type { EChartsVisualizationRenderer } from '../renderer/echartsRenderer';
 import { VisualizationState, shouldRenderVisualizationData } from './VisualizationState';
 import { selectedVisualizationLabel, VisualizationTable } from './VisualizationTable';
 import styles from './Visualization.module.css';
+import { localizeVisualizationSpec } from './localizeVisualizationSpec';
 
 export type VisualizationView = 'chart' | 'table';
 
@@ -22,15 +24,21 @@ type VisualizationProps = {
 };
 
 export function Visualization({ defaultView = 'chart', height = 360, onSelectionChange, spec }: VisualizationProps) {
+  const i18n = useShellI18n();
+  const localizedSpec = useMemo(
+    () => localizeVisualizationSpec(spec, i18n.translateText),
+    [i18n.translateText, spec],
+  );
   const chartElementRef = useRef<HTMLDivElement>(null);
   const rendererRef = useRef<EChartsVisualizationRenderer | null>(null);
   const [view, setView] = useState<VisualizationView>(defaultView);
   const [rendererState, setRendererState] = useState<'idle' | 'loading' | 'ready' | 'error'>('idle');
   const [selectedKey, setSelectedKey] = useState<string | null>(null);
-  const issues = useMemo(() => validateVisualizationSpec(spec), [spec]);
-  const rows = useMemo(() => tableRowsForVisualization(spec), [spec]);
-  const canRenderData = issues.length === 0 && shouldRenderVisualizationData(spec) && rows.length > 0;
-  const selectedLabel = selectedVisualizationLabel(spec, selectedKey);
+  const issues = useMemo(() => validateVisualizationSpec(localizedSpec), [localizedSpec]);
+  const rows = useMemo(() => tableRowsForVisualization(localizedSpec), [localizedSpec]);
+  const canRenderData = issues.length === 0 && shouldRenderVisualizationData(localizedSpec) && rows.length > 0;
+  const selectedLabel = selectedVisualizationLabel(localizedSpec, selectedKey);
+  const ariaDescription = visualizationAriaDescription(localizedSpec, i18n.translateText);
 
   useEffect(() => {
     setSelectedKey(current => (current && rows.some(row => row.key === current) ? current : rows[0]?.key ?? null));
@@ -57,7 +65,7 @@ export function Visualization({ defaultView = 'chart', height = 360, onSelection
         if (cancelled) return;
         return createEChartsVisualizationRenderer(
           element,
-          spec,
+          localizedSpec,
           selectKey,
           { animate: !prefersReducedMotion(), signal: abortController.signal },
         );
@@ -85,7 +93,7 @@ export function Visualization({ defaultView = 'chart', height = 360, onSelection
       rendererRef.current?.dispose();
       rendererRef.current = null;
     };
-  }, [canRenderData, spec, view]);
+  }, [canRenderData, localizedSpec, view]);
 
   function selectKey(key: string) {
     setSelectedKey(key);
@@ -107,39 +115,39 @@ export function Visualization({ defaultView = 'chart', height = 360, onSelection
     if (!dataUrl) return;
     const anchor = document.createElement('a');
     anchor.href = dataUrl;
-    anchor.download = `codex-${spec.id}.svg`;
+    anchor.download = `codex-${localizedSpec.id}.svg`;
     anchor.click();
   }
 
-  const titleId = `${spec.id}-title`;
-  const descriptionId = `${spec.id}-description`;
+  const titleId = `${localizedSpec.id}-title`;
+  const descriptionId = `${localizedSpec.id}-description`;
 
   return (
     <section
       className={styles.root}
       aria-labelledby={titleId}
-      data-visualization-id={spec.id}
-      data-visualization-state={spec.state.kind}
+      data-visualization-id={localizedSpec.id}
+      data-visualization-state={localizedSpec.state.kind}
     >
       <header className={styles.header}>
         <div>
-          <h3 id={titleId}>{spec.title}</h3>
-          {spec.description ? <p>{spec.description}</p> : null}
+          <h3 id={titleId}>{localizedSpec.title}</h3>
+          {localizedSpec.description ? <p>{localizedSpec.description}</p> : null}
         </div>
         <div className={styles.toolbar}>
-          <div className={styles.segmented} role="group" aria-label="Visualization view">
-            <button type="button" aria-label="Chart view" title="Chart view" aria-pressed={view === 'chart'} onClick={() => setView('chart')}>
+          <div className={styles.segmented} role="group" aria-label={i18n.translateText('Visualization view')}>
+            <button type="button" aria-label={i18n.translateText('Chart view')} title={i18n.translateText('Chart view')} aria-pressed={view === 'chart'} onClick={() => setView('chart')}>
               <BarChart3 size={16} />
             </button>
-            <button type="button" aria-label="Table view" title="Table view" aria-pressed={view === 'table'} onClick={() => setView('table')}>
+            <button type="button" aria-label={i18n.translateText('Table view')} title={i18n.translateText('Table view')} aria-pressed={view === 'table'} onClick={() => setView('table')}>
               <Table2 size={16} />
             </button>
           </div>
           <button
             className={styles.iconButton}
             type="button"
-            aria-label="Export visualization as SVG"
-            title="Export SVG"
+            aria-label={i18n.translateText('Export visualization as SVG')}
+            title={i18n.translateText('Export SVG')}
             disabled={view !== 'chart' || rendererState !== 'ready'}
             onClick={exportSvg}
           >
@@ -149,20 +157,20 @@ export function Visualization({ defaultView = 'chart', height = 360, onSelection
       </header>
 
       <div className={styles.meta}>
-        <span>{spec.scope.label}</span>
-        <span>{spec.scope.rowCount.toLocaleString()} evidence rows</span>
-        <span>Updated {formatFreshness(spec.freshness.generatedAt)}</span>
+        <span>{localizedSpec.scope.label}</span>
+        <span>{i18n.translateText(`${localizedSpec.scope.rowCount.toLocaleString()} evidence rows`)}</span>
+        <span>{i18n.translateText(`Updated ${formatFreshness(localizedSpec.freshness.generatedAt)}`)}</span>
       </div>
 
       {issues.length ? (
         <div className={styles.state} data-state="error" role="alert">
-          <strong>Visualization contract error</strong>
-          <span>{issues[0].path}: {issues[0].message}</span>
+          <strong>{i18n.translateText('Visualization contract error')}</strong>
+          <span>{i18n.translateText(issues[0].path)}：{i18n.translateText(issues[0].message)}</span>
         </div>
       ) : null}
 
-      {!issues.length && !shouldRenderVisualizationData(spec) ? <VisualizationState spec={spec} /> : null}
-      {!issues.length && (spec.state.kind === 'partial' || spec.state.kind === 'stale') ? <VisualizationState spec={spec} /> : null}
+      {!issues.length && !shouldRenderVisualizationData(localizedSpec) ? <VisualizationState spec={localizedSpec} /> : null}
+      {!issues.length && (localizedSpec.state.kind === 'partial' || localizedSpec.state.kind === 'stale') ? <VisualizationState spec={localizedSpec} /> : null}
 
       {canRenderData && view === 'chart' ? (
         <div
@@ -171,7 +179,7 @@ export function Visualization({ defaultView = 'chart', height = 360, onSelection
           role="region"
           tabIndex={0}
           aria-describedby={descriptionId}
-          aria-label={`${spec.title} chart`}
+          aria-label={i18n.translateText(`${localizedSpec.title} chart`)}
           aria-keyshortcuts="ArrowLeft ArrowRight ArrowUp ArrowDown Home End"
           onKeyDown={handleChartKeyDown}
         >
@@ -182,20 +190,20 @@ export function Visualization({ defaultView = 'chart', height = 360, onSelection
             data-testid="visualization-chart"
             aria-hidden="true"
           />
-          {rendererState === 'loading' ? <div className={styles.chartStatus}>Loading renderer...</div> : null}
-          {rendererState === 'error' ? <div className={styles.chartStatus}>Chart unavailable. Use the synchronized table view.</div> : null}
+          {rendererState === 'loading' ? <div className={styles.chartStatus}>{i18n.translateText('Loading renderer...')}</div> : null}
+          {rendererState === 'error' ? <div className={styles.chartStatus}>{i18n.translateText('Chart unavailable. Use the synchronized table view.')}</div> : null}
         </div>
       ) : null}
 
       {canRenderData && view === 'table' ? (
-        <VisualizationTable spec={spec} selectedKey={selectedKey} onSelectionChange={selectKey} />
+        <VisualizationTable spec={localizedSpec} selectedKey={selectedKey} onSelectionChange={selectKey} />
       ) : null}
 
       <footer className={styles.summary} id={descriptionId}>
-        <strong>{spec.accessibility.summary}</strong>
-        {selectedLabel ? <span aria-live="polite">Selected {selectedLabel}</span> : null}
-        <span className={styles.screenReaderOnly}>{visualizationAriaDescription(spec)}</span>
-        {spec.caveats?.length ? <span>{spec.caveats[0]}</span> : null}
+        <strong>{localizedSpec.accessibility.summary}</strong>
+        {selectedLabel ? <span aria-live="polite">{i18n.translateText('Selected')} {selectedLabel}</span> : null}
+        <span className={styles.screenReaderOnly}>{ariaDescription}</span>
+        {localizedSpec.caveats?.length ? <span>{localizedSpec.caveats[0]}</span> : null}
       </footer>
     </section>
   );
diff --git a/frontend/dashboard/src/visualization/react/VisualizationState.tsx b/frontend/dashboard/src/visualization/react/VisualizationState.tsx
index 69ec5ef0..400af1e8 100644
--- a/frontend/dashboard/src/visualization/react/VisualizationState.tsx
+++ b/frontend/dashboard/src/visualization/react/VisualizationState.tsx
@@ -1,18 +1,20 @@
 import { AlertTriangle, Clock3, Database, LoaderCircle } from 'lucide-react';
 
+import { useShellI18n } from '../../app/i18nContext';
 import { stateDescription } from '../spec';
 import type { VisualizationSpecV1 } from '../spec';
 import styles from './Visualization.module.css';
 
 export function VisualizationState({ spec }: { spec: VisualizationSpecV1 }) {
+  const i18n = useShellI18n();
   const state = spec.state;
   const Icon = state.kind === 'loading' ? LoaderCircle : state.kind === 'stale' ? Clock3 : state.kind === 'error' ? AlertTriangle : Database;
   return (
     <div className={styles.state} data-state={state.kind} role={state.kind === 'error' ? 'alert' : 'status'}>
       <Icon aria-hidden="true" className={state.kind === 'loading' ? styles.spinning : undefined} size={20} />
       <div>
-        <strong>{stateTitle(state.kind)}</strong>
-        <span>{stateDescription(spec)}</span>
+        <strong>{i18n.translateText(stateTitle(state.kind))}</strong>
+        <span>{i18n.translateText(stateDescription(spec))}</span>
       </div>
     </div>
   );
diff --git a/frontend/dashboard/src/visualization/react/VisualizationTable.tsx b/frontend/dashboard/src/visualization/react/VisualizationTable.tsx
index 0909282b..fa6ca567 100644
--- a/frontend/dashboard/src/visualization/react/VisualizationTable.tsx
+++ b/frontend/dashboard/src/visualization/react/VisualizationTable.tsx
@@ -1,5 +1,6 @@
 import { useCallback, useEffect, useRef, useState, type KeyboardEvent } from 'react';
 
+import { useShellI18n } from '../../app/i18nContext';
 import { formatVisualizationValue, tableRowsForVisualization } from '../spec';
 import type { VisualizationSpecV1, VisualizationTableColumn } from '../spec';
 import styles from './VisualizationTable.module.css';
@@ -11,6 +12,7 @@ type VisualizationTableProps = {
 };
 
 export function VisualizationTable({ onSelectionChange, selectedKey, spec }: VisualizationTableProps) {
+  const i18n = useShellI18n();
   const rows = tableRowsForVisualization(spec);
   const scrollRef = useRef<HTMLDivElement>(null);
   const [hasMoreRight, setHasMoreRight] = useState(false);
@@ -50,7 +52,7 @@ export function VisualizationTable({ onSelectionChange, selectedKey, spec }: Vis
         ref={scrollRef}
         className={styles.tableScroll}
         role="region"
-        aria-label={`${spec.title} table`}
+        aria-label={i18n.translateText(`${spec.title} table`)}
         tabIndex={0}
         onScroll={updateOverflowCue}
       >
diff --git a/frontend/dashboard/src/visualization/react/localizeVisualizationSpec.test.ts b/frontend/dashboard/src/visualization/react/localizeVisualizationSpec.test.ts
new file mode 100644
index 00000000..22d3d0d4
--- /dev/null
+++ b/frontend/dashboard/src/visualization/react/localizeVisualizationSpec.test.ts
@@ -0,0 +1,78 @@
+import { describe, expect, it } from 'vitest';
+
+import type { CartesianVisualizationSpecV1 } from '../spec';
+import { localizeVisualizationSpec } from './localizeVisualizationSpec';
+
+const fixture: CartesianVisualizationSpecV1 = {
+  schema: 'codex-usage-visualization/v1',
+  id: 'localization-fixture',
+  kind: 'cartesian',
+  title: 'Recent token movement',
+  description: 'Daily input',
+  state: { kind: 'empty', message: 'No matching evidence' },
+  scope: { label: 'All time', rowCount: 0 },
+  freshness: { generatedAt: '2026-07-15T00:00:00Z' },
+  caveats: ['Local data only'],
+  accessibility: { summary: 'No data' },
+  table: {
+    caption: 'Token table',
+    columns: [{ field: 'value', label: 'Total Tokens', type: 'number', unit: 'tokens' }],
+  },
+  data: { rows: [] },
+  axes: {
+    x: { field: 'date', label: 'Date', type: 'time' },
+    y: { field: 'value', label: 'Total Tokens', type: 'number', unit: 'tokens' },
+  },
+  series: [{ id: 'total', label: 'Total Tokens', mark: 'line', xField: 'date', yField: 'value' }],
+};
+
+describe('localizeVisualizationSpec', () => {
+  it('localizes chart, table, state, and accessibility labels while preserving data contracts', () => {
+    const translations: Record<string, string> = {
+      'Recent token movement': '近期token变化',
+      'Daily input': '每日输入',
+      'No matching evidence': '没有匹配的证据',
+      'All time': '全部时间',
+      'Local data only': '仅使用本地数据',
+      'No data': '暂无数据',
+      'Token table': 'token表',
+      'Total Tokens': 'token总数',
+      Date: '日期',
+    };
+    const localized = localizeVisualizationSpec(fixture, value => translations[value] ?? value);
+
+    expect(localized.title).toBe('近期token变化');
+    expect(localized.state).toEqual({ kind: 'empty', message: '没有匹配的证据' });
+    expect(localized.table.columns[0].label).toBe('token总数');
+    expect(localized.kind).toBe('cartesian');
+    if (localized.kind === 'cartesian') {
+      expect(localized.axes.x.label).toBe('日期');
+      expect(localized.series[0].label).toBe('token总数');
+      expect(localized.data).toBe(fixture.data);
+    }
+  });
+
+  it('localizes known categorical UI values while preserving user identity fields', () => {
+    const categorical: CartesianVisualizationSpecV1 = {
+      ...fixture,
+      data: { rows: [{ id: 'one', finding: 'Tool output pressure', thread: 'Overview' }] },
+      table: {
+        ...fixture.table,
+        columns: [
+          { field: 'finding', label: 'Finding', type: 'category' },
+          { field: 'thread', label: 'Thread', type: 'text' },
+        ],
+      },
+    };
+    const localized = localizeVisualizationSpec(categorical, value => ({
+      'Tool output pressure': '工具输出压力',
+      Overview: '概览',
+    })[value] ?? value);
+
+    expect(localized.kind).toBe('cartesian');
+    if (localized.kind === 'cartesian') {
+      expect(localized.data.rows[0].finding).toBe('工具输出压力');
+      expect(localized.data.rows[0].thread).toBe('Overview');
+    }
+  });
+});
diff --git a/frontend/dashboard/src/visualization/react/localizeVisualizationSpec.ts b/frontend/dashboard/src/visualization/react/localizeVisualizationSpec.ts
new file mode 100644
index 00000000..ab6eee79
--- /dev/null
+++ b/frontend/dashboard/src/visualization/react/localizeVisualizationSpec.ts
@@ -0,0 +1,153 @@
+import type {
+  CartesianVisualizationSpecV1,
+  FlowVisualizationSpecV1,
+  HeatmapVisualizationSpecV1,
+  VisualizationAccessibility,
+  VisualizationAnnotation,
+  VisualizationDataState,
+  VisualizationRecord,
+  VisualizationSpecV1,
+  VisualizationTableSpec,
+} from '../spec';
+import { visualizationAriaDescription } from '../spec';
+
+type Translate = (value: string) => string;
+
+export function localizeVisualizationSpec(
+  spec: VisualizationSpecV1,
+  translate: Translate,
+): VisualizationSpecV1 {
+  const base = {
+    title: translate(spec.title),
+    description: spec.description ? translate(spec.description) : undefined,
+    state: localizeState(spec.state, translate),
+    scope: {
+      ...spec.scope,
+      label: translate(spec.scope.label),
+      filters: spec.scope.filters?.map(translate),
+    },
+    caveats: spec.caveats?.map(translate),
+    accessibility: {
+      ...localizeAccessibility(spec.accessibility, translate),
+      description: visualizationAriaDescription(spec, translate),
+    },
+    table: localizeTable(spec.table, translate),
+    annotations: spec.annotations?.map(annotation => localizeAnnotation(annotation, translate)),
+  };
+
+  if (spec.kind === 'cartesian') {
+    const rows = localizeRows(spec.data.rows, spec.table, translate);
+    return {
+      ...spec,
+      ...base,
+      kind: 'cartesian',
+      data: rows === spec.data.rows ? spec.data : { rows },
+      axes: {
+        x: { ...spec.axes.x, label: translate(spec.axes.x.label) },
+        y: { ...spec.axes.y, label: translate(spec.axes.y.label) },
+      },
+      series: spec.series.map(series => ({ ...series, label: translate(series.label) })),
+    } satisfies CartesianVisualizationSpecV1;
+  }
+  if (spec.kind === 'heatmap') {
+    const rows = localizeRows(spec.data.rows, spec.table, translate);
+    return {
+      ...spec,
+      ...base,
+      kind: 'heatmap',
+      data: rows === spec.data.rows ? spec.data : { rows },
+      encoding: {
+        ...spec.encoding,
+        x: { ...spec.encoding.x, label: translate(spec.encoding.x.label) },
+        y: { ...spec.encoding.y, label: translate(spec.encoding.y.label) },
+        value: { ...spec.encoding.value, label: translate(spec.encoding.value.label) },
+      },
+    } satisfies HeatmapVisualizationSpecV1;
+  }
+  return {
+    ...spec,
+    ...base,
+    kind: 'flow',
+    data: {
+      ...spec.data,
+      nodes: spec.data.nodes.map(node => ({ ...node, label: translate(node.label) })),
+    },
+    encoding: {
+      ...spec.encoding,
+      sourceLabel: translate(spec.encoding.sourceLabel),
+      targetLabel: translate(spec.encoding.targetLabel),
+      valueLabel: translate(spec.encoding.valueLabel),
+    },
+  } satisfies FlowVisualizationSpecV1;
+}
+
+function localizeState(state: VisualizationDataState, translate: Translate): VisualizationDataState {
+  if (state.kind === 'ready') return state;
+  if (state.kind === 'loading') {
+    return { ...state, message: state.message ? translate(state.message) : undefined };
+  }
+  return { ...state, message: translate(state.message) };
+}
+
+function localizeAccessibility(
+  accessibility: VisualizationAccessibility,
+  translate: Translate,
+): VisualizationAccessibility {
+  return {
+    ...accessibility,
+    summary: translate(accessibility.summary),
+    details: accessibility.details?.map(translate),
+    keyboardInstructions: accessibility.keyboardInstructions
+      ? translate(accessibility.keyboardInstructions)
+      : undefined,
+  };
+}
+
+function localizeTable(table: VisualizationTableSpec, translate: Translate): VisualizationTableSpec {
+  return {
+    ...table,
+    caption: translate(table.caption),
+    columns: table.columns.map(column => ({ ...column, label: translate(column.label) })),
+  };
+}
+
+function localizeAnnotation(
+  annotation: VisualizationAnnotation,
+  translate: Translate,
+): VisualizationAnnotation {
+  return { ...annotation, label: translate(annotation.label) };
+}
+
+const protectedDataFields = new Set([
+  'branch', 'command', 'cwd', 'date', 'file', 'id', 'key', 'model', 'name', 'observed',
+  'path', 'project', 'record_id', 'remote', 'session', 'source', 'thread', 'time', 'timestamp', 'window',
+]);
+
+function localizeRows(
+  rows: VisualizationRecord[],
+  table: VisualizationTableSpec,
+  translate: Translate,
+): VisualizationRecord[] {
+  if (!rows.length) return rows;
+  const localizableFields = new Set(
+    table.columns
+      .filter(column => (column.type === 'category' || column.type === 'text') && !protectedDataFields.has(column.field))
+      .map(column => column.field),
+  );
+  if (!localizableFields.size) return rows;
+  let changed = false;
+  const localized = rows.map(row => {
+    let next: Record<string, string | number | boolean | null> | null = null;
+    for (const field of localizableFields) {
+      const value = row[field];
+      if (typeof value !== 'string') continue;
+      const translated = translate(value);
+      if (translated === value) continue;
+      next ??= { ...row };
+      next[field] = translated;
+      changed = true;
+    }
+    return next ?? row;
+  });
+  return changed ? localized : rows;
+}
diff --git a/frontend/dashboard/src/visualization/renderer/modelShared.ts b/frontend/dashboard/src/visualization/renderer/modelShared.ts
index ac5c5b83..245c3c70 100644
--- a/frontend/dashboard/src/visualization/renderer/modelShared.ts
+++ b/frontend/dashboard/src/visualization/renderer/modelShared.ts
@@ -7,7 +7,7 @@ import type { VisualizationSelectionTarget } from './modelTypes';
 export function baseOption(spec: VisualizationSpecV1, animate: boolean): EChartsCoreOption {
   return {
     animation: animate,
-    aria: { enabled: true, description: visualizationAriaDescription(spec) },
+    aria: { enabled: true, description: spec.accessibility.description ?? visualizationAriaDescription(spec) },
     tooltip: { trigger: spec.kind === 'flow' ? 'item' : 'axis', confine: true },
   };
 }
diff --git a/frontend/dashboard/src/visualization/spec/accessibility.ts b/frontend/dashboard/src/visualization/spec/accessibility.ts
index 389c1f0b..6386a1ac 100644
--- a/frontend/dashboard/src/visualization/spec/accessibility.ts
+++ b/frontend/dashboard/src/visualization/spec/accessibility.ts
@@ -1,12 +1,15 @@
 import { tableRowsForVisualization } from './table';
 import type { VisualizationSpecV1 } from './types';
 
-export function visualizationAriaDescription(spec: VisualizationSpecV1): string {
+export function visualizationAriaDescription(
+  spec: VisualizationSpecV1,
+  translateText: (value: string) => string = value => value,
+): string {
   const rows = tableRowsForVisualization(spec);
-  const parts = [spec.title, stateDescription(spec), spec.accessibility.summary];
-  if (rows.length) parts.push(`${rows.length.toLocaleString()} table rows available.`);
-  if (spec.caveats?.length) parts.push(`Caveats: ${spec.caveats.join(' ')}`);
-  if (spec.accessibility.keyboardInstructions) parts.push(spec.accessibility.keyboardInstructions);
+  const parts = [translateText(spec.title), translateText(stateDescription(spec)), translateText(spec.accessibility.summary)];
+  if (rows.length) parts.push(translateText(`${rows.length.toLocaleString()} table rows available.`));
+  if (spec.caveats?.length) parts.push(`${translateText('Caveats:')} ${spec.caveats.map(translateText).join(' ')}`);
+  if (spec.accessibility.keyboardInstructions) parts.push(translateText(spec.accessibility.keyboardInstructions));
   return parts.filter(Boolean).join(' ');
 }
 
diff --git a/frontend/dashboard/src/visualization/spec/types.ts b/frontend/dashboard/src/visualization/spec/types.ts
index baf23a0b..257a7f33 100644
--- a/frontend/dashboard/src/visualization/spec/types.ts
+++ b/frontend/dashboard/src/visualization/spec/types.ts
@@ -44,6 +44,7 @@ export type VisualizationTableSpec = {
 
 export type VisualizationAccessibility = {
   summary: string;
+  description?: string;
   details?: string[];
   keyboardInstructions?: string;
 };
diff --git a/src/codex_usage_tracker/cli/commands_lifecycle.py b/src/codex_usage_tracker/cli/commands_lifecycle.py
index e7c8a6d1..b11ed041 100644
--- a/src/codex_usage_tracker/cli/commands_lifecycle.py
+++ b/src/codex_usage_tracker/cli/commands_lifecycle.py
@@ -17,6 +17,7 @@
 from codex_usage_tracker.core.formatting import (
     format_doctor,
 )
+from codex_usage_tracker.core.i18n import normalize_language
 from codex_usage_tracker.diagnostics.api import run_doctor
 from codex_usage_tracker.pricing.api import update_pricing_from_openai_docs, write_pricing_template
 from codex_usage_tracker.recommendation_engine.api import (
@@ -27,6 +28,10 @@
 from codex_usage_tracker.store.api import reset_usage_database
 
 
+def _chinese_output(args: argparse.Namespace) -> bool:
+    return normalize_language(getattr(args, "lang", None)) == "zh-Hans"
+
+
 def _run_setup(args: argparse.Namespace) -> int:
     lines = ["Codex Usage Tracker setup summary", ""]
     codex_home_exists = args.codex_home.expanduser().exists()
@@ -138,11 +143,18 @@ def _run_install_plugin(args: argparse.Namespace) -> int:
     if args.as_json:
         print_json(plugin_install_payload(result, schema="codex-usage-tracker-plugin-install-v1"))
         return 0
-    replacement_note = " Replaced existing plugin path." if result.replaced_existing else ""
-    print(f"Installed Codex Usage Tracker plugin at {result.plugin_dir}.{replacement_note}")
-    print(f"MCP Python: {result.python_executable}")
-    print(f"Updated marketplace: {result.marketplace_path}")
-    print("Restart Codex to discover the plugin.")
+    if _chinese_output(args):
+        replacement_note = "（已替换原有插件路径）" if result.replaced_existing else ""
+        print(f"Codex Usage Tracker 插件已安装到 {result.plugin_dir}{replacement_note}。")
+        print(f"MCP Python：{result.python_executable}")
+        print(f"已更新插件市场配置：{result.marketplace_path}")
+        print("请重启 Codex 以加载插件。")
+    else:
+        replacement_note = " Replaced existing plugin path." if result.replaced_existing else ""
+        print(f"Installed Codex Usage Tracker plugin at {result.plugin_dir}.{replacement_note}")
+        print(f"MCP Python: {result.python_executable}")
+        print(f"Updated marketplace: {result.marketplace_path}")
+        print("Restart Codex to discover the plugin.")
     return 0
 
 
@@ -156,10 +168,16 @@ def _run_upgrade_plugin(args: argparse.Namespace) -> int:
     if args.as_json:
         print_json(plugin_install_payload(result, schema="codex-usage-tracker-plugin-upgrade-v1"))
         return 0
-    print(f"Upgraded Codex Usage Tracker plugin at {result.plugin_dir}.")
-    print(f"MCP Python: {result.python_executable}")
-    print(f"Updated marketplace: {result.marketplace_path}")
-    print("Restart Codex to discover the refreshed plugin.")
+    if _chinese_output(args):
+        print(f"Codex Usage Tracker 插件已更新：{result.plugin_dir}。")
+        print(f"MCP Python：{result.python_executable}")
+        print(f"已更新插件市场配置：{result.marketplace_path}")
+        print("请重启 Codex 以加载更新后的插件。")
+    else:
+        print(f"Upgraded Codex Usage Tracker plugin at {result.plugin_dir}.")
+        print(f"MCP Python: {result.python_executable}")
+        print(f"Updated marketplace: {result.marketplace_path}")
+        print("Restart Codex to discover the refreshed plugin.")
     return 0
 
 
@@ -171,15 +189,22 @@ def _run_uninstall_plugin(args: argparse.Namespace) -> int:
     if args.as_json:
         print_json(plugin_uninstall_payload(result))
         return 0
-    print(
-        f"Removed plugin path: {'yes' if result.removed_plugin_path else 'already absent'} "
-        f"({result.plugin_dir})"
-    )
-    print(
-        f"Removed marketplace entry: {'yes' if result.removed_marketplace_entry else 'not present'} "
-        f"({result.marketplace_path})"
-    )
-    print("Restart Codex to unload plugin tools from new sessions.")
+    if _chinese_output(args):
+        plugin_state = "已移除" if result.removed_plugin_path else "原本不存在"
+        marketplace_state = "已移除" if result.removed_marketplace_entry else "原本不存在"
+        print(f"插件路径：{plugin_state}（{result.plugin_dir}）")
+        print(f"插件市场条目：{marketplace_state}（{result.marketplace_path}）")
+        print("请重启 Codex，使新会话不再加载该插件工具。")
+    else:
+        print(
+            f"Removed plugin path: {'yes' if result.removed_plugin_path else 'already absent'} "
+            f"({result.plugin_dir})"
+        )
+        print(
+            f"Removed marketplace entry: {'yes' if result.removed_marketplace_entry else 'not present'} "
+            f"({result.marketplace_path})"
+        )
+        print("Restart Codex to unload plugin tools from new sessions.")
     return 0
 
 
diff --git a/src/codex_usage_tracker/cli/dashboard.py b/src/codex_usage_tracker/cli/dashboard.py
index 3234e46b..40de85f6 100644
--- a/src/codex_usage_tracker/cli/dashboard.py
+++ b/src/codex_usage_tracker/cli/dashboard.py
@@ -29,7 +29,11 @@ def run_dashboard(args: argparse.Namespace) -> int:
             )
         )
     else:
-        print(f"Wrote dashboard to {output}")
+        print(
+            f"仪表盘已写入 {output}"
+            if _language(args) == "zh-Hans"
+            else f"Wrote dashboard to {output}"
+        )
     if args.open:
         webbrowser.open(output.resolve().as_uri())
     return 0
@@ -52,7 +56,11 @@ def run_open_dashboard(args: argparse.Namespace) -> int:
             }
         )
     else:
-        print(f"Opening dashboard at {output}")
+        print(
+            f"正在打开仪表盘：{output}"
+            if _language(args) == "zh-Hans"
+            else f"Opening dashboard at {output}"
+        )
     webbrowser.open(output.resolve().as_uri())
     return 0
 
diff --git a/src/codex_usage_tracker/cli/help_i18n.py b/src/codex_usage_tracker/cli/help_i18n.py
new file mode 100644
index 00000000..935a238d
--- /dev/null
+++ b/src/codex_usage_tracker/cli/help_i18n.py
@@ -0,0 +1,170 @@
+"""Human-facing CLI help localization without changing command contracts."""
+
+from __future__ import annotations
+
+import argparse
+from collections.abc import Sequence
+
+from codex_usage_tracker.core.i18n import normalize_language
+
+_ZH_HANS = "zh-Hans"
+
+_ZH_HANS_HELP: dict[str, str] = {
+    "show this help message and exit": "显示此帮助信息并退出",
+    "show program's version number and exit": "显示程序版本并退出",
+    "Initial dashboard language. Accepts supported language codes and common aliases; defaults to CODEX_USAGE_TRACKER_LANG or en.": "仪表盘初始语言。可使用受支持的语言代码和常见别名；默认读取 CODEX_USAGE_TRACKER_LANG，未设置时使用英语。",
+    "Project metadata display mode: normal keeps local labels, redacted hides raw paths and hashes unnamed projects, strict also hides branch, relative cwd, and tags.": "项目元数据展示模式：normal 保留本地标签；redacted 隐藏原始路径并哈希未命名项目；strict 还会隐藏分支、相对工作目录和标签。",
+    "Python executable Codex should use for the MCP server.": "Codex 启动 MCP 服务器时使用的 Python 可执行文件。",
+    "Replace an existing generated plugin wrapper or source-checkout symlink.": "替换现有的插件包装目录或源码检出符号链接。",
+    "Fetch current pricing during setup instead of writing a local template.": "设置时获取当前定价，而不是写入本地模板。",
+    "Include read-only repair suggestions for warning and failure checks.": "为警告和失败检查提供只读修复建议。",
+    "Replace an existing generated plugin directory or source-checkout symlink.": "替换现有的插件目录或源码检出符号链接。",
+    "Skip local content indexing and store aggregate usage rows only.": "跳过本地内容索引，只保存聚合用量记录。",
+    "Rebuild aggregate usage rows without local content indexing.": "重建聚合用量记录，但不建立本地内容索引。",
+    "Only include calls at or after this ISO date/time": "只包含此 ISO 日期/时间之后（含）的调用",
+    "Only include calls at or before this ISO date/time": "只包含此 ISO 日期/时间之前（含）的调用",
+    "Run slower full hypothesis evidence scans instead of quick routing checks.": "运行较慢的完整假设证据扫描，而不是快速路由检查。",
+    "Also run the slower full usage_investigate dogfood paths instead of reusing action brief findings.": "同时运行较慢的完整 usage_investigate 自测流程，不复用行动摘要结论。",
+    "Refresh active local usage before running the dogfood report.": "运行自测报告前刷新活动的本地用量。",
+    "Write a compact Markdown summary next to summary.json.": "在 summary.json 旁写入精简的 Markdown 摘要。",
+    "Confirm clearing local aggregate usage rows. Raw Codex logs are not touched.": "确认清除本地聚合用量记录；不会改动 Codex 原始日志。",
+    "Convenience preset for common summaries": "常用摘要的快捷预设",
+    "Maximum rows to return; use 0 for all": "最多返回的记录数；0 表示全部",
+    "Accepted for consistency; query always returns JSON.": "为保持接口一致而接受；query 始终返回 JSON。",
+    "Accepted for consistency; action-brief always returns JSON.": "为保持接口一致而接受；action-brief 始终返回 JSON。",
+    "Maximum rows; use 0 for all": "最大记录数；0 表示全部",
+    "Recompute and persist the overview snapshot before reading it.": "读取前重新计算并保存概览快照。",
+    "Recompute and persist the tool-output snapshot before reading it.": "读取前重新计算并保存工具输出快照。",
+    "Recompute and persist the command snapshot before reading it.": "读取前重新计算并保存命令快照。",
+    "Recompute and persist the Git interaction snapshot before reading it.": "读取前重新计算并保存 Git 交互快照。",
+    "Recompute and persist the file-read snapshot before reading it.": "读取前重新计算并保存文件读取快照。",
+    "Recompute and persist the file-modification snapshot before reading it.": "读取前重新计算并保存文件修改快照。",
+    "Recompute and persist the read-productivity snapshot before reading it.": "读取前重新计算并保存读取成效快照。",
+    "Recompute and persist the concentration snapshot before reading it.": "读取前重新计算并保存集中度快照。",
+    "Recompute and persist guided summary snapshot before reading it.": "读取前重新计算并保存引导式摘要快照。",
+    "Recompute and persist the usage-drain snapshot before reading it.": "读取前重新计算并保存用量消耗快照。",
+    "Maximum redacted context characters to return; use 0 for no character limit.": "最多返回的脱敏上下文字符数；0 表示不限制字符数。",
+    "Maximum context entries to return; use 0 for all matching entries.": "最多返回的上下文条目数；0 表示返回全部匹配条目。",
+    "Include redacted, size-limited tool output in the on-demand context.": "在按需上下文中包含经过脱敏和大小限制的工具输出。",
+    "Include redacted compaction replacement history when a compaction event is present.": "存在压缩事件时，包含经过脱敏的压缩替换历史。",
+    "Maximum calls to load; use 0 for all": "最多加载的调用数；0 表示全部",
+    "Include archived session rows already present in the SQLite index.": "包含 SQLite 索引中已有的归档会话记录。",
+    "Include archived sessions when refreshing and in the generated dashboard.": "刷新和生成仪表盘时包含归档会话。",
+    "Refresh the SQLite index before generating the dashboard. This is the default; use --no-refresh to open the cached index only.": "生成仪表盘前刷新 SQLite 索引（默认行为）；使用 --no-refresh 可只打开缓存索引。",
+    "Initial maximum calls to load; use 0 for all": "初始最多加载的调用数；0 表示全部",
+    "Enable explicit per-row context loading or disable the context API.": "启用显式的逐记录上下文加载，或禁用上下文 API。",
+    "Start with dashboard context loading off; it can be enabled from the local dashboard.": "启动时关闭仪表盘上下文加载；之后可在本地仪表盘中启用。",
+    "Refresh the SQLite index before generating and serving the dashboard. This is the default; use --no-refresh to serve the cached index only.": "生成并提供仪表盘前刷新 SQLite 索引（默认行为）；使用 --no-refresh 可只提供缓存索引。",
+    "Accepted for API consistency; serve-dashboard still runs as a long-lived server.": "为保持 API 一致而接受；serve-dashboard 仍会作为常驻服务器运行。",
+    "Convenience date window": "快捷日期范围",
+    "Return the coverage report as JSON": "以 JSON 返回覆盖率报告",
+    "Return source coverage report as JSON": "以 JSON 返回来源覆盖率报告",
+    "Skip estimated prices for internal Codex model labels.": "跳过内部 Codex 模型标签的估算价格。",
+    "Pasted usage text. Reads stdin when omitted.": "粘贴的用量文本；省略时从标准输入读取。",
+    "Overwrite an invalid existing allowance config.": "覆盖现有的无效使用限额配置。",
+    "Limit analysis to one observed allowance window kind.": "仅分析一种已观测的额度窗口。",
+    "Maximum normalized observations to inspect. Use 0 for all.": "最多检查的标准化观测数；0 表示全部。",
+    "Include archived Codex sessions.": "包含已归档的 Codex 会话。",
+    "Validate and copy this JSON rate-card snapshot instead of the bundled one.": "验证并复制此 JSON 费率表快照，而不使用内置快照。",
+    "Run first-time setup: plugin install, pricing init, refresh, and doctor": "执行首次设置：安装插件、初始化定价、刷新索引并运行环境检查",
+    "Check local setup without writing files": "检查本地设置，不写入文件",
+    "Register this installed package as a local Codex plugin": "将已安装的软件包注册为本地 Codex 插件",
+    "Refresh the generated local Codex plugin wrapper for this installed package": "刷新此软件包生成的本地 Codex 插件包装目录",
+    "Remove the generated local Codex plugin wrapper and marketplace entry": "移除生成的本地 Codex 插件包装目录和市场条目",
+    "Scan Codex logs into SQLite": "扫描 Codex 日志并写入 SQLite",
+    "Inspect one Codex JSONL log through the parser without writing to SQLite": "使用解析器检查一个 Codex JSONL 日志，不写入 SQLite",
+    "Clear aggregate rows and rescan local Codex logs": "清除聚合记录并重新扫描本地 Codex 日志",
+    "Run repeatable local dogfood checks for agentic MCP investigation reports": "针对智能体 MCP 调查报告运行可重复的本地自测",
+    "Clear tracker-owned aggregate rows and refresh metadata": "清除跟踪器管理的聚合记录并刷新元数据",
+    "Show aggregate usage summary": "显示聚合用量摘要",
+    "Return stable JSON aggregate usage rows with filters": "按筛选条件返回稳定格式的 JSON 聚合用量记录",
+    "Rank aggregate usage rows and threads by action recommendation severity": "按行动建议严重程度排列聚合用量记录和线程",
+    "Build compact aggregate remediation brief for usage-waste investigations": "为用量浪费调查生成精简的聚合改进摘要",
+    "Inspect aggregate diagnostic facts and their associated token costs": "检查聚合诊断事实及其关联token成本",
+    "Show one session's usage": "显示一个会话的用量",
+    "Load raw logged context for one usage record on demand": "按需加载一条用量记录的原始日志上下文",
+    "Generate static dashboard": "生成静态仪表盘",
+    "Generate the default dashboard and open it": "生成并打开默认仪表盘",
+    "Serve dashboard with lazy localhost context loading": "启动仪表盘服务，并按需从本机加载上下文",
+    "Show copied clone usage rows excluded from billable totals": "显示已从计费汇总中排除的克隆复制记录",
+    "Show largest last-call usage rows": "显示末次调用用量最大的记录",
+    "Show priced, estimated, and unpriced token coverage": "显示已定价、估算和未定价token的覆盖情况",
+    "Show source provenance and parser coverage": "显示数据来源和解析器覆盖情况",
+    "Export aggregate usage CSV": "导出聚合用量 CSV",
+    "Write a local pricing template": "写入本地定价模板",
+    "Fetch OpenAI text-token pricing into the local config": "获取 OpenAI 文本token定价并写入本地配置",
+    "Copy the current local pricing config to a reproducible report snapshot": "将当前本地定价配置复制为可复现的报告快照",
+    "Write a local template for optional Codex allowance windows": "写入可选 Codex 额度窗口的本地模板",
+    "Update allowance windows from pasted Codex /status or usage text": "根据粘贴的 Codex /status 或用量文本更新额度窗口",
+    "Return normalized observed Codex allowance history": "返回标准化的 Codex 额度观测历史",
+    "Diagnose observed allowance movement against local credit estimates": "结合本地点数估算诊断已观测的额度变化",
+    "Build strict-privacy allowance evidence bundle for manual sharing": "生成可手动分享的严格隐私额度证据包",
+    "Write the bundled or supplied Codex credit rate-card snapshot locally": "在本地写入内置或指定的 Codex 点数费率表快照",
+    "Write a local template for dashboard recommendation thresholds": "写入仪表盘建议阈值的本地模板",
+    "Write a local template for project aliases, ignored paths, and tags": "写入项目别名、忽略路径和标签的本地模板",
+    "Write a privacy-preserving diagnostic bundle for support": "写入保护隐私的支持诊断包",
+}
+
+
+class ChineseArgumentParser(argparse.ArgumentParser):
+    """Argument parser with Simplified Chinese argparse section labels."""
+
+    def format_help(self) -> str:
+        return _translate_argparse_sections(super().format_help())
+
+    def format_usage(self) -> str:
+        return _translate_argparse_sections(super().format_usage())
+
+
+def requested_cli_language(argv: Sequence[str]) -> str:
+    """Read the global language before argparse renders help or errors."""
+
+    for index, argument in enumerate(argv):
+        if argument.startswith("--lang="):
+            return normalize_language(argument.partition("=")[2])
+        if argument == "--lang" and index + 1 < len(argv):
+            return normalize_language(argv[index + 1])
+    return normalize_language()
+
+
+def argument_parser_class(language: str | None) -> type[argparse.ArgumentParser]:
+    return ChineseArgumentParser if normalize_language(language) == _ZH_HANS else argparse.ArgumentParser
+
+
+def localize_parser_help(parser: argparse.ArgumentParser, language: str | None) -> None:
+    """Translate parser descriptions and help strings in place for human output."""
+
+    if normalize_language(language) != _ZH_HANS:
+        return
+    parser.description = _translate(parser.description)
+    parser.epilog = _translate(parser.epilog)
+    for action in parser._actions:
+        if isinstance(action.help, str):
+            action.help = _translate(action.help)
+        if isinstance(action, argparse._SubParsersAction):
+            for choice_action in action._choices_actions:
+                if isinstance(choice_action.help, str):
+                    choice_action.help = _translate(choice_action.help)
+            for child in action.choices.values():
+                localize_parser_help(child, language)
+
+
+def localized_cli_error_prefix(language: str | None) -> str:
+    return "错误" if normalize_language(language) == _ZH_HANS else "Error"
+
+
+def _translate(value: str | None) -> str | None:
+    if value is None:
+        return None
+    return _ZH_HANS_HELP.get(value, value)
+
+
+def _translate_argparse_sections(value: str) -> str:
+    replacements = {
+        "usage: ": "用法：",
+        "positional arguments:\n": "位置参数：\n",
+        "options:\n": "选项：\n",
+    }
+    for source, translated in replacements.items():
+        value = value.replace(source, translated)
+    return value
diff --git a/src/codex_usage_tracker/cli/main.py b/src/codex_usage_tracker/cli/main.py
index 9691b2ec..934a6997 100644
--- a/src/codex_usage_tracker/cli/main.py
+++ b/src/codex_usage_tracker/cli/main.py
@@ -52,6 +52,7 @@
     run_serve_dashboard,
 )
 from codex_usage_tracker.cli.diagnostics import run_diagnostics
+from codex_usage_tracker.cli.help_i18n import localized_cli_error_prefix, requested_cli_language
 from codex_usage_tracker.cli.inspect_log_output import print_inspect_log_summary
 from codex_usage_tracker.cli.parser import build_parser
 from codex_usage_tracker.core.api_payloads import (
@@ -73,16 +74,18 @@ def main() -> int:
         ValueError,
         OSError,
     ) as exc:
-        print(f"Error: [{error_code(exc)}] {exc}", file=sys.stderr)
+        language = requested_cli_language(sys.argv[1:])
+        print(f"{localized_cli_error_prefix(language)}: [{error_code(exc)}] {exc}", file=sys.stderr)
         return 1
 
 
 def _main() -> int:
-    parser = build_parser()
+    language = requested_cli_language(sys.argv[1:])
+    parser = build_parser(language)
     args = parser.parse_args()
     handler = _COMMAND_HANDLERS.get(args.command)
     if handler is None:
-        parser.error("unknown command")
+        parser.error("未知命令" if language == "zh-Hans" else "unknown command")
         return 2
     return handler(args)
 
diff --git a/src/codex_usage_tracker/cli/parser.py b/src/codex_usage_tracker/cli/parser.py
index 4b6baca8..3ea78056 100644
--- a/src/codex_usage_tracker/cli/parser.py
+++ b/src/codex_usage_tracker/cli/parser.py
@@ -6,6 +6,7 @@
 from pathlib import Path
 
 from codex_usage_tracker import __version__
+from codex_usage_tracker.cli.help_i18n import argument_parser_class, localize_parser_help
 from codex_usage_tracker.cli.parser_data import (
     _add_allowance_intelligence_parsers,
     _add_allowance_parser,
@@ -53,8 +54,9 @@
 from codex_usage_tracker.core.projects import PRIVACY_MODE_CHOICES
 
 
-def build_parser() -> argparse.ArgumentParser:
-    parser = argparse.ArgumentParser(prog="codex-usage-tracker")
+def build_parser(language: str | None = None) -> argparse.ArgumentParser:
+    parser_class = argument_parser_class(language)
+    parser = parser_class(prog="codex-usage-tracker")
     parser.add_argument("--version", action="version", version=f"%(prog)s {__version__}")
     parser.add_argument("--db", type=Path, default=DEFAULT_DB_PATH)
     parser.add_argument("--pricing", type=Path, default=DEFAULT_PRICING_PATH)
@@ -110,4 +112,5 @@ def build_parser() -> argparse.ArgumentParser:
     _add_threshold_parser(subparsers)
     _add_project_parser(subparsers)
     _add_support_bundle_parser(subparsers)
+    localize_parser_help(parser, language)
     return parser
diff --git a/src/codex_usage_tracker/plugin_data/dashboard/locales/zh-Hans.json b/src/codex_usage_tracker/plugin_data/dashboard/locales/zh-Hans.json
index f033439a..408353f4 100644
--- a/src/codex_usage_tracker/plugin_data/dashboard/locales/zh-Hans.json
+++ b/src/codex_usage_tracker/plugin_data/dashboard/locales/zh-Hans.json
@@ -1,23 +1,23 @@
 {
-  "action.check_cache_drop": "检查缓存重用删除后重新引入的文件或工具输出。",
+  "action.check_cache_drop": "检查缓存复用下降后是否重新引入了文件或工具输出。",
   "action.compare_fresh_input": "在继续之前，将新输入与上一回合进行比较。",
-  "action.compare_subagent_calls": "在更改父工作流程之前比较附加的子代理或审查调用。",
-  "action.configure_pricing": "在信任成本总计之前配置定价。",
+  "action.compare_subagent_calls": "调整父级工作流前，先比较关联的子智能体调用或审查调用。",
+  "action.configure_pricing": "配置定价后再采用成本汇总。",
   "action.copied": "已复制",
   "action.copy_failed": "复制失败",
   "action.expand_or_select_recommendations": "展开调用或选择一行以获取调用级别的建议。",
-  "action.exported": "导出 {count}",
+  "action.exported": "已导出 {count} 项",
   "action.inspect_thread_timeline": "检查线程时间线并考虑启动一个新线程。",
   "action.review_context_growth": "查看上下文增长的开始位置并考虑启动一个新线程。",
-  "action.review_reasoning_effort": "检查推理工作是否适合这项任务。",
+  "action.review_reasoning_effort": "检查当前推理强度是否适合此任务。",
   "action.run": "运行",
   "action.set_limits": "设置限额",
   "action.use_aggregate_first": "先使用聚合字段；仅当信号仍不清楚时才加载上下文。",
-  "allowance.counted": "{value} 使用额度计入 Codex 使用限额",
-  "allowance.cr_left": "剩余 {value} 使用额度",
-  "allowance.credit_coverage": "已加载 Token 的使用额度覆盖率为 {ratio}。",
-  "allowance.credit_rates": "使用额度费率：{source}。",
-  "allowance.credits_remaining": "剩余 {value} 使用额度",
+  "allowance.counted": "{value} 点已计入 Codex 使用限额",
+  "allowance.cr_left": "剩余 {value} 点",
+  "allowance.credit_coverage": "已加载token的点数费率覆盖率为 {ratio}。",
+  "allowance.credit_rates": "点数费率：{source}。",
+  "allowance.credits_remaining": "剩余 {value} 点",
   "allowance.init_hint": "运行 codex-usage-tracker init-allowance 以添加剩余使用额度窗口。",
   "allowance.live_check_recommended": "最近 {count} 次 Codex 调用报告了另一组限额桶 {limit}，因此此本地快照可能已过期。在参考顶部卡片的剩余额度前，建议先核对实时使用情况。",
   "allowance.live_check_short": "核对实时数据",
@@ -28,14 +28,14 @@
   "allowance.observed_last": "最近观测：{age}。",
   "allowance.observed_limit": "限额：{limit}。",
   "allowance.observed_plan": "套餐：{plan}。",
-  "allowance.observed_source_hint": "读取自最新一条包含剩余使用额度的本地 Codex Token 计数日志；这不是实时账号查询，可能无法覆盖其他 Agent 平台。",
+  "allowance.observed_source_hint": "读取自最新一条包含剩余额度信息的本地 Codex token计数日志；这不是实时账户查询，也可能未涵盖其他智能体功能入口。",
   "allowance.observed_window": "{label}：已用 {used}",
   "allowance.of_allowance": "占限额 {ratio}",
-  "allowance.of_total": "{total} 使用额度中已用 {used}",
-  "allowance.rate_card_error": "费率卡错误：{error}",
+  "allowance.of_total": "已用 {used}/{total} 点",
+  "allowance.rate_card_error": "费率表错误：{error}",
   "allowance.remaining": "剩余 {value}",
   "allowance.resets": "重置时间：{resets}",
-  "allowance.row_no_rate": "没有匹配的 Codex 使用额度费率",
+  "allowance.row_no_rate": "未匹配到 Codex 点数费率",
   "allowance.title_hint": "添加 ~/.codex-usage-tracker/allowance.json 以显示 5 小时和每周剩余使用额度。",
   "allowance.used_vs_remaining": "已用 {used}，剩余 {remaining}",
   "allowance.window_configured": "{label} 已配置",
@@ -49,7 +49,7 @@
   "aria.refresh_controls": "仪表板刷新控件",
   "aria.table_pages": "表格分页",
   "badge.costs": "成本",
-  "badge.credits": "使用额度",
+  "badge.credits": "点数",
   "badge.live": "实时",
   "badge.metadata_mode": "元数据：{mode}",
   "badge.metadata_normal": "元数据正常",
@@ -82,12 +82,12 @@
   "button.show_turn_evidence": "显示轮次日志证据",
   "button.top": "返回顶部",
   "call.cache_accounting_delta": "缓存与计量差异",
-  "call.cache_body_cold": "会话专用缓存可能已过期或未命中；剩余缓存可能是稳定的 Codex 脚手架或工具 schema 前缀。",
+  "call.cache_body_cold": "会话专用缓存可能已过期或未命中；剩余缓存可能来自稳定的 Codex 框架内容或工具定义前缀。",
   "call.cache_body_partial": "部分前缀复用了缓存，但输入中有相当一部分是新的或被重新序列化。",
-  "call.cache_body_post_compaction": "此调用关联了压缩标记或类似重置的配置。请检查已加载证据以确认替换上下文。",
-  "call.cache_body_spike": "与此已解析线程中的上一次调用相比，新输入急剧上升。",
+  "call.cache_body_post_compaction": "此调用关联了压缩标记或类似重置的特征。请检查已加载证据，确认替换后的上下文。",
+  "call.cache_body_spike": "与当前归属线程中的上一次调用相比，新增输入急剧上升。",
   "call.cache_body_uncached": "此调用几乎没有或完全没有缓存复用，因此大部分输入按新输入计费。",
-  "call.cache_body_warm": "大多数输入 Token 复用了提示缓存。未缓存部分最可能是调查目标。",
+  "call.cache_body_warm": "大多数输入token复用了提示缓存；未缓存部分最值得优先排查。",
   "call.cache_cold": "冷启动恢复 / 缓存已失效",
   "call.cache_diagnostics": "缓存诊断",
   "call.cache_partial": "部分缓存未命中",
@@ -95,50 +95,50 @@
   "call.cache_steady": "缓存状态稳定",
   "call.cache_warm": "缓存复用良好",
   "call.compaction_diagnostics": "压缩诊断",
-  "call.compaction_hint": "加载的证据可以显示明确的压缩事件。仅在压缩替换操作之后才会显示编辑的替换历史记录。",
+  "call.compaction_hint": "已加载证据可显示明确的压缩事件。仅在选择“显示压缩后的替换历史”后，才会显示已脱敏的替换历史。",
   "call.context_estimate": "上下文变化估算",
   "call.context_estimate_hint": "将精确的未缓存输入与分词器计数的可见日志证据进行比较。该差距应被视为隐藏的脚手架、序列化或分词器估计错误。",
   "call.delta.cache_drop": "新输入增加 {uncached}，而缓存输入减少 {cached}；这是典型的缓存下降模式。",
-  "call.delta.stable": "与该解析后线程中的上一次调用相比，Token 计量整体稳定。",
+  "call.delta.stable": "与当前归属线程中的上一次调用相比，token计量整体稳定。",
   "call.delta.uncached_decrease_cached_increase": "新输入减少 {uncached}，缓存输入增加，因此此调用比上一次更高效地复用了上下文。",
   "call.delta.uncached_increase": "新输入比上一次调用增加 {uncached}；请检查证据中是否有新文件、工具结果或重写的上下文。",
   "call.derived_label": "根据相邻调用汇总数据推导",
   "call.estimated_label": "根据可见日志量估算",
   "call.evidence_label": "运行时证据",
-  "call.exact_accounting": "精确 Token 计量",
-  "call.exact_label": "来自 Token 回调的精确数据",
+  "call.exact_accounting": "精确token计量",
+  "call.exact_label": "来自token计数回调的精确数据",
   "call.hidden_estimate": "未解释的隐藏/序列化输入估算",
   "call.next_step.cold": "先比较上一次调用，再检查已加载证据，查看缓存未命中后发送了哪些新上下文。",
   "call.next_step.delta": "使用增量卡定位变化来自缓存输入、未缓存输入还是输出/推理。",
   "call.next_step.isolated": "如果聚合总数不足以理解这个孤立调用，请使用已加载证据。",
   "call.next_step.post_compaction": "在解释缓存增量前，请检查已加载证据中是否有明确的压缩标记或替换历史。",
   "call.next_step.spike": "请先检查最新的证据条目；峰值来自新的未缓存输入，而不是缓存历史。",
-  "call.next_step.warm": "缓存复用健康；重点关注仍按新输入计费的 {uncached} 个未缓存 Token。",
-  "call.no_previous": "该解析后线程中没有上一次调用。",
+  "call.next_step.warm": "缓存复用状况良好；重点检查仍按新增输入计费的 {uncached} 个未缓存token。",
+  "call.no_previous": "当前归属线程中没有上一次调用。",
   "call.not_found": "在已加载的仪表板行中未找到所选调用。",
   "call.open_hint": "单击调用行可查看深度诊断。",
-  "call.position": "该解析后线程中的第 {position} 次调用",
+  "call.position": "当前归属线程中的第 {position} 次调用",
   "call.post_compaction": "可能发生过上下文压缩",
   "call.raw_evidence": "原始证据",
   "call.readout.badge": "精确数据 + 推导数据 + 按需证据",
-  "call.readout.evidence_analyzed": "证据已分析：{totalEntries} 个选中轮次条目，{visibleChars} 个可见已编辑字符，通过 {estimator} 得到 {visibleTokens} 个可见 token。{serializedDetail} 初始渲染 {renderedEntries} 个条目。",
+  "call.readout.evidence_analyzed": "证据分析完成：选中轮次包含 {totalEntries} 个条目、{visibleChars} 个可见脱敏字符；通过 {estimator} 估得 {visibleTokens} 个可见token。{serializedDetail} 初始渲染了 {renderedEntries} 个条目。",
   "call.readout.evidence_label": "证据状态",
-  "call.readout.evidence_loading": "正在从本地 JSONL 源加载证据。聚合 token 计数是精确的，但可见上下文归因需要这些运行时证据。",
-  "call.readout.evidence_serialized_bound": "序列化本地上限：来自 {chars} 个原始 JSON 字符的 {tokens} 个 token。",
+  "call.readout.evidence_loading": "正在从本地 JSONL 源加载证据。聚合token计数是精确的，但可见上下文归因仍需要这些运行时证据。",
+  "call.readout.evidence_serialized_bound": "本地序列化上限：{chars} 个原始 JSON 字符对应 {tokens} 个token。",
   "call.readout.evidence_serialized_deferred": "仅快速序列化估算；完整序列化分组已延后。",
-  "call.readout.exact_body": "{input} 输入 Token = {cached} 缓存 + {uncached} 未缓存；{output} 输出 Token；{cache} 缓存复用。",
+  "call.readout.exact_body": "{input} 个输入token = {cached} 个缓存token + {uncached} 个未缓存token；{output} 个输出token；缓存复用率 {cache}。",
   "call.readout.exact_label": "精确回调计量",
   "call.readout.next_label": "下一步诊断建议",
   "call.readout.previous_label": "与上一次调用对比",
-  "call.readout.previous_unavailable": "此已解析线程没有加载上一次调用，因此调用间增量不可用。",
+  "call.readout.previous_unavailable": "当前归属线程的上一次调用尚未加载，因此无法计算调用间增量。",
   "call.readout.title": "调用分析摘要",
   "call.remaining_after_serialized": "扣除序列化上限后的剩余量",
-  "call.remaining_after_serialized_hint": "即使序列化上限也未覆盖未缓存的输入",
-  "call.serialized_bound_hint": "上限局部 JSONL 结构；不准确的提示文本。",
+  "call.remaining_after_serialized_hint": "序列化上限仍未覆盖的未缓存输入量",
+  "call.serialized_bound_hint": "本地 JSONL 结构的上限估算；并非精确的提示词文本。",
   "call.serialized_breakdown": "序列化证据分组",
   "call.serialized_bucket_detail": "{count} 字段 · {chars} 字符",
   "call.serialized_candidate": "可能的序列化开销",
-  "call.serialized_candidate_hint": "序列化上限减去可见估计，由精确的未缓存输入限制",
+  "call.serialized_candidate_hint": "序列化上限减去可见估算，并以精确未缓存输入为上限",
   "call.serialized_deferred": "已加载快速估算；完整序列化分组已延后。",
   "call.serialized_quick_hint": "快速估算",
   "call.serialized_upper_bound": "本地序列化上限",
@@ -146,31 +146,31 @@
   "call.visible_gap": "未缓存输入减去可见估算",
   "caption.ascending": "升序",
   "caption.call_investigator": "调查调用 {record}。",
-  "caption.calls": "显示按 {sort} 排序的各个模型调用。 {loaded}。",
+  "caption.calls": "显示按 {sort} 排序的各次模型调用。{loaded}。",
   "caption.date_prefix": "{label}。",
   "caption.descending": "降序",
   "caption.initial_calls": "显示单独的模型调用。",
-  "caption.insights": "按成本、使用积分、缓存重用、上下文压力和定价信心排名。",
-  "caption.loaded": "{loaded} 调用已加载",
-  "caption.loaded_capped": "已加载 {available} 调用中的 {loaded}",
+  "caption.insights": "按成本、使用点数、缓存复用率、上下文压力和定价置信度排序。",
+  "caption.loaded": "已加载 {loaded} 次调用",
+  "caption.loaded_capped": "已加载 {loaded}/{available} 次调用",
   "caption.rows_loaded_progress": "已加载行：{loaded} / {total}",
   "caption.rows_loading_background": "仪表板汇总已就绪。行数据正在后台加载。",
   "caption.rows_loading_progress": "正在加载行：{loaded} / {total}",
   "caption.sort_direction": "{label} {direction}",
-  "caption.threads": "显示来自 {calls} 过滤调用的 {threads} 线程，按 {sort} 排序。 {loaded}。单击一个线程可展开其调用。",
+  "caption.threads": "从筛选后的 {calls} 次调用中显示 {threads} 个线程，按 {sort} 排序。{loaded}。单击线程可展开其调用。",
   "context.api_http": "上下文 API 返回 HTTP {status}。",
   "context.api_unavailable": "此处无法使用上下文 API。请运行 codex-usage-tracker serve-dashboard --open 以按需加载上下文。",
   "context.auto_loading": "正在加载所选轮次的证据，并包含工具输出。",
   "context.chars_omitted": "已省略超出上限的 {count} 个字符。",
   "context.compaction_detected": "检测到上下文压缩",
   "context.compaction_replacement": "压缩后的替换上下文",
-  "context.compaction_replacement_count": "{count} 替换历史记录条目可用。",
+  "context.compaction_replacement_count": "{count} 条替换历史记录可用。",
   "context.disabled_hint": "此仪表板服务器已关闭上下文加载。请在此启用后按需读取本地 JSONL 上下文。",
   "context.enabled_note": "已启用上下文加载。点击“显示轮次日志证据”可从本地 JSONL 源读取此次调用。",
   "context.file_hint": "使用 codex-usage-tracker serve-dashboard 打开此仪表板，以按需加载原始上下文。",
   "context.line": "第 {line} 行",
   "context.loading": "正在加载本地上下文…",
-  "context.local_redacted": "按需加载本地 JSONL 上下文。提示和工具输出针对常见秘密模式进行了编辑，并且不会保留到 SQLite 或仪表板 HTML。",
+  "context.local_redacted": "按需加载本地 JSONL 上下文。提示词和工具输出会按常见敏感信息模式脱敏，且不会写入 SQLite 或仪表板 HTML。",
   "context.no_char_limit_active": "未设置字符数限制。",
   "context.no_record_id": "此行没有可用于查询上下文的记录 ID。",
   "context.no_response": "没有响应正文",
@@ -178,30 +178,30 @@
   "context.ready_hint": "此仪表板不嵌入上下文。点击按钮可从本地 JSONL 源读取此次调用。",
   "context.settings_http": "上下文设置返回 HTTP {status}。",
   "context.source": "来源：{file}:{line}",
-  "context.token_breakdown": "Token 明细",
+  "context.token_breakdown": "token明细",
   "context.token_cached": "缓存输入",
   "context.token_input": "输入",
   "context.token_output": "输出",
   "context.token_reasoning": "推理输出",
-  "context.token_required": "上下文加载需要 localhost 仪表板 API Token。",
+  "context.token_required": "上下文加载需要 localhost 仪表板 API 令牌。",
   "context.token_scope_call": "这个调用",
-  "context.token_scope_earlier": "同一回合较早的Token计数",
-  "context.token_scope_previous": "同一回合中之前的Token计数",
-  "context.token_scope_selected": "选定的调用Token计数",
+  "context.token_scope_earlier": "同一轮次中较早的token计数",
+  "context.token_scope_previous": "同一轮次中的上一次token计数",
+  "context.token_scope_selected": "所选调用的token计数",
   "context.token_scope_session": "会话累计",
   "context.token_total": "总计",
   "context.token_type": "类型",
   "context.token_uncached": "未缓存输入",
-  "context.tool_included": "工具输出包含修订和大小限制。",
+  "context.tool_included": "工具输出已纳入，并施加脱敏和大小限制。",
   "context.tool_omitted": "该视图的工具输出已隐藏。",
-  "credit.configured_rate": "已配置费率",
-  "credit.estimated_mapping": "估算映射",
+  "credit.configured_rate": "已配置点数费率",
+  "credit.estimated_mapping": "估算的点数映射",
   "credit.inferred_mapping": "推断模型映射",
-  "credit.no_mapped_rate": "无匹配费率",
-  "credit.no_rate": "无使用额度费率",
-  "credit.official_match": "匹配官方费率卡",
-  "credit.user_rate": "用户提供的使用额度费率",
-  "credit.with_status": "{value} 使用额度 · {status}",
+  "credit.no_mapped_rate": "未匹配到点数费率",
+  "credit.no_rate": "无点数费率",
+  "credit.official_match": "匹配官方费率表",
+  "credit.user_rate": "用户提供的点数费率",
+  "credit.with_status": "{value} 点 · {status}",
   "dashboard.call_details": "调用详情",
   "dashboard.detail.empty": "悬停或单击一行可查看汇总使用字段。",
   "dashboard.eyebrow": "本地 Codex 使用分析",
@@ -218,34 +218,34 @@
   "date.invalid_range": "日期范围无效",
   "date.range_between": "{prefix} {start} 至 {end}",
   "date.range_exact": "{prefix} {date}",
-  "date.range_from": "{prefix} 来自 {start}",
-  "date.range_through": "{prefix} 到 {end}",
-  "detail.agent_nickname": "Agent 昵称",
-  "detail.agent_role": "Agent 角色",
+  "date.range_from": "{prefix} 从 {start} 起",
+  "date.range_through": "{prefix} 截至 {end}",
+  "detail.agent_nickname": "智能体昵称",
+  "detail.agent_role": "智能体角色",
   "detail.allowance_impact": "限额影响",
   "detail.attached_calls": "关联调用",
   "detail.auto_review_calls": "自动审查调用",
-  "detail.cache_savings": "缓存节省",
+  "detail.cache_savings": "缓存节省量",
   "detail.call_number": "第 {number} 次调用",
   "detail.calls": "调用",
   "detail.context_window": "上下文窗口",
   "detail.cost_usage_context": "成本、使用情况与上下文",
-  "detail.credit_confidence": "使用额度置信度",
-  "detail.credit_model": "使用额度模型",
-  "detail.credit_note": "使用额度说明",
-  "detail.credit_source": "使用额度来源",
-  "detail.credit_source_fetched": "使用额度来源获取时间",
-  "detail.credit_tier": "使用额度层级",
-  "detail.cwd": "西德",
+  "detail.credit_confidence": "点数映射置信度",
+  "detail.credit_model": "点数计费模型",
+  "detail.credit_note": "点数说明",
+  "detail.credit_source": "点数来源",
+  "detail.credit_source_fetched": "点数来源获取时间",
+  "detail.credit_tier": "点数档位",
+  "detail.cwd": "工作目录",
   "detail.efficiency_signals": "效率信号",
   "detail.first_expensive_turn": "首次高成本轮次",
-  "detail.git_branch": "git分支",
+  "detail.git_branch": "Git 分支",
   "detail.largest_cumulative_jump": "最大累计增幅",
   "detail.latest_activity": "最近活动",
   "detail.model_mix": "模型分布",
   "detail.next_action": "下一步操作",
   "detail.no_above_thresholds": "没有超过阈值的项目",
-  "detail.no_aggregate_action": "没有标记的汇总操作。",
+  "detail.no_aggregate_action": "未发现需要处理的聚合信号。",
   "detail.parent_session": "父会话",
   "detail.parent_thread": "父线程",
   "detail.parent_updated": "父级更新时间",
@@ -254,19 +254,19 @@
   "detail.project_cwd": "项目工作目录",
   "detail.project_tags": "项目标签",
   "detail.raw_identifiers": "原始汇总标识符",
-  "detail.reasoning_mix": "推理占比",
+  "detail.reasoning_mix": "推理强度分布",
   "detail.relationships": "关联关系",
   "detail.remote_hash": "远程哈希",
   "detail.remote_label": "远程标签",
   "detail.secondary_thread_fields": "辅助线程字段",
   "detail.source_file_line": "源文件与行号",
-  "detail.source_line": "源代码行",
-  "detail.spawned_child_calls": "生成的子调用",
+  "detail.source_line": "来源行号",
+  "detail.spawned_child_calls": "派生的子调用",
   "detail.spawned_from": "派生自",
-  "detail.spawned_threads": "生成的线程",
-  "detail.subagent_before_spike": "突增前的子 Agent",
-  "detail.subagent_calls": "子 Agent 调用",
-  "detail.subagent_type": "子 Agent 类型",
+  "detail.spawned_threads": "派生线程",
+  "detail.subagent_before_spike": "突增前的子智能体",
+  "detail.subagent_calls": "子智能体调用",
+  "detail.subagent_type": "子智能体类型",
   "detail.thread_attachment": "线程关联",
   "detail.thread_attention_summary": "线程关注度摘要",
   "detail.thread_lifecycle": "线程生命周期",
@@ -275,10 +275,10 @@
   "detail.thread_timeline": "线程时间线",
   "detail.timeline_context": "上下文 {value}",
   "detail.timeline_empty": "此线程中没有调用。",
-  "detail.timeline_meta": "{tokens} Token · {cost} · {credits} · 缓存 {cache}",
+  "detail.timeline_meta": "{tokens} 个token · {cost} · {credits} · 缓存 {cache}",
   "detail.timestamp": "时间戳",
-  "detail.token_pricing_breakdown": "Token 与定价明细",
-  "detail.tokens_at": "{time} 的 {tokens} Token",
+  "detail.token_pricing_breakdown": "token与定价明细",
+  "detail.tokens_at": "{time} 时为 {tokens} 个token",
   "detail.turn": "轮次",
   "detail.why_flagged": "标记原因",
   "docs.dashboard_guide": "仪表板指南",
@@ -298,12 +298,12 @@
   "filter.start": "开始",
   "filter.thread": "线程",
   "filter.time": "时间",
-  "flag.elevated_context_use": "提升上下文使用",
+  "flag.elevated_context_use": "上下文使用率偏高",
   "flag.expensive_low_output_call": "昂贵的低输出调用",
   "flag.high_context_use": "高上下文使用",
   "flag.high_estimated_cost": "预估成本高",
-  "flag.high_reasoning_share": "高推理分享",
-  "flag.low_cache_reuse": "缓存重用率低",
+  "flag.high_reasoning_share": "推理占比高",
+  "flag.low_cache_reuse": "缓存复用率低",
   "history.active_hidden": "仅显示活动会话；已隐藏 {count} 次归档调用",
   "history.active_only": "仅显示活动会话",
   "history.all_empty": "已选择所有历史记录；尚未索引归档调用",
@@ -311,62 +311,62 @@
   "history.archived_scan_hint": "{detail}。仅当在实时刷新期间选择“所有历史记录”时才会扫描已存档的会话。",
   "insight.apply_cache_misses": "应用缓存未命中预设",
   "insight.apply_context_bloat": "应用上下文膨胀预设",
-  "insight.codex_allowance_usage": "Codex 使用额度情况",
+  "insight.codex_allowance_usage": "Codex 使用限额情况",
   "insight.context_bloat": "上下文膨胀",
-  "insight.context_bloat_body": "{calls} 调用等于或高于 {ratio} 上下文使用。",
+  "insight.context_bloat_body": "有 {calls} 次调用的上下文使用率达到或超过 {ratio}。",
   "insight.costliest_thread": "成本最高的线程",
-  "insight.costliest_thread_body": "{thread} 有 {calls} 调用和 {tokens} Token。",
-  "insight.credit_coverage_body": "可见Token的 {ratio} 映射到 Codex 信用率。",
+  "insight.costliest_thread_body": "{thread} 包含 {calls} 次调用，共 {tokens} 个token。",
+  "insight.credit_coverage_body": "{ratio} 的可见token已匹配 Codex 点数费率。",
   "insight.estimated_pricing": "估算定价",
-  "insight.estimated_pricing_body": "包括标记的最佳猜测价格，但应单独审查。",
+  "insight.estimated_pricing_body": "已包含明确标注的推测价格，但应单独审查。",
   "insight.inspect_selected_call": "查看所选调用",
   "insight.low_cache_reuse": "缓存复用率低",
-  "insight.low_cache_reuse_body": "{calls} 调用在 {ratio} 缓存重用下。从 {thread} 开始。",
+  "insight.low_cache_reuse_body": "有 {calls} 次调用的缓存复用率低于 {ratio}；可先查看 {thread}。",
   "insight.open_thread_timeline": "打开线程时间线",
   "insight.reasoning_output_spike": "推理输出突增",
-  "insight.reasoning_spike_body": "{thread} 在当前过滤器中具有最大的推理输出调用。",
+  "insight.reasoning_spike_body": "在当前筛选结果中，{thread} 包含推理输出最大的调用。",
   "insight.review_estimates": "审查估算",
-  "insight.review_highest_credit": "审查使用额度最高的调用",
+  "insight.review_highest_credit": "审查点数最高的调用",
   "insight.review_pricing_gaps": "审查定价缺口",
   "insight.unpriced_usage": "未定价使用情况",
-  "insight.unpriced_usage_body": "在配置定价之前，这些Token将从估计成本总额中省略。",
+  "insight.unpriced_usage_body": "配置定价前，这些token不会计入估算成本总额。",
   "language.english": "英语",
   "language.label": "语言",
-  "language.vietnamese": "越南",
+  "language.vietnamese": "越南语",
   "live.checking_usage": "正在检查新的使用记录…",
   "live.every": "每 {seconds} 秒实时刷新一次",
-  "live.history_static_hint": "运行 codex-usage-tracker serve-dashboard 在活动会话和仪表板中的所有历史记录之间切换。",
-  "live.indexed": "索引 {rows} 聚合 {files} 日志中的行。",
-  "live.load_static_hint": "运行 codex-usage-tracker serve-dashboard 从仪表板加载不同的历史记录大小。",
+  "live.history_static_hint": "运行 codex-usage-tracker serve-dashboard，即可在仪表板中切换活动会话与所有历史记录。",
+  "live.indexed": "已从 {files} 个日志文件中索引 {rows} 条聚合记录。",
+  "live.load_static_hint": "运行 codex-usage-tracker serve-dashboard，即可在仪表板中调整加载的历史记录数量。",
   "live.loading_rows": "正在后台加载行…",
   "live.paused": "实时刷新已暂停",
   "live.refresh_suffix": "。重新生成静态仪表板后重新加载此页面，或运行 codex-usage-tracker serve-dashboard。",
   "live.refresh_unavailable": "实时刷新不可用：{message}{suffix}",
   "live.refreshing_index": "正在刷新本地使用索引…",
   "live.reloading_static": "正在重新加载静态仪表板快照…",
-  "live.skipped": "已跳过 {count} 条格式错误的 Token 计数事件。",
+  "live.skipped": "已跳过 {count} 条格式错误的token计数事件。",
   "live.updated_detail": "已更新 {time}。{loaded}。{history}。{indexed}{skipped}",
   "metric.attention_score": "关注度评分",
   "metric.cache_ratio": "缓存复用率",
   "metric.cache_trend": "缓存趋势",
   "metric.cached_input": "缓存输入",
-  "metric.codex_credits": "Codex 使用额度",
+  "metric.codex_credits": "Codex 点数",
   "metric.context_trend": "上下文趋势",
   "metric.context_use": "上下文使用率",
   "metric.estimated_cost": "估算成本",
-  "metric.input_tokens": "输入 Token",
+  "metric.input_tokens": "输入token",
   "metric.last_call_input": "上次调用输入",
   "metric.last_call_total": "上次调用总量",
   "metric.max_context_use": "最大上下文使用率",
   "metric.output": "输出",
-  "metric.output_tokens": "输出 Token",
-  "metric.reasoning_output": "推理输出 Token",
+  "metric.output_tokens": "输出token",
+  "metric.reasoning_output": "推理输出token",
   "metric.remaining_usage": "剩余使用额度",
   "metric.session_cumulative": "会话累计",
   "metric.total": "总计",
-  "metric.total_tokens": "Token 总数",
+  "metric.total_tokens": "token总数",
   "metric.uncached_input": "未缓存输入",
-  "metric.usage_credits": "使用额度",
+  "metric.usage_credits": "使用点数",
   "metric.usage_observed": "已观测的使用情况",
   "metric.usage_remaining": "剩余使用额度",
   "metric.visible_calls": "当前显示的调用",
@@ -381,10 +381,10 @@
   "option.all_time": "全部时间",
   "option.custom_range": "自定义范围",
   "option.estimated_cost": "估算成本",
-  "option.estimated_credit_mapping": "估算使用额度映射",
+  "option.estimated_credit_mapping": "估算点数映射",
   "option.exact_cost": "精确成本",
-  "option.exact_credit_rate": "精确使用额度费率",
-  "option.highest_codex_credits": "Codex 使用额度最高",
+  "option.exact_credit_rate": "精确点数费率",
+  "option.highest_codex_credits": "Codex 点数最高",
   "option.highest_context_use": "上下文使用率最高",
   "option.highest_estimated_cost": "估算成本最高",
   "option.last_7_days": "过去 7 天",
@@ -395,9 +395,9 @@
   "option.longest_duration": "耗时最长",
   "option.longest_gap": "间隔最长",
   "option.lowest_cache_ratio": "缓存复用率最低",
-  "option.missing_credit_rate": "缺少使用额度费率",
+  "option.missing_credit_rate": "缺少点数费率",
   "option.most_signals": "信号最多",
-  "option.most_tokens": "Token 最多",
+  "option.most_tokens": "token最多",
   "option.needs_attention": "需要关注",
   "option.newest_calls": "最新调用",
   "option.this_month": "本月",
@@ -405,25 +405,25 @@
   "option.thread_name": "线程名称",
   "option.today": "今天",
   "option.unpriced_cost": "未定价成本",
-  "option.user_credit_override": "用户覆盖使用额度",
+  "option.user_credit_override": "用户自定义点数费率",
   "parser.warnings_title": "最新刷新报告了 {count} 解析器诊断：{entries}。运行 codex-usage-tracker inspect-log <path> 以调查架构漂移。",
   "preset.cache_misses": "缓存未命中",
   "preset.cache_misses_caption": "缓存未命中预设",
-  "preset.cache_misses_desc": "按 cwd、模型和线程分组的低缓存比率调用。",
+  "preset.cache_misses_desc": "按工作目录、模型和线程分组的低缓存复用率调用。",
   "preset.caption": "{caption}：{description}",
   "preset.context_bloat": "上下文膨胀",
   "preset.context_bloat_caption": "上下文膨胀预设",
-  "preset.context_bloat_desc": "调用超过 60% 的上下文使用或具有非常高的累积标记。",
+  "preset.context_bloat_desc": "上下文使用率超过 60% 或累计token数极高的调用。",
   "preset.description": "常见使用问题的一键起点。",
   "preset.estimated_price_review": "估算价格审查",
   "preset.estimated_price_review_caption": "估算价格审查预设",
-  "preset.estimated_price_review_desc": "使用量的定价带有标记的最佳猜测估计。",
-  "preset.highest_codex_credits": "Codex 使用额度最高",
-  "preset.highest_codex_credits_caption": "Codex 使用额度最高预设",
+  "preset.estimated_price_review_desc": "使用量采用已明确标注的推测性估算价格。",
+  "preset.highest_codex_credits": "Codex 点数最高",
+  "preset.highest_codex_credits_caption": "Codex 点数最高预设",
   "preset.highest_codex_credits_desc": "调用按对 Codex 使用限额的估计影响排序。",
   "preset.highest_cost_threads": "成本最高的线程",
   "preset.highest_cost_threads_caption": "成本最高的线程预设",
-  "preset.highest_cost_threads_desc": "主题按预计支出排序，并附加子代理。",
+  "preset.highest_cost_threads_desc": "线程按估算支出排序，并计入关联的子智能体调用。",
   "preset.investigation_presets": "调查预设",
   "preset.no_preset": "未应用预设。",
   "preset.pricing_gaps": "定价缺口",
@@ -431,51 +431,51 @@
   "preset.pricing_gaps_desc": "未定价的使用导致估计成本总计不完整。",
   "pricing.configure_hint": "运行 codex-usage-tracker update-pricing 以配置估计成本。",
   "pricing.fetched": "已获取 {time}",
-  "pricing.pinned": "固定快照",
+  "pricing.pinned": "固定版本快照",
   "pricing.source": "定价来源",
   "pricing.tier": "{tier} 层",
-  "pricing.title": "{parts}。内部 Codex 标签可以使用标记的最佳猜测估计。{warning}",
-  "pricing.title_fetched": "{parts}。从 {url} 的 {time} 获取。内部 Codex 标签可以使用标记的最佳猜测估计。{warning}",
-  "privacy.aliases_preserved": "配置的项目别名被视为显式显示选择。",
-  "privacy.cwd_redacted": "原始 cwd 路径已被编辑。",
+  "pricing.title": "{parts}。内部 Codex 标签可能使用已明确标注的推测性估算。{warning}",
+  "pricing.title_fetched": "{parts}。于 {time} 从 {url} 获取。内部 Codex 标签可能使用已明确标注的推测性估算。{warning}",
+  "privacy.aliases_preserved": "已配置的项目别名视为用户明确同意显示。",
+  "privacy.cwd_redacted": "原始工作目录路径已脱敏。",
   "privacy.git_branch_hidden": "Git 分支被隐藏。",
   "privacy.git_remote_label_hidden": "Git 远程标签被隐藏。",
   "privacy.mode": "项目元数据隐私模式：{mode}。",
-  "privacy.normal_title": "项目元数据显示为本地 cwd、项目、分支和配置的标签。",
+  "privacy.normal_title": "项目元数据显示本地工作目录、项目、分支和已配置标签。",
   "privacy.project_names_redacted": "未命名的项目使用稳定的散列标签。",
-  "privacy.relative_cwd_hidden": "相对 cwd 被隐藏。",
+  "privacy.relative_cwd_hidden": "相对工作目录已隐藏。",
   "privacy.tags_hidden": "项目标签被隐藏。",
   "recommendation.context_bloat.action": "如果旧的上下文不再相关，请考虑启动一个新的 Codex 线程。",
-  "recommendation.context_bloat.title": "高情境压力",
+  "recommendation.context_bloat.title": "上下文压力过高",
   "recommendation.context_bloat.why": "此调用使用了模型上下文窗口的很大一部分。",
-  "recommendation.elevated_context.action": "在添加更多工作之前检查是否可以缩小线程。",
-  "recommendation.elevated_context.title": "环境压力升高",
-  "recommendation.elevated_context.why": "上下文的使用会增加，并且在以后的回合中可能会变得昂贵。",
-  "recommendation.estimated_pricing.action": "如果此调用很重要，请查看定价范围并固定或覆盖模型费率。",
-  "recommendation.estimated_pricing.title": "预计定价",
-  "recommendation.estimated_pricing.why": "此成本使用推断模型映射而不是直接定价行。",
+  "recommendation.elevated_context.action": "继续添加工作前，检查能否收窄任务范围。",
+  "recommendation.elevated_context.title": "上下文压力偏高",
+  "recommendation.elevated_context.why": "上下文使用率偏高，后续轮次的成本可能继续上升。",
+  "recommendation.estimated_pricing.action": "检查定价覆盖情况；若此调用很重要，请固定或覆盖模型费率。",
+  "recommendation.estimated_pricing.title": "估算定价",
+  "recommendation.estimated_pricing.why": "此成本基于推断的模型映射，而非直接定价条目。",
   "recommendation.high_cost.action": "打开线程时间线并检查前一回合，然后再继续。",
   "recommendation.high_cost.title": "预估成本高",
   "recommendation.high_cost.why": "此调用超出了配置的高成本阈值。",
-  "recommendation.large_thread.action": "更喜欢使用新线程来进行不相关的后续工作。",
-  "recommendation.large_thread.title": "大累积线程",
-  "recommendation.large_thread.why": "会话累计总数足够高，使得后面的轮次变得昂贵。",
-  "recommendation.low_cache.action": "检查是否不必要地重新引入了文件、工具输出或广泛上下文。",
-  "recommendation.low_cache.title": "缓存重用率低",
-  "recommendation.low_cache.why": "新鲜的未缓存输入较高，而缓存重用率较低。",
+  "recommendation.large_thread.action": "无关的后续工作建议新开线程。",
+  "recommendation.large_thread.title": "线程累计用量过高",
+  "recommendation.large_thread.why": "会话累计用量较高，可能使后续轮次成本上升。",
+  "recommendation.low_cache.action": "检查是否无意中重复引入文件、工具输出或过宽的上下文。",
+  "recommendation.low_cache.title": "缓存复用率低",
+  "recommendation.low_cache.why": "新增的未缓存输入量较高，而缓存复用率较低。",
   "recommendation.low_output.action": "首先检查聚合上下文；仅当原因不清楚时才加载原始上下文。",
-  "recommendation.low_output.title": "大低输出调用",
-  "recommendation.low_output.why": "该调用消耗了很多Token，但产生的输出很少。",
-  "recommendation.none.action": "没有标记聚合操作；继续监控使用模式。",
-  "recommendation.pricing_gap.action": "在信任成本总计之前更新定价或添加本地别名。",
-  "recommendation.pricing_gap.title": "定价差距",
+  "recommendation.low_output.title": "高耗用、低输出调用",
+  "recommendation.low_output.why": "该调用消耗了大量token，但输出很少。",
+  "recommendation.none.action": "未发现需处理的聚合信号；请继续监控用量模式。",
+  "recommendation.pricing_gap.action": "更新定价或添加本地别名后，再采用成本汇总。",
+  "recommendation.pricing_gap.title": "定价缺口",
   "recommendation.pricing_gap.why": "此模型调用没有配置价格，因此成本总计低估了可见使用情况。",
-  "recommendation.reasoning_spike.action": "检查此任务是否需要所选的推理工作。",
-  "recommendation.reasoning_spike.title": "高推理分享",
+  "recommendation.reasoning_spike.action": "检查此任务是否需要当前所选的推理强度。",
+  "recommendation.reasoning_spike.title": "推理占比高",
   "recommendation.reasoning_spike.why": "推理输出在该调用的可见输出中占主导地位。",
-  "recommendation.subagent_attribution.action": "将直接调用与附加的子座席进行比较，或在更改工作流程之前审核调用。",
-  "recommendation.subagent_attribution.title": "子代理归因",
-  "recommendation.subagent_attribution.why": "此调用附加到委派工作，并且可以解释父线程的增长。",
+  "recommendation.subagent_attribution.action": "调整工作流前，先比较直接调用与关联的子智能体调用或审查调用。",
+  "recommendation.subagent_attribution.title": "子智能体归因",
+  "recommendation.subagent_attribution.why": "此调用属于委派任务，可能解释父线程的增长。",
   "section.allowance": "使用限额",
   "section.needs_attention": "需要关注",
   "section.pricing": "定价",
@@ -485,13 +485,13 @@
   "severity.review": "需审查",
   "source.auto_review": "自动审查",
   "source.codex_initiated": "由 Codex 发起",
-  "source.subagent": "子 Agent",
-  "source.subagent_role": "子 Agent：{role}",
+  "source.subagent": "子智能体",
+  "source.subagent_role": "子智能体：{role}",
   "source.user": "用户",
   "source.user_initiated": "由用户发起",
   "state.allowance_config_error": "使用限额配置错误",
   "state.allowance_configured": "已配置使用限额",
-  "state.best_guess_estimate": "最佳猜测估算",
+  "state.best_guess_estimate": "推测性估算",
   "state.configured": "已配置",
   "state.configured_price": "已配置价格",
   "state.error": "错误",
@@ -533,7 +533,7 @@
   "table.more_efforts": "{effort} +{count} 种推理强度",
   "table.more_models": "{model} +{count} 个模型",
   "table.output": "输出",
-  "table.page_status": "{total} {items} 的 {start}-{end} · 页 {page}/{pages}",
+  "table.page_status": "{items}：第 {start}–{end} 项，共 {total} 项 · 第 {page}/{pages} 页",
   "table.previous_gap": "与上次间隔",
   "table.rows": "行",
   "table.signals": "信号",
@@ -541,9 +541,9 @@
   "table.thread": "线程",
   "table.threads": "线程",
   "table.time": "时间",
-  "table.tokens": "Token",
+  "table.tokens": "token",
   "table.uncached": "未缓存输入",
-  "table.visible_status": "显示 {total} {items} 的 {end}",
+  "table.visible_status": "{items}：已显示 {end}/{total} 项",
   "thread.attached": "已关联",
   "thread.attention": "关注度 {score}",
   "thread.auto_review": "{count} 次自动审查",
@@ -551,14 +551,14 @@
   "thread.direct": "直接",
   "thread.expand": "展开",
   "thread.expand_label": "{action} {thread} 的调用。关注度评分 {score}。",
-  "thread.explicit_parent": "显式父级",
-  "thread.explicit_parent_thread": "显式父线程",
+  "thread.explicit_parent": "已明确指定父级",
+  "thread.explicit_parent_thread": "已明确指定父线程",
   "thread.parent": "父级 {id}",
   "thread.session": "会话",
   "thread.spawned": "已派生",
   "thread.spawned_from": "派生自 {thread}",
   "thread.spawned_threads": "{count} 个派生线程",
-  "thread.subagent": "{count} 个子 Agent",
+  "thread.subagent": "{count} 个子智能体",
   "thread.unknown": "未知线程",
-  "thread.unmatched_subagent": "未匹配的子 Agent"
+  "thread.unmatched_subagent": "未匹配的子智能体"
 }
diff --git a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/App.js b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/App.js
index 44255a0c..b318831c 100644
--- a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/App.js
+++ b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/App.js
@@ -1,133 +1,133 @@
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+var Za=e=>{throw TypeError(e)};var Gt=(e,t,a)=>t.has(e)||Za("Cannot "+a);var d=(e,t,a)=>(Gt(e,t,"read from private field"),a?a.call(e):t.get(e)),A=(e,t,a)=>t.has(e)?Za("Cannot add the same private member more than once"):t instanceof WeakSet?t.add(e):t.set(e,a),S=(e,t,a,n)=>(Gt(e,t,"write to private field"),n?n.call(e,a):t.set(e,a),a),V=(e,t,a)=>(Gt(e,t,"access private method"),a);var St=(e,t,a,n)=>({set _(r){S(e,t,r,a)},get _(){return d(e,t,n)}});import{r as C,j as c,_ as U}from"./dashboard-react.js";import{i as Ps}from"./dashboardRouter.js";import{a9 as ie}from"./router.js";/**
  * @license lucide-react v0.468.0 - ISC
  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
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+ */const Ns=e=>e.replace(/([a-z0-9])([A-Z])/g,"$1-$2").toLowerCase(),zn=(...e)=>e.filter((t,a,n)=>!!t&&t.trim()!==""&&n.indexOf(t)===a).join(" ").trim();/**
  * @license lucide-react v0.468.0 - ISC
  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */var fs={xmlns:"http://www.w3.org/2000/svg",width:24,height:24,viewBox:"0 0 24 24",fill:"none",stroke:"currentColor",strokeWidth:2,strokeLinecap:"round",strokeLinejoin:"round"};/**
+ */var Es={xmlns:"http://www.w3.org/2000/svg",width:24,height:24,viewBox:"0 0 24 24",fill:"none",stroke:"currentColor",strokeWidth:2,strokeLinecap:"round",strokeLinejoin:"round"};/**
  * @license lucide-react v0.468.0 - ISC
  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const ms=C.forwardRef(({color:e="currentColor",size:t=24,strokeWidth:a=2,absoluteStrokeWidth:n,className:r="",children:s,iconNode:i,...c},f)=>C.createElement("svg",{ref:f,...fs,width:t,height:t,stroke:e,strokeWidth:n?Number(a)*24/Number(t):a,className:Rn("lucide",r),...c},[...i.map(([m,d])=>C.createElement(m,d)),...Array.isArray(s)?s:[s]]));/**
+ */const Is=C.forwardRef(({color:e="currentColor",size:t=24,strokeWidth:a=2,absoluteStrokeWidth:n,className:r="",children:s,iconNode:i,...o},u)=>C.createElement("svg",{ref:u,...Es,width:t,height:t,stroke:e,strokeWidth:n?Number(a)*24/Number(t):a,className:zn("lucide",r),...o},[...i.map(([p,h])=>C.createElement(p,h)),...Array.isArray(s)?s:[s]]));/**
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  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const I=(e,t)=>{const a=C.forwardRef(({className:n,...r},s)=>C.createElement(ms,{ref:s,iconNode:t,className:Rn(`lucide-${hs(e)}`,n),...r}));return a.displayName=`${e}`,a};/**
+ */const O=(e,t)=>{const a=C.forwardRef(({className:n,...r},s)=>C.createElement(Is,{ref:s,iconNode:t,className:zn(`lucide-${Ns(e)}`,n),...r}));return a.displayName=`${e}`,a};/**
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+ */const js=O("Activity",[["path",{d:"M22 12h-2.48a2 2 0 0 0-1.93 1.46l-2.35 8.36a.25.25 0 0 1-.48 0L9.24 2.18a.25.25 0 0 0-.48 0l-2.35 8.36A2 2 0 0 1 4.49 12H2",key:"169zse"}]]);/**
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  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const ps=I("ArrowUp",[["path",{d:"m5 12 7-7 7 7",key:"hav0vg"}],["path",{d:"M12 19V5",key:"x0mq9r"}]]);/**
+ */const Ds=O("ArrowUp",[["path",{d:"m5 12 7-7 7 7",key:"hav0vg"}],["path",{d:"M12 19V5",key:"x0mq9r"}]]);/**
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+ */const Os=O("BookOpen",[["path",{d:"M12 7v14",key:"1akyts"}],["path",{d:"M3 18a1 1 0 0 1-1-1V4a1 1 0 0 1 1-1h5a4 4 0 0 1 4 4 4 4 0 0 1 4-4h5a1 1 0 0 1 1 1v13a1 1 0 0 1-1 1h-6a3 3 0 0 0-3 3 3 3 0 0 0-3-3z",key:"ruj8y"}]]);/**
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  * This source code is licensed under the ISC license.
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- */const bs=I("Boxes",[["path",{d:"M2.97 12.92A2 2 0 0 0 2 14.63v3.24a2 2 0 0 0 .97 1.71l3 1.8a2 2 0 0 0 2.06 0L12 19v-5.5l-5-3-4.03 2.42Z",key:"lc1i9w"}],["path",{d:"m7 16.5-4.74-2.85",key:"1o9zyk"}],["path",{d:"m7 16.5 5-3",key:"va8pkn"}],["path",{d:"M7 16.5v5.17",key:"jnp8gn"}],["path",{d:"M12 13.5V19l3.97 2.38a2 2 0 0 0 2.06 0l3-1.8a2 2 0 0 0 .97-1.71v-3.24a2 2 0 0 0-.97-1.71L17 10.5l-5 3Z",key:"8zsnat"}],["path",{d:"m17 16.5-5-3",key:"8arw3v"}],["path",{d:"m17 16.5 4.74-2.85",key:"8rfmw"}],["path",{d:"M17 16.5v5.17",key:"k6z78m"}],["path",{d:"M7.97 4.42A2 2 0 0 0 7 6.13v4.37l5 3 5-3V6.13a2 2 0 0 0-.97-1.71l-3-1.8a2 2 0 0 0-2.06 0l-3 1.8Z",key:"1xygjf"}],["path",{d:"M12 8 7.26 5.15",key:"1vbdud"}],["path",{d:"m12 8 4.74-2.85",key:"3rx089"}],["path",{d:"M12 13.5V8",key:"1io7kd"}]]);/**
+ */const Fs=O("Boxes",[["path",{d:"M2.97 12.92A2 2 0 0 0 2 14.63v3.24a2 2 0 0 0 .97 1.71l3 1.8a2 2 0 0 0 2.06 0L12 19v-5.5l-5-3-4.03 2.42Z",key:"lc1i9w"}],["path",{d:"m7 16.5-4.74-2.85",key:"1o9zyk"}],["path",{d:"m7 16.5 5-3",key:"va8pkn"}],["path",{d:"M7 16.5v5.17",key:"jnp8gn"}],["path",{d:"M12 13.5V19l3.97 2.38a2 2 0 0 0 2.06 0l3-1.8a2 2 0 0 0 .97-1.71v-3.24a2 2 0 0 0-.97-1.71L17 10.5l-5 3Z",key:"8zsnat"}],["path",{d:"m17 16.5-5-3",key:"8arw3v"}],["path",{d:"m17 16.5 4.74-2.85",key:"8rfmw"}],["path",{d:"M17 16.5v5.17",key:"k6z78m"}],["path",{d:"M7.97 4.42A2 2 0 0 0 7 6.13v4.37l5 3 5-3V6.13a2 2 0 0 0-.97-1.71l-3-1.8a2 2 0 0 0-2.06 0l-3 1.8Z",key:"1xygjf"}],["path",{d:"M12 8 7.26 5.15",key:"1vbdud"}],["path",{d:"m12 8 4.74-2.85",key:"3rx089"}],["path",{d:"M12 13.5V8",key:"1io7kd"}]]);/**
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  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const ws=I("BrainCircuit",[["path",{d:"M12 5a3 3 0 1 0-5.997.125 4 4 0 0 0-2.526 5.77 4 4 0 0 0 .556 6.588A4 4 0 1 0 12 18Z",key:"l5xja"}],["path",{d:"M9 13a4.5 4.5 0 0 0 3-4",key:"10igwf"}],["path",{d:"M6.003 5.125A3 3 0 0 0 6.401 6.5",key:"105sqy"}],["path",{d:"M3.477 10.896a4 4 0 0 1 .585-.396",key:"ql3yin"}],["path",{d:"M6 18a4 4 0 0 1-1.967-.516",key:"2e4loj"}],["path",{d:"M12 13h4",key:"1ku699"}],["path",{d:"M12 18h6a2 2 0 0 1 2 2v1",key:"105ag5"}],["path",{d:"M12 8h8",key:"1lhi5i"}],["path",{d:"M16 8V5a2 2 0 0 1 2-2",key:"u6izg6"}],["circle",{cx:"16",cy:"13",r:".5",key:"ry7gng"}],["circle",{cx:"18",cy:"3",r:".5",key:"1aiba7"}],["circle",{cx:"20",cy:"21",r:".5",key:"yhc1fs"}],["circle",{cx:"20",cy:"8",r:".5",key:"1e43v0"}]]);/**
+ */const Us=O("BrainCircuit",[["path",{d:"M12 5a3 3 0 1 0-5.997.125 4 4 0 0 0-2.526 5.77 4 4 0 0 0 .556 6.588A4 4 0 1 0 12 18Z",key:"l5xja"}],["path",{d:"M9 13a4.5 4.5 0 0 0 3-4",key:"10igwf"}],["path",{d:"M6.003 5.125A3 3 0 0 0 6.401 6.5",key:"105sqy"}],["path",{d:"M3.477 10.896a4 4 0 0 1 .585-.396",key:"ql3yin"}],["path",{d:"M6 18a4 4 0 0 1-1.967-.516",key:"2e4loj"}],["path",{d:"M12 13h4",key:"1ku699"}],["path",{d:"M12 18h6a2 2 0 0 1 2 2v1",key:"105ag5"}],["path",{d:"M12 8h8",key:"1lhi5i"}],["path",{d:"M16 8V5a2 2 0 0 1 2-2",key:"u6izg6"}],["circle",{cx:"16",cy:"13",r:".5",key:"ry7gng"}],["circle",{cx:"18",cy:"3",r:".5",key:"1aiba7"}],["circle",{cx:"20",cy:"21",r:".5",key:"yhc1fs"}],["circle",{cx:"20",cy:"8",r:".5",key:"1e43v0"}]]);/**
  * @license lucide-react v0.468.0 - ISC
  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const ys=I("ChartColumn",[["path",{d:"M3 3v16a2 2 0 0 0 2 2h16",key:"c24i48"}],["path",{d:"M18 17V9",key:"2bz60n"}],["path",{d:"M13 17V5",key:"1frdt8"}],["path",{d:"M8 17v-3",key:"17ska0"}]]);/**
+ */const Hs=O("ChartColumn",[["path",{d:"M3 3v16a2 2 0 0 0 2 2h16",key:"c24i48"}],["path",{d:"M18 17V9",key:"2bz60n"}],["path",{d:"M13 17V5",key:"1frdt8"}],["path",{d:"M8 17v-3",key:"17ska0"}]]);/**
  * @license lucide-react v0.468.0 - ISC
  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const sa=I("Copy",[["rect",{width:"14",height:"14",x:"8",y:"8",rx:"2",ry:"2",key:"17jyea"}],["path",{d:"M4 16c-1.1 0-2-.9-2-2V4c0-1.1.9-2 2-2h10c1.1 0 2 .9 2 2",key:"zix9uf"}]]);/**
+ */const ma=O("Copy",[["rect",{width:"14",height:"14",x:"8",y:"8",rx:"2",ry:"2",key:"17jyea"}],["path",{d:"M4 16c-1.1 0-2-.9-2-2V4c0-1.1.9-2 2-2h10c1.1 0 2 .9 2 2",key:"zix9uf"}]]);/**
  * @license lucide-react v0.468.0 - ISC
  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const _s=I("Database",[["ellipse",{cx:"12",cy:"5",rx:"9",ry:"3",key:"msslwz"}],["path",{d:"M3 5V19A9 3 0 0 0 21 19V5",key:"1wlel7"}],["path",{d:"M3 12A9 3 0 0 0 21 12",key:"mv7ke4"}]]);/**
+ */const Vs=O("Database",[["ellipse",{cx:"12",cy:"5",rx:"9",ry:"3",key:"msslwz"}],["path",{d:"M3 5V19A9 3 0 0 0 21 19V5",key:"1wlel7"}],["path",{d:"M3 12A9 3 0 0 0 21 12",key:"mv7ke4"}]]);/**
  * @license lucide-react v0.468.0 - ISC
  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const Ss=I("Download",[["path",{d:"M21 15v4a2 2 0 0 1-2 2H5a2 2 0 0 1-2-2v-4",key:"ih7n3h"}],["polyline",{points:"7 10 12 15 17 10",key:"2ggqvy"}],["line",{x1:"12",x2:"12",y1:"15",y2:"3",key:"1vk2je"}]]);/**
+ */const Ks=O("Download",[["path",{d:"M21 15v4a2 2 0 0 1-2 2H5a2 2 0 0 1-2-2v-4",key:"ih7n3h"}],["polyline",{points:"7 10 12 15 17 10",key:"2ggqvy"}],["line",{x1:"12",x2:"12",y1:"15",y2:"3",key:"1vk2je"}]]);/**
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  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const Cs=I("FileText",[["path",{d:"M15 2H6a2 2 0 0 0-2 2v16a2 2 0 0 0 2 2h12a2 2 0 0 0 2-2V7Z",key:"1rqfz7"}],["path",{d:"M14 2v4a2 2 0 0 0 2 2h4",key:"tnqrlb"}],["path",{d:"M10 9H8",key:"b1mrlr"}],["path",{d:"M16 13H8",key:"t4e002"}],["path",{d:"M16 17H8",key:"z1uh3a"}]]);/**
+ */const qs=O("FileText",[["path",{d:"M15 2H6a2 2 0 0 0-2 2v16a2 2 0 0 0 2 2h12a2 2 0 0 0 2-2V7Z",key:"1rqfz7"}],["path",{d:"M14 2v4a2 2 0 0 0 2 2h4",key:"tnqrlb"}],["path",{d:"M10 9H8",key:"b1mrlr"}],["path",{d:"M16 13H8",key:"t4e002"}],["path",{d:"M16 17H8",key:"z1uh3a"}]]);/**
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  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const xs=I("Filter",[["polygon",{points:"22 3 2 3 10 12.46 10 19 14 21 14 12.46 22 3",key:"1yg77f"}]]);/**
+ */const zs=O("Filter",[["polygon",{points:"22 3 2 3 10 12.46 10 19 14 21 14 12.46 22 3",key:"1yg77f"}]]);/**
  * @license lucide-react v0.468.0 - ISC
  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const ks=I("FlaskConical",[["path",{d:"M14 2v6a2 2 0 0 0 .245.96l5.51 10.08A2 2 0 0 1 18 22H6a2 2 0 0 1-1.755-2.96l5.51-10.08A2 2 0 0 0 10 8V2",key:"18mbvz"}],["path",{d:"M6.453 15h11.094",key:"3shlmq"}],["path",{d:"M8.5 2h7",key:"csnxdl"}]]);/**
+ */const Ws=O("FlaskConical",[["path",{d:"M14 2v6a2 2 0 0 0 .245.96l5.51 10.08A2 2 0 0 1 18 22H6a2 2 0 0 1-1.755-2.96l5.51-10.08A2 2 0 0 0 10 8V2",key:"18mbvz"}],["path",{d:"M6.453 15h11.094",key:"3shlmq"}],["path",{d:"M8.5 2h7",key:"csnxdl"}]]);/**
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  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const Ls=I("House",[["path",{d:"M15 21v-8a1 1 0 0 0-1-1h-4a1 1 0 0 0-1 1v8",key:"5wwlr5"}],["path",{d:"M3 10a2 2 0 0 1 .709-1.528l7-5.999a2 2 0 0 1 2.582 0l7 5.999A2 2 0 0 1 21 10v9a2 2 0 0 1-2 2H5a2 2 0 0 1-2-2z",key:"1d0kgt"}]]);/**
+ */const Bs=O("House",[["path",{d:"M15 21v-8a1 1 0 0 0-1-1h-4a1 1 0 0 0-1 1v8",key:"5wwlr5"}],["path",{d:"M3 10a2 2 0 0 1 .709-1.528l7-5.999a2 2 0 0 1 2.582 0l7 5.999A2 2 0 0 1 21 10v9a2 2 0 0 1-2 2H5a2 2 0 0 1-2-2z",key:"1d0kgt"}]]);/**
  * @license lucide-react v0.468.0 - ISC
  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const Rs=I("RefreshCw",[["path",{d:"M3 12a9 9 0 0 1 9-9 9.75 9.75 0 0 1 6.74 2.74L21 8",key:"v9h5vc"}],["path",{d:"M21 3v5h-5",key:"1q7to0"}],["path",{d:"M21 12a9 9 0 0 1-9 9 9.75 9.75 0 0 1-6.74-2.74L3 16",key:"3uifl3"}],["path",{d:"M8 16H3v5",key:"1cv678"}]]);/**
+ */const Gs=O("RefreshCw",[["path",{d:"M3 12a9 9 0 0 1 9-9 9.75 9.75 0 0 1 6.74 2.74L21 8",key:"v9h5vc"}],["path",{d:"M21 3v5h-5",key:"1q7to0"}],["path",{d:"M21 12a9 9 0 0 1-9 9 9.75 9.75 0 0 1-6.74-2.74L3 16",key:"3uifl3"}],["path",{d:"M8 16H3v5",key:"1cv678"}]]);/**
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  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const Mn=I("Search",[["circle",{cx:"11",cy:"11",r:"8",key:"4ej97u"}],["path",{d:"m21 21-4.3-4.3",key:"1qie3q"}]]);/**
+ */const Wn=O("Search",[["circle",{cx:"11",cy:"11",r:"8",key:"4ej97u"}],["path",{d:"m21 21-4.3-4.3",key:"1qie3q"}]]);/**
  * @license lucide-react v0.468.0 - ISC
  *
  * This source code is licensed under the ISC license.
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e.include_archived=="boolean"?e.include_archived?"all":"active":e.history_scope==="all-history"||e.history_scope==="all"?"all":e.history_scope==="active"?"active":t:t}function Qi({historyScope:e,activeRows:t,allRows:a,archivedRows:n}){const r=Hi({activeRows:t,allRows:a,archivedRows:n});return e==="all"?r===null?"All history selected":r>0?`All history includes ${r.toLocaleString()} archived calls`:"All history selected; no archived calls are indexed yet":r===null||r<=0?"Active sessions only":`Active sessions only; ${r.toLocaleString()} archived calls hidden`}function Hi({activeRows:e,allRows:t,archivedRows:a}){const n=Bt(a);if(n!==null)return n;const r=Bt(e),s=Bt(t);return r!==null&&s!==null?Math.max(s-r,0):null}function Bt(e){return typeof e=="number"&&Number.isFinite(e)&&e>=0?Math.round(e):null}const Tt=["May 12","May 19","May 26","Jun 02","Jun 09","Jun 16","Jun 23","Jun 30"],it=Tt.slice(2),Jn={contextRuntime:{apiToken:"",contextApiEnabled:!1,fileMode:!1},cards:[{label:"Total 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observed",color:"#2563eb",points:Tt.map((e,t)=>({label:e,value:[59800,44900,45e3,40500,42800,38900,31400,35900][t]??0,low:[52100,38800,38900,34700,36200,32200,26100,29900][t]??0,high:[67400,51200,51100,46800,49200,45100,37300,41900][t]??0}))},H("pro-trend","Pro trend","#1d4ed8",[54.2,51,47.8,44.6,41.4,38.2,35,31.8],1e3,!0),H("prolite","Prolite observed","#0f766e",[15.9,15.8,15.9,16.1,15.7,15.6,15.9,15.8],1e3)],usageRemainingSeries:[H("remaining","Usage remaining","#059669",[87,71,63,56,56,48,50,54]),H("allowance","Allowance guide","#0f766e",[86,85,84,83,82,81,80,79],1,!0)],actualVsPredictedSeries:[H("observed","Observed drain","#2563eb",[18.7,22.1,45.3,31,34.8],1e3),H("predicted","Predicted baseline","#1d4ed8",[17.9,21.4,41.2,29.6,33.9],1e3,!0)],findings:[{rank:1,title:"Long Thread: data-engine-refactor",severity:"High",credits:12847,share:25.6,summary:"Very long duration with high model effort."},{rank:2,title:"Cache Misses (Large 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as a8,An as a9,Us as aa,Vs as ab,zt as ac,Tn as ad,ni as ae,Hs as af,vl as ag,_l as ah,xt as ai,rn as aj,Me as ak,Il as al,sa as b,I as c,xl as d,Ll as e,Le as f,Rl as g,gi as h,ce as i,pi as j,El as k,Dl as l,Xt as m,ar as n,yl as o,Rt as p,yr as q,mi as r,Mt as s,Ml as t,xi as u,Pl as v,jl as w,un as x,or as y,Pr as z};
+ */const va=O("X",[["path",{d:"M18 6 6 18",key:"1bl5f8"}],["path",{d:"m6 6 12 12",key:"d8bk6v"}]]),Bn={"Where is avoidable token waste concentrated?":"可避免的token浪费主要集中在哪里？","Stored diagnostics ready":"已存储的诊断数据已就绪","Refreshing investigation evidence...":"正在刷新调查证据…","Strict local evidence bundle exported":"已导出严格本地证据包","Refresh evidence":"刷新证据","Refreshing investigation evidence":"正在刷新调查证据","Loading investigation evidence":"正在加载调查证据","Live report services":"实时报告服务","Loaded aggregate fallback":"已加载的聚合回退数据","linked evidence rows":"关联证据记录","Content access enabled":"内容访问已启用","Content access off":"内容访问未启用",Testing:"正在检验","Test hypothesis":"检验假设","Enable in Settings":"在设置中启用","Local pattern":"本地模式","Linked rows":"关联记录","Impact signal":"影响信号","Ranking score":"排序评分","No investigation evidence is available for the loaded scope.":"已加载范围内没有可用的调查证据。","Root-cause workspace":"根因分析工作区","Ranked waste signals, linked evidence, and one explicit verification path.":"对浪费信号排序，关联证据，并提供一条明确的验证路径。","Export evidence":"导出证据","Selected finding":"所选发现","Ranked findings":"已排序发现","Confidence, scope, and evidence stay visible while comparing.":"比较时始终显示置信度、范围和证据。","Recommended change":"建议的改进","Deterministic action from the selected evidence family.":"根据所选证据类别给出的确定性操作。","Verify with":"验证依据","Missing access":"缺少的访问权限","Verify in call":"在调用中验证","Evidence ledger":"证据台账","Each supported row opens the underlying call or thread.":"每条有支撑的记录都可打开对应调用或线程。","Local hypothesis trace":"本地假设追踪","Bounded pattern exploration over the local content/event index.":"在本地内容/事件索引上进行有界模式探索。","Investigation question":"调查问题","Method and caveats":"方法与注意事项","No supported local pattern met the current threshold.":"没有达到当前阈值且有证据支持的本地模式。","Open call":"打开调用","Open thread":"打开线程","No linked record":"没有关联记录",Pattern:"模式",Events:"事件数",Tokens:"token数",Evidence:"证据",Detail:"详情",Source:"来源",Open:"打开","This finding has no directly linked evidence rows at the current scope.":"当前范围内，此发现没有直接关联的证据记录。","Local Codex logs only; this is not an official OpenAI usage ledger.":"仅使用本地 Codex 日志；这不是 OpenAI 官方用量台账。","Static fallback findings use loaded aggregate rows and cannot identify shell or file rediscovery directly.":"静态回退发现仅使用已加载的聚合记录，无法直接识别 Shell 重复操作或文件重复查找。","Waste fingerprint matrix":"浪费特征矩阵","Recurring diagnostic patterns by thread or aggregate scope; darker cells carry more supporting events.":"按线程或聚合范围展示重复出现的诊断模式；颜色越深，支撑事件越多。","No diagnostic fingerprints are available for the current scope.":"当前范围内没有可用的诊断特征。","Event counts rank evidence volume, not guaranteed token savings.":"事件数只用于衡量证据量，并不保证可以节省相应token。","Use arrow keys to move between cells; use the synchronized table for exact values.":"使用方向键在单元格之间移动；精确数值请查看同步表格。","Waste fingerprints by thread and diagnostic family":"按线程和诊断类别展示浪费特征","Diagnostic family":"诊断类别","Supporting events":"支撑事件数",Finding:"发现","The local report found a repeatable aggregate signal worth reviewing.":"本地报告发现了值得检查的可重复聚合信号。","Inspect the strongest supporting evidence before changing the workflow.":"更改工作流前，请先检查最有力的支撑证据。","No additional access is required for the aggregate evidence.":"查看聚合证据无需额外访问权限。","No raw fragments are included.":"不包含原始片段。","Agentic investigation":"智能体调查","Supporting activity":"支撑活动","Stored diagnostic snapshot":"已存储的诊断快照","Outcome quality remains outside aggregate telemetry.":"聚合遥测无法判断结果质量。","Live diagnostics are unavailable in static mode.":"静态模式下无法使用实时诊断。","This module uses aggregate or stored diagnostic fields and omits raw fragments.":"此模块使用聚合或已存储的诊断字段，并省略原始片段。","Diagnostic snapshot":"诊断快照","Static mode cannot inspect indexed commands or repeated safe file identities.":"静态模式无法检查已索引命令或重复出现的安全文件标识。","Only loaded aggregate call fields are used.":"仅使用已加载的聚合调用字段。","Cache and context pressure":"缓存与上下文压力","Inspect a high-token evidence call, preserve a concise handoff, and start fresh before cold context is resent.":"检查高token证据调用，保留简洁交接信息，并在冷上下文被重新发送前开启新线程。","Aggregate evidence cannot determine whether the large context was necessary for output quality.":"聚合证据无法判断大量上下文是否确实为输出质量所必需。","No prompt or raw tool output is included.":"不包含提示词或原始工具输出。","Loaded call aggregates":"已加载的调用聚合数据","aggregate call":"聚合调用","Open the call and verify whether the context and effort matched the task.":"打开调用，确认上下文和推理强度是否与任务匹配。","Shell churn":"Shell 重复操作","read pattern":"读取模式","File rediscovery":"文件重复查找","Low output":"低输出","Usage driver":"用量驱动因素","Guided summary":"引导式摘要","File modifications":"文件修改","Read productivity":"读取产出效率","Tool output pressure":"工具输出压力","File read patterns":"文件读取模式","File modification concentration":"文件修改集中度","Read-to-change productivity":"读取到修改的产出效率","Usage concentration":"用量集中度","Guided usage summary":"引导式用量摘要","Diagnostic evidence":"诊断证据","Replace repeated inspection sequences with one scoped script or reusable task.":"将重复检查步骤替换为一个范围明确的脚本或可复用任务。","Keep a short repository orientation note and reuse prior findings before reopening the same files.":"保留简短的仓库导览说明，重新打开相同文件前先复用已有发现。","Bound command output and summarize noisy tool results before the next model turn.":"限制命令输出，并在下一轮模型调用前总结冗长的工具结果。","Use a concise handoff and start a fresh thread before a cold resume resends large context.":"使用简洁交接信息，并在冷恢复重新发送大量上下文前开启新线程。","Inspect the dominant thread before applying a broad workflow change.":"大范围调整工作流前，请先检查占主导地位的线程。","Open the strongest evidence row and verify the suspected waste before changing the workflow.":"更改工作流前，请打开最有力的证据记录并验证疑似浪费。","No diagnostic fingerprints are available.":"没有可用的诊断特征。","Investigation report":"调查报告",high:"高",medium:"中",low:"低",evidence:"有证据","no evidence":"无证据",no_evidence:"无证据","Context efficiency research":"上下文效率研究","Measure repeated context and tool-output exposure, allocate overlap once, and rank the largest local savings opportunities.":"测量重复上下文和工具输出暴露，统一分配重叠部分，并对最大的本地节省机会排序。","No current profile":"当前没有分析档案","Refresh analysis":"刷新分析","Analyze usage":"分析用量",Analyzing:"正在分析","Compression analysis progress":"上下文压缩分析进度","Waiting for the usage refresh to finish before starting analysis...":"正在等待用量刷新完成，然后开始分析…","Loading the newest exact-scope profile...":"正在加载最新的精确范围分析档案…","Compression Lab jobs run against the local SQLite index and are unavailable in static-file mode.":"上下文压缩实验室任务基于本地 SQLite 索引运行，静态文件模式下不可用。","No analysis for this scope yet":"尚未分析此范围","Start one persistent run. Returning to this scope will reuse the completed profile until its source revision changes.":"启动一次持久化分析。再次进入此范围时，会复用已完成的分析档案，直到源数据修订发生变化。","Overlap-adjusted portfolio":"已扣除重叠的机会组合","Profile complete":"分析档案已完成","Observed exposure":"观测暴露量","Tokens in analyzed components":"已分析组件中的token数","Likely avoidable":"可能可避免","Overlap-adjusted estimate":"已扣除重叠的估算值","Estimate range":"估算范围","Low to high heuristic":"启发式低值至高值",Candidates:"候选项","Opportunity families":"机会类别","Largest overlap-adjusted detector portfolios first.":"优先显示扣除重叠后规模最大的检测器机会组合。","Shared MCP profile":"共享 MCP 分析档案","Compression opportunity families":"上下文压缩机会类别",Family:"类别","Likely savings":"可能节省量",Range:"范围","Profile integrity":"分析档案完整性","Scope, coverage, and disclosure state for this result.":"此结果的范围、覆盖度和披露状态。",Cache:"缓存","Calls covered":"覆盖的调用数","Content mode":"内容模式","Raw fragments":"原始片段",Included:"已包含","Not included":"未包含","Build time":"生成耗时","Coverage warning":"覆盖度警告","Interpretation limits":"解读限制","Exact warm profile":"精确热缓存档案","Incremental profile":"增量分析档案","Reused profile":"复用的分析档案","Fresh profile":"新生成的分析档案","Preparing detector pipeline":"正在准备检测器流水线",detectors:"个检测器","records examined":"条记录已检查","tokens are the current likely savings estimate":"个token是当前可能节省量估算值","ranked candidates. Exposure is measured; avoidability remains an estimate.":"个已排序候选项。暴露量为实测值，可避免程度仍为估算值。","Compression analysis failed":"上下文压缩分析失败","Profile unavailable":"分析档案不可用",aggregate:"聚合数据",unclassified:"未分类","Stored allowance evidence ready":"已存储的限额证据已就绪","Weekly primary signal selected":"已选择每周主要信号","5-hour noisy context selected":"已选择 5 小时噪声上下文","Refreshing allowance evidence...":"正在刷新限额证据…","Allowance refresh failed":"限额证据刷新失败","Allowance evidence refreshed":"限额证据已刷新","Strict allowance evidence exported":"已导出严格限额证据","Weekly hypothesis evaluated against detector output":"已使用检测器输出评估每周假设","Loading allowance history and detector":"正在加载限额历史记录与检测器",Exporting:"正在导出","Live detector payload":"实时检测器数据","Local claim threshold met":"已达到本地结论阈值","Research caution":"研究结论需谨慎","Outside usage possible":"可能存在外部用量","No large outside-usage flag":"未发现明显的外部用量信号","Weekly evidence first, rolling-window context second, and no claim beyond the loaded local data.":"以每周证据为主、滚动窗口上下文为辅，结论不超出已加载的本地数据。","Observed snapshots":"观测快照数","Weekly primary signal":"每周主要信号","Positive spans":"正向区间数","Candidate ratio":"候选比例","Recent vs earlier proxy":"近期与较早期代理值对比","Unexplained movement":"无法解释的变化","Weekly allowance evidence":"每周限额证据","5-hour rolling context":"5 小时滚动窗口上下文","Primary change detector with recent evidence shown first.":"主要变化检测器，优先显示近期证据。","Secondary context only; rolling-window movement is noisy.":"仅作为辅助上下文；滚动窗口变化包含较多噪声。","Allowance window":"限额窗口",Weekly:"每周","5-hour":"5 小时","Hypothesis check":"假设检验","Evaluate a community-style claim using the server detector result.":"使用服务器检测器结果评估社区常见说法。","Allowance hypothesis":"限额假设","Allowance decreased":"限额下降","Behavior stayed stable":"行为保持稳定","Not evaluated":"尚未评估","Choose a claim, then test it against the weekly detector":"选择一种说法，然后使用每周检测器进行检验","The dashboard reports the backend evidence grade; it does not run a separate client-side detector.":"仪表盘展示后端给出的证据等级，不会在客户端另行运行检测器。","More evidence required":"需要更多证据","Test weekly claim":"检验每周限额说法","Evidence grade":"证据等级","What supports or weakens the current result.":"支持或削弱当前结果的因素。",Method:"方法","No candidate split tested":"尚未检验候选分割点","Effect size":"效应量","One-sided p-value":"单侧 p 值","95% median intervals":"95% 中位数区间","Available for both regimes":"两个区间均可用","Available for one regime; the other sample is too small":"一个区间可用；另一个区间样本量过小","Unavailable at the current sample size":"当前样本量下不可用","Method, readiness, and caveats":"方法、就绪度与注意事项","Weekly observations are the primary signal. The 5-hour counter is rolling-window context.":"每周观测是主要信号；5 小时计数器仅作为滚动窗口上下文。","Weekly windows are treated as the primary signal for allowance-change claims.":"涉及限额变化的结论以每周窗口作为主要信号。","Five-hour windows are rolling counters and are downgraded unless supported by weekly evidence.":"5 小时窗口是滚动计数器；没有每周证据支持时，其证据权重会降低。","Unexplained movement can mean allowance behavior changed, but it can also mean usage outside these local Codex logs.":"无法解释的变化可能表示限额行为发生改变，也可能来自本地 Codex 日志之外的用量。","Allowance intelligence uses aggregate token counters and observed usage percentages only.":"限额分析仅使用聚合token计数和观测到的用量百分比。","Strict privacy output omits prompts, assistant text, tool output, file paths, thread names, and record identifiers.":"严格隐私输出会省略提示词、助手文本、工具输出、文件路径、线程名称和记录标识。","This project cannot read OpenAI's internal allowance ledger.":"此项目无法读取 OpenAI 内部限额台账。","Detector summary unavailable.":"检测器摘要不可用。","Insufficient evidence":"证据不足","The loaded weekly history cannot test this claim yet":"已加载的每周历史记录尚不足以检验此说法","More positive weekly spans are required before comparing regimes.":"比较不同区间前，需要更多正向每周区间。","Not supported":"不支持","No weekly regime change was detected":"未检测到每周区间变化","The loaded spans are more consistent with stable local behavior than a lower allowance regime.":"已加载区间更符合本地行为稳定，而不是限额区间下降。",Inconclusive:"无法确定","A local shift is plausible, but attribution is unresolved":"本地变化有一定可能，但归因尚未解决","Usage outside these local Codex logs could explain enough movement that an allowance change is not isolated.":"本地 Codex 日志之外的用量足以解释部分变化，因此无法单独确认限额发生变化。","Supported locally":"本地证据支持","Repeated weekly spans support a lower local capacity regime":"重复出现的每周区间支持本地容量区间下降","The nonparametric detector meets its local sample, effect-size, and p-value thresholds. This remains local evidence, not an internal ledger result.":"非参数检测器已达到本地样本量、效应量和 p 值阈值；这仍是本地证据，并非内部台账结论。","Possible change":"可能发生变化","The direction is consistent, but the sample is not claim-ready":"变化方向一致，但样本尚不足以形成可靠结论","More weekly spans are required on both sides of the candidate split.":"候选分割点两侧都需要更多每周区间。","Static dashboard fallback; local identifiers omitted.":"静态仪表盘回退数据；已省略本地标识。","Live allowance diagnostics are required before testing a change claim.":"检验限额变化说法前，需要实时限额诊断。","Evidence status":"证据状态","Live allowance detector unavailable in this static snapshot":"此静态快照中无法使用实时限额检测器","Projected weekly windows remain visible for orientation, but only the localhost detector can compare normalized positive spans and candidate regimes.":"仍显示预测的每周窗口用于参考，但只有本机检测器能比较标准化正向区间和候选区间。","Descriptive fallback":"描述性回退数据","Loaded aggregate projections are descriptive fallback data, not detector output.":"已加载的聚合预测仅为描述性回退数据，并非检测器输出。","Current result":"当前结果","No weekly regime change detected":"未检测到每周区间变化","The loaded positive spans remain within one local regime.":"已加载的正向区间仍处于同一本地区间。","No change detected":"未检测到变化","The 5-hour counter is behaving like a noisy rolling window":"5 小时计数器表现为噪声较多的滚动窗口","Use weekly spans as the primary signal before drawing a limit conclusion.":"得出限额结论前，请将每周区间作为主要信号。","Counter noise likely":"计数器可能存在噪声","Observed movement is not fully attributable to these local logs":"观测到的变化无法完全归因于这些本地日志","Outside usage remains plausible, so the detector cannot isolate an allowance change.":"仍可能存在外部用量，因此检测器无法单独确认限额变化。","Candidate regime change":"候选区间变化","The direction is consistent, but repeated weekly evidence is still below the public-claim threshold.":"变化方向一致，但重复出现的每周证据仍低于公开结论阈值。","Local sample, effect-size, and p-value thresholds are met. This is still not an OpenAI ledger result.":"本地样本量、效应量和 p 值均已达到阈值；但这仍不是 OpenAI 台账结论。","The local shift is strong, but at least one research-readiness requirement remains unmet.":"本地变化信号较强，但至少一项研究就绪要求尚未满足。","Claim-ready locally":"本地证据已可形成结论","Strong local evidence":"较强本地证据","Not enough weekly evidence to test an allowance change":"每周证据不足，无法检验限额变化","Insufficient data":"数据不足",Consistent:"一致","Stable weekly behavior fits the loaded evidence":"稳定的每周行为符合已加载证据","No candidate split cleared the detector thresholds.":"没有候选分割点达到检测器阈值。","Stable behavior cannot be isolated either":"同样无法单独确认行为稳定","Outside usage and unexplained movement weaken both the stable and decreased hypotheses.":"外部用量和无法解释的变化同时削弱了“稳定”和“下降”两种假设。","A candidate weekly shift conflicts with the stable hypothesis":"候选每周变化与稳定假设冲突","Review the candidate split and readiness criteria before deciding whether the shift is durable.":"判断变化是否持续前，请检查候选分割点和就绪标准。","the candidate split":"候选分割点","Supporting windows":"支撑窗口","Exact local evidence behind the selected chart. Linked rows open the underlying call.":"所选图表背后的精确本地证据；关联记录可打开底层调用。","Scrollable allowance evidence table":"可滚动的限额证据表格","Allowance evidence windows and linked calls":"限额证据窗口与关联调用",Observed:"观测时间","Capacity proxy":"容量代理值",Remaining:"剩余比例",Movement:"变化","Est. credits":"估算点数",Plan:"套餐",Actions:"操作",Aggregate:"聚合数据","No usable evidence rows are available for this window.":"此窗口没有可用的证据记录。","Load more windows":"加载更多窗口","Weekly local capacity evidence":"每周本地容量证据","Observed weekly remaining":"每周剩余比例观测值","Estimated credits per 100 percentage points of observed weekly movement, with exact median intervals when the sample supports them.":"按每周观测变化的每 100 个百分点估算点数；样本充分时显示精确中位数区间。","Loaded aggregate weekly projections for orientation. Exact detector intervals require the localhost allowance endpoints.":"已加载的每周聚合预测仅供参考；精确检测器区间需要本机限额接口。","Observed percentage remaining. The 5-hour view is intentionally secondary because rolling-window movement is noisy.":"观测到的剩余百分比。由于滚动窗口变化噪声较多，5 小时视图仅作为辅助。","weekly spans":"每周区间","weekly primary signal":"每周主要信号","secondary rolling-window context":"辅助滚动窗口上下文","This is a local capacity proxy, not an official OpenAI allowance or billing ledger.":"这是本地容量代理值，并非 OpenAI 官方限额或计费台账。","Rolling-window movement, resets, and sparse observations make the 5-hour counter noisy.":"滚动窗口变化、重置和稀疏观测会使 5 小时计数器包含较多噪声。","Use left and right arrow keys to move through observations. Switch to the table for exact values.":"使用左右方向键浏览观测值；精确数值请切换到表格。","95% low":"95% 下限","95% high":"95% 上限","Observed movement":"观测变化","Weekly evidence span":"每周证据区间","Observed time":"观测时间","Credits per 100% observed movement":"每 100% 观测变化对应点数","Percent remaining":"剩余百分比","Local capacity proxy":"本地容量代理值","Weekly remaining":"每周剩余比例","Noisy 5-hour remaining":"含噪声的 5 小时剩余比例","Candidate shift · outside usage possible":"候选变化 · 可能存在外部用量","Candidate weekly regime shift":"候选每周区间变化","Observed counter reset or rollback":"观测到计数器重置或回退","Observation gap":"观测间隔","weekly span":"每周区间",observation:"观测值","strong local evidence":"较强本地证据","possible regime change":"可能发生区间变化","inconclusive other usage possible":"无法确定，可能存在其他用量","no change detected":"未检测到变化","counter noise likely":"计数器可能存在噪声","insufficient data":"数据不足","Cache And Context Lab":"缓存与上下文实验室","Cache behavior, cold resumes, context pressure, optimization recommendations.":"分析缓存行为、冷恢复、上下文压力和优化建议。","Full-scope endpoints":"完整范围接口","Snapshot fallback":"快照回退数据","Context safe":"上下文安全","Loading cache and context evidence":"正在加载缓存与上下文证据","Cache Hit Rate & Context Window Over Time":"缓存命中率与上下文窗口趋势","Cache reuse and context pressure":"缓存复用与上下文压力",Percent:"百分比","Cache Reuse Heatmap":"缓存复用热力图","No cache heatmap rows":"没有缓存热力图记录","Scrollable cache reuse heatmap":"可滚动的缓存复用热力图","Cache reuse heatmap":"缓存复用热力图","No cache heatmap rows in the current aggregate snapshot.":"当前聚合快照中没有缓存热力图记录。","Threads Overview":"线程概览","Cold resume and cache efficiency signals":"冷恢复与缓存效率信号","Hover previews; rows open latest call":"悬停可预览；单击记录可打开最新调用","Cache context threads overview":"缓存与上下文线程概览","Selected Thread Diagnosis":"所选线程诊断","No grouped thread is available in the current aggregate snapshot.":"当前聚合快照中没有可用的分组线程。","Efficiency Profile":"效率概况","Cache hit":"缓存命中率","Est. cost":"估算成本","Cost/call":"单次调用成本","Cache Windows":"缓存窗口","Weekly reuse":"每周复用","No heatmap row":"没有热力图记录","no heatmap row":"没有热力图记录","No weekly cache heatmap row matches this selected thread.":"没有与所选线程匹配的每周缓存热力图记录。","No loaded aggregate call rows match this selected thread.":"没有与所选线程匹配的已加载聚合调用记录。","Diagnosis Basis":"诊断依据","Suggested Actions":"建议操作","Summarize before the next work session.":"在下次工作会话前先做摘要。","Split completed topics or reduce repeated uncached context.":"拆分已完成的主题，或减少重复的未缓存上下文。","Open a related call and inspect whether model effort was justified.":"打开相关调用，检查模型推理强度是否合理。","Keep the thread warm and continue monitoring cache reuse.":"保持线程热缓存，并继续监控缓存复用。","Thread summaries":"线程摘要","Selected thread calls":"所选线程调用","Focused evidence":"聚焦证据","server-side aggregate":"服务器端聚合数据","review cache reuse":"检查缓存复用",Window:"窗口"},ti=[{pattern:/^Live evidence refreshed · ([\d,.]+) diagnostic modules$/u,replace:"实时证据已刷新 · $1 个诊断模块"},{pattern:/^Refresh failed: (.+)$/u,replace:"刷新失败：$1"},{pattern:/^Live report unavailable: (.+)$/u,replace:"实时报告不可用：$1"},{pattern:/^Investigation report unavailable: (.+)$/u,replace:"调查报告不可用：$1"},{pattern:/^(.+) unavailable: (.+)$/u,replace:"$1不可用：$2"},{pattern:/^Loading diagnostics ([\d,.]+)\/([\d,.]+)$/u,replace:"正在加载诊断模块 $1/$2"},{pattern:/^([\d,.]+) diagnostic modules$/u,replace:"$1 个诊断模块"},{pattern:/^([\d,.]+) ranked findings$/u,replace:"$1 个已排序发现"},{pattern:/^([\d,.]+) signals$/u,replace:"$1 个信号"},{pattern:/^([\d,.]+) rows$/u,replace:"$1 条记录"},{pattern:/^([\d,.]+) linked$/u,replace:"已关联 $1 条"},{pattern:/^([\d,.]+) score$/u,replace:"评分 $1"},{pattern:/^Evidence ledger for (.+)$/u,replace:(e,t)=>`“${Xa(t)}”的证据台账`},{pattern:/^(.+) · ([\d,.]+) events · ([\d,.]+(?:[KMBT])?) tokens$/iu,replace:"$1 · $2 个事件 · $3 个token"},{pattern:/^history (active|all) · no stored snapshot\. Function calls: ([\d,.]+); Function outputs: ([\d,.]+); Original tokens: ([\d,.]+)\.$/u,replace:(e,t,a,n,r)=>`历史范围：${t==="all"?"全部历史记录":"活动会话"} · 没有已存储快照。函数调用：${a}；函数输出：${n}；原始token数：${r}。`},{pattern:/^(Open call|Open thread|No linked record) for (.+)$/u,replace:(e,t,a)=>`${ai(t)}：${a}`},{pattern:/^Copy call link for (.+)$/u,replace:"复制以下模式对应的调用链接：$1"},{pattern:/^Open call evidence for (.+)$/u,replace:"打开以下模式的调用证据：$1"},{pattern:/^Open thread evidence for (.+)$/u,replace:"打开以下模式的线程证据：$1"},{pattern:/^([\d,.]+) loaded calls combine weak cache reuse or elevated context pressure\.$/u,replace:"$1 次已加载调用存在缓存复用较弱或上下文压力升高的情况。"},{pattern:/^(.+) is the highest-ranked of ([\d,.]+) findings with ([\d,.]+) supporting rows\.$/u,replace:(e,t,a,n)=>`“${Xa(t)}”在 ${a} 个发现中排名最高，并有 ${n} 条支撑记录。`},{pattern:/^([\d,.]+(?:\.\d+)?)% cache · ([\d,.]+(?:[KMBT])?) output$/iu,replace:"缓存 $1% · 输出 $2 个token"},{pattern:/^Compression analysis failed: (.+)$/u,replace:"上下文压缩分析失败：$1"},{pattern:/^Profile unavailable: (.+)$/u,replace:"分析档案不可用：$1"},{pattern:/^([\d,.]+) of ([\d,.]+) detectors \/ ([\d,.]+) records examined$/u,replace:"检测器 $1/$2 · 已检查 $3 条记录"},{pattern:/^([\d,.]+(?:[KMBT])?) tokens are the current likely savings estimate$/iu,replace:"当前可能节省量估算为 $1 个token"},{pattern:/^([\d,.]+) to ([\d,.]+) across ([\d,.]+) ranked candidates\. Exposure is measured; avoidability remains an estimate\.$/u,replace:"在 $3 个已排序候选项中，估算范围为 $1 至 $2。暴露量为实测值，可避免程度仍为估算值。"},{pattern:/^([\d,.]+) coverage warnings$/u,replace:"$1 条覆盖度警告"},{pattern:/^([\d,.]+) detector families$/u,replace:"$1 个检测器类别"},{pattern:/^(.+) detector$/u,replace:"$1 检测器"},{pattern:/^Export failed: (.+)$/u,replace:"导出失败：$1"},{pattern:/^Live detector unavailable: (.+)$/u,replace:"实时检测器不可用：$1"},{pattern:/^([\d,.]+) weekly spans · (.+)$/u,replace:"$1 个每周区间 · $2"},{pattern:/^([\d,.]+) resets \/ rollbacks$/u,replace:"$1 次重置/回退"},{pattern:/^([\d,.]+) positive weekly spans are loaded\. More observations are needed before comparing regimes\.$/u,replace:"已加载 $1 个正向每周区间。比较不同区间前还需要更多观测值。"},{pattern:/^Weekly behavior shifted around (.+)$/u,replace:"每周行为在 $1 附近发生变化"},{pattern:/^The recent local capacity proxy is ([\d,.]+)% of the earlier regime after (.+)$/u,replace:"$2 之后，近期本地容量代理值为较早区间的 $1%"},{pattern:/^Span ([\d,.]+)$/u,replace:"区间 $1"},{pattern:/^Observation ([\d,.]+)$/u,replace:"观测 $1"},{pattern:/^Open allowance evidence call observed (.+)$/u,replace:"打开以下观测对应的限额证据调用：$1"},{pattern:/^Copy link to allowance evidence call observed (.+)$/u,replace:"复制以下观测对应的限额证据调用链接：$1"},{pattern:/^At least two (weekly spans|observations) are required for a trend\.$/u,replace:(e,t)=>`至少需要两个${t==="weekly spans"?"每周区间":"观测值"}才能显示趋势。`},{pattern:/^(.+) · weekly primary signal$/u,replace:"$1 · 每周主要信号"},{pattern:/^(.+) · secondary rolling-window context$/u,replace:"$1 · 辅助滚动窗口上下文"},{pattern:/^(Weekly local capacity evidence|Observed weekly remaining|5-hour rolling context) evidence$/u,replace:(e,t)=>`${ni(t)}证据`},{pattern:/^Only ([\d,.]+) usable weekly span is available\.$/u,replace:"仅有 $1 个可用的每周区间。"},{pattern:/^Only ([\d,.]+) usable observation is available\.$/u,replace:"仅有 $1 个可用的观测值。"},{pattern:/^([\d,.]+) 5-hour observations are shown as noisy rolling-window context, not primary allowance evidence\.$/u,replace:"当前显示 $1 个 5 小时观测值，它们仅作为含噪声的滚动窗口上下文，而非主要限额证据。"},{pattern:/^([\d,.]+) cache windows$/u,replace:"$1 个缓存窗口"},{pattern:/^Selected (.+): ([\d,.]+(?:\.\d+)?)% cache$/u,replace:"已选择“$1”：缓存 $2%"},{pattern:/^Selected (.+)$/u,replace:"已选择：$1"},{pattern:/^Showing ([\d,.]+) of ([\d,.]+) full-scope thread summaries\.$/u,replace:"显示 $1 / $2 个完整范围线程摘要。"},{pattern:/^([\d,.]+) loaded$/u,replace:"已加载 $1 条"},{pattern:/^([\d,.]+) loaded calls$/u,replace:"已加载 $1 次调用"},{pattern:/^([\d,.]+(?:[KMBT])?) tokens - ([\d,.]+(?:\.\d+)?)% cache$/iu,replace:"$1 个token - 缓存 $2%"},{pattern:/^([\d,.]+(?:[KMBT])?) total tokens$/iu,replace:"共 $1 个token"},{pattern:/^Window ([\d,.]+)$/u,replace:"窗口 $1"},{pattern:/^Cache windows for (.+)$/u,replace:"“$1”的缓存窗口"},{pattern:/^Open investigator for cache thread call (.+)$/u,replace:"在分析器中打开缓存线程调用：$1"},{pattern:/^Copy link for cache thread call (.+)$/u,replace:"复制缓存线程调用链接：$1"},{pattern:/^Risk: (High|Medium|Low) cold-resume score$/u,replace:(e,t)=>`风险：冷恢复评分${Ya(t)}`},{pattern:/^(High|Medium|Low) risk$/u,replace:(e,t)=>`${Ya(t)}风险`},{pattern:/^Cache: ([\d,.]+(?:\.\d+)?)% hit rate; action threshold below 35%$/u,replace:"缓存：命中率 $1%；操作阈值低于 35%"},{pattern:/^Cost: (.+) per call; inspect threshold above \$1\.00$/u,replace:"成本：每次调用 $1；检查阈值高于 $1.00"},{pattern:/^Evidence: ([\d,.]+) loaded calls, ([\d,.]+) cache windows$/u,replace:"证据：已加载 $1 次调用，包含 $2 个缓存窗口"},{pattern:/^Evidence: ([\d,.]+) loaded calls, no heatmap row$/u,replace:"证据：已加载 $1 次调用，没有热力图记录"}];function ai(e){return e==="Open call"?"打开调用":e==="Open thread"?"打开线程":"没有关联记录"}function Xa(e){return Bn[e]??e}function ni(e){return e==="Weekly local capacity evidence"?"每周本地容量":e==="Observed weekly remaining"?"每周剩余比例观测值":"5 小时滚动窗口上下文"}function Ya(e){return e==="High"?"高":e==="Medium"?"中":"低"}const ri={"Active history":"活动记录","Active sessions":"活动会话","Active sessions only":"仅活动会话","Aggregate fallback":"聚合数据回退","Aggregate only":"仅聚合数据","All calls visible":"显示全部调用","All history selected":"已选择全部历史记录","All time":"全部时间","Analysis scope":"分析范围","Auto refresh":"自动刷新","Auto refresh paused":"自动刷新已暂停","Auto refresh pauses on this evidence-heavy view":"此证据密集页面会暂停自动刷新","Available languages":"可用语言","Back to top":"返回顶部","Browse all calls":"浏览全部调用","Cancel refresh":"取消刷新","Chart view":"图表视图","Chart unavailable. Use the synchronized table view.":"图表不可用，请使用同步表格视图。","Caveats:":"注意事项：","Choose loaded call window":"选择调用加载范围","Clear filters":"清除筛选条件","Clipboard unavailable":"剪贴板不可用",Columns:"列",Commands:"命令","Copy call link":"复制调用链接","Copy investigator link":"复制分析器链接","Copy unavailable in browser":"浏览器中无法复制",Custom:"自定义","Dashboard filters":"仪表盘筛选器","Dashboard route could not load":"仪表盘页面无法加载","Dashboard toolbar":"仪表盘工具栏",Day:"日期",Dense:"紧凑",Daily:"每日",Density:"显示密度","Endpoint fallback":"接口回退数据","Endpoint unavailable.":"接口不可用。",Export:"导出","Export overview":"导出概览","Export SVG":"导出 SVG","Export visualization as SVG":"将可视化导出为 SVG",Files:"文件",FILTERS:"筛选",Filters:"筛选",From:"来源","Global confidence filter":"全局置信度筛选器","Global effort filter":"全局推理强度筛选器","Global end date":"全局结束日期","Global model filter":"全局模型筛选器","Global start date":"全局开始日期","Global time filter":"全局时间筛选器","History scope":"历史记录范围","Incomplete page evidence":"页面证据不完整",Lifecycle:"生命周期","Invalid date range":"日期范围无效","Last 24h":"过去 24 小时","Last 7 days":"过去 7 天","Live API":"实时 API","Loaded snapshot":"已加载快照","Loading dashboard":"正在加载仪表盘","Loading renderer...":"正在加载图表渲染器…","Local API token present for refresh actions.":"已提供本地 API 令牌，可执行刷新操作。","Local data only":"仅使用本地数据",Models:"模型","More columns":"更多列","No data":"暂无数据","No matching evidence":"没有匹配的证据","No rows match current filters.":"没有符合当前筛选条件的记录。",Primary:"主导航",Privacy:"隐私","Quick Links":"快捷入口",Recent:"最近记录","Recent rows":"最近记录","Refresh data":"刷新数据","Restore defaults":"恢复默认设置","Restoring the local usage workspace...":"正在恢复本地用量工作区…",Retry:"重试",Roomy:"宽松",Search:"搜索",Selected:"已选择","Show more columns":"显示更多列","Static embedded snapshot":"静态内嵌快照","Static embedded snapshot; live refresh is unavailable.":"当前为静态内嵌快照，无法实时刷新。","Stored snapshot":"已存储的快照","Stored snapshot loaded just now":"刚刚载入已存储的快照","Table view":"表格视图",Table:"表格","Tokens line chart":"token折线图","Tokens history. Recent dates are shown first; scroll left for earlier dates.":"token历史记录。近期日期优先显示；向左滚动可查看更早日期。","Cache % line chart":"缓存比例折线图","Cache % history. Recent dates are shown first; scroll left for earlier dates.":"缓存比例历史记录。近期日期优先显示；向左滚动可查看更早日期。","Text direction":"文字方向",Today:"今天","Unofficial project notice":"非官方项目声明","Unofficial project.":"非官方项目。",Updated:"已更新","Updated unversioned":"更新于未标记版本","Updating evidence":"正在更新证据","Updating page evidence":"正在更新页面证据","Working on full-scope evidence":"正在处理完整范围的证据","Usage summary ready":"用量摘要已就绪","Recommendations loading":"建议正在加载","Recommendations ready":"建议已就绪","24 hours":"24 小时","7 days":"7 天","Aggregate Identity":"聚合记录标识","Aggregate summary":"聚合摘要",Auto:"自动","Cache And Context":"缓存与上下文","Cache Reuse":"缓存复用率",Cached:"缓存输入","Cached %":"缓存比例","Cached Input":"缓存输入","Call filters":"调用筛选器","Compression Lab":"上下文压缩实验室","Context %":"上下文比例","Context window":"上下文窗口","Diagnostics Notebook":"诊断工作台",Duration:"耗时",Effort:"推理强度","Input Tokens":"输入token",Initiated:"发起方",Investigate:"调查分析",Investigation:"调查分析",Limits:"使用限额","Loaded usage metrics":"已加载的用量指标","Loading overview evidence":"正在加载概览证据","Loading overview evidence modules":"正在加载概览证据模块","Loaded token accounting":"已加载的token统计","Local telemetry console":"本地用量分析控制台","No calls are available for token accounting.":"没有可用于token统计的调用。","No daily token movement is available.":"没有可用的每日token变化数据。","No dated aggregate usage is available in this scope.":"当前范围内没有带日期的聚合用量数据。","No loaded calls match the current search.":"已加载的调用中没有符合当前搜索条件的记录。","No token accounting is available in this scope.":"当前范围内没有可用的token统计数据。","Not made by, affiliated with, endorsed by, sponsored by, or supported by OpenAI.":"本项目并非由 OpenAI 制作，也不隶属于 OpenAI，未获其认可、赞助或支持。",Overview:"概览","Prev Gap":"与上次间隔","Pricing configured":"已配置定价","Project metadata is shown normally.":"项目元数据按正常模式显示。","Recent token movement":"近期token变化","Daily input, cached reuse, and output volume in the selected history scope.":"所选历史范围内的每日输入、缓存复用和输出量。","Daily aggregates describe local records; they do not represent OpenAI billing.":"每日聚合仅描述本地记录，不代表 OpenAI 账单。","Categories mirror reported fields and may overlap; flow widths are accounting, not causality or billed cost.":"分类与日志报告字段一致，彼此可能重叠；流量宽度仅表示统计量，不代表因果关系或计费成本。","The four reported token categories across calls currently loaded in the dashboard.":"仪表盘当前已加载调用中的四类token统计。","The important changes first, with direct paths into supporting evidence.":"优先展示重要变化，并可直接查看支撑证据。","reported token accounting":"日志报告的token统计","loaded evidence rows":"已加载的证据记录","loaded calls only":"仅统计已加载调用","calls with mapped cost and credit rates":"已匹配成本与点数费率的调用","Estimated credits":"估算点数","risk: low cache reuse":"风险：缓存复用率低",Reasoning:"推理输出","Reasoning Output":"推理输出",Reports:"报告",Settings:"设置",Signals:"信号",CACHE:"缓存",CTX:"上下文",EST:"估算",LO:"低输出",RSN:"推理",BIG:"长线程",PRICE:"定价",SUB:"子智能体","Sort by Cached %":"按缓存比例排序","Sort by Cached Input":"按缓存输入排序","Sort by Codex Credits":"按 Codex 点数排序","Sort by Context %":"按上下文比例排序","Sort by Duration":"按耗时排序","Sort by Effort":"按推理强度排序","Sort by Est. Cost":"按估算成本排序","Sort by Initiated":"按发起方排序","Sort by Input Tokens":"按输入token排序","Sort by Model":"按模型排序","Sort by Output Tokens":"按输出token排序","Sort by Prev Gap":"按与上次间隔排序","Sort by Reasoning Output":"按推理输出排序","Sort by Signals":"按信号排序","Sort by Thread":"按线程排序","Sort by Time":"按时间排序","Sort by Total Tokens":"按token总数排序","Sort by Uncached Input":"按未缓存输入排序","Total Calls":"调用总数","Total Tokens":"token总数","Total Tokens breakdown":"token总数明细","Estimated Cost breakdown":"估算成本明细",Uncached:"未缓存输入","Uncached Input":"未缓存输入","Usage pulse":"用量脉搏","Visualization contract error":"可视化定义错误","Visualization view":"可视化视图","Visualization is loading.":"正在加载可视化。","Partial evidence":"部分证据","Evidence unavailable":"证据不可用","must include at least one series":"必须至少包含一个数据系列",series:"数据系列","Recent dates shown. Scroll left for earlier dates.":"当前显示近期日期；向左滚动可查看更早日期。","Data is ready.":"数据已就绪。","Live facts":"实时事实","Live snapshots":"实时快照",loading:"正在加载",updating:"正在更新",unavailable:"不可用",waiting:"等待中","Model calls display controls":"模型调用显示控件","Highest-attention Threads display controls":"关注度最高的对话线程显示控件","aggregate rows":"聚合记录","grouped threads":"分组线程","Percent line chart":"百分比折线图","Percent history. Recent dates are shown first; scroll left for earlier dates.":"百分比历史记录。近期日期优先显示；向左滚动可查看更早日期。","Reload Commands diagnostic snapshot":"重新加载命令诊断快照","Reload Git Interactions diagnostic snapshot":"重新加载 Git 交互诊断快照","unknown · weekly primary signal":"未知 · 每周主要信号","Cache hit %":"缓存命中率","Thread lifecycle":"线程生命周期",Call:"调用",Elapsed:"已经过时间",Context:"上下文",Continuation:"延续调用",Initiator:"发起方",total:"总计",blank:"未指定",max:"最大",ultra:"极高",xhigh:"超高"},si=[{pattern:/^(.+) table$/u,replace:"$1表格"},{pattern:/^([\d,.]+)m ([\d,.]+)s$/u,replace:"$1 分 $2 秒"},{pattern:/^([\d,.]+)s$/u,replace:"$1 秒"},{pattern:/^Sort by (.+)$/u,replace:(e,t)=>`按${t}排序`},{pattern:/^Showing ([\d,.]+) of ([\d,.]+) table rows$/u,replace:"显示 $1 / $2 条表格记录"},{pattern:/^Show ([\d,.]+) more rows$/u,replace:"再显示 $1 条记录"},{pattern:/^Loaded ([\d,.]+) of ([\d,.]+) available calls$/u,replace:"已加载 $1 / $2 次可用调用"},{pattern:/^([\d,.]+) calls analyzed · ([\d,.]+) detail rows cached$/u,replace:"已分析 $1 次调用 · 已缓存 $2 条详情记录"},{pattern:/^([\d,.]+) calls available in scope$/u,replace:"当前范围内有 $1 次调用"},{pattern:/^([\d,.]+) loaded calls$/u,replace:"已加载 $1 次调用"},{pattern:/^([\d,.]+) evidence rows$/u,replace:"$1 条证据记录"},{pattern:/^Unknown project ([\d,.]+)$/u,replace:"未知项目 $1"},{pattern:/^([\d,.]+) ranked evidence rows$/u,replace:"$1 条已排序证据记录"},{pattern:/^Updated (.+)$/u,replace:"更新于 $1"},{pattern:/^Loading (.+)\.\.\.$/u,replace:"正在加载$1…"},{pattern:/^No (.+) to export$/u,replace:"没有可导出的$1"},{pattern:/^Exported ([\d,.]+) (.+)$/u,replace:"已导出 $1 条$2"},{pattern:/^(.+) endpoint failed with HTTP ([\d]+)\.$/u,replace:"$1接口请求失败（HTTP $2）。"},{pattern:/^Back to (.+)$/u,replace:"返回$1"},{pattern:/^Clear (.+)$/u,replace:"清除$1"},{pattern:/^Incomplete page evidence: (.+)$/u,replace:"页面证据不完整：$1"},{pattern:/^All time analysis uses ([\d,.]+) calls; ([\d,.]+) detail rows cached$/u,replace:"全部时间范围共分析 $1 次调用；已缓存 $2 条详情记录"},{pattern:/^Focused pages analyze all ([\d,.]+) calls in scope; ([\d,.]+) call rows are cached for immediate detail views\.$/u,replace:"聚焦页面会分析范围内全部 $1 次调用；已缓存 $2 条调用记录，可立即查看详情。"},{pattern:/^([\d,.]+) of ([\d,.]+) modules ready$/u,replace:"$1/$2 个模块已就绪"},{pattern:/^([\d,.]+(?:[KMBT])?) cached input tokens$/iu,replace:"$1 个缓存输入token"},{pattern:/^([\d,.]+(?:[KMBT])?) cached input$/iu,replace:"$1 个缓存输入token"},{pattern:/^(.+) · (.+) · ([\d,.]+(?:[KMBT])?) tokens · ([\d,.]+(?:\.\d+)?)% cache$/iu,replace:"$1 · $2 · $3 个token · 缓存 $4%"},{pattern:/^([\d,.]+) matching calls with the same evidence fields as the Calls workspace\.$/u,replace:"$1 次调用符合条件，证据字段与“调用”工作区一致。"},{pattern:/^Load more recent calls$/u,replace:"加载更多近期调用"},{pattern:/^(.+) line chart$/u,replace:"$1折线图"},{pattern:/^(.+) chart$/u,replace:"$1图表"},{pattern:/^(.+) history\. Recent dates are shown first; scroll left for earlier dates\.$/u,replace:"$1历史记录。近期日期优先显示；向左滚动可查看更早日期。"},{pattern:/^Showing ([\d,.]+) of ([\d,.]+) full-scope thread summaries\.$/u,replace:"显示 $1 / $2 个完整范围线程摘要。"},{pattern:/^([\d,.]+) table rows available\.$/u,replace:"可查看 $1 条表格记录。"},{pattern:/^(.+) display controls$/u,replace:"$1显示控件"},{pattern:/^(.+) modules$/u,replace:"$1模块"}],ii={"High-level telemetry":"全局用量概览","Root-cause evidence":"根因证据","Context savings":"上下文节省分析","Model-call table":"模型调用明细","Thread efficiency":"线程效率","Allowance intelligence":"限额分析","Cache and cold resumes":"缓存与冷恢复","Technical report":"技术诊断","Generated analyses":"生成的分析报告","Local configuration":"本地配置","Search dashboard":"搜索仪表盘","Search calls, threads, models, diagnostics...":"搜索调用、线程、模型和诊断…","Loaded cached dashboard snapshot":"已加载缓存的仪表盘快照","Refresh cancelled; stored snapshot remains visible":"刷新已取消，仍显示已存储的快照","Copied current view link":"已复制当前视图链接","Copied call investigator link":"已复制调用分析器链接","Copied investigator link":"已复制分析器链接","Copied Calls view link":"已复制“调用”视图链接","Copy unavailable in this browser":"此浏览器无法复制","Investigation preset cleared":"已清除调查预设","Calls filters cleared":"已清除调用筛选条件","Thread filters cleared":"已清除线程筛选条件","Refreshing usage index":"正在刷新用量索引","All history selected; no archived calls are indexed yet":"已选择全部历史记录，但尚未索引归档调用","All calls loaded":"已加载全部调用","Rows to load":"加载记录数","Rows to load slider":"加载记录数滑块","Row loading progress":"记录加载进度","All effort":"全部推理强度","All confidence":"全部置信度","All models":"全部模型","All sources":"全部来源","Exact cost":"精确成本","Estimated cost":"估算成本","Unpriced cost":"未定价成本","Exact credit":"精确点数","Estimated credit":"估算点数","Credit override":"点数费率覆盖值","Missing credit":"缺少点数费率","Exact credit rate":"精确点数费率","Estimated credit mapping":"估算点数映射","User credit override":"用户点数费率覆盖值","Missing credit rate":"缺少点数费率","This week":"本周","This month":"本月","Custom range":"自定义范围","Scope accounting categories":"范围统计分类","Loaded accounting categories":"已加载数据统计分类",To:"去向",Basis:"依据","More filters":"更多筛选条件","Project / cwd":"项目 / 工作目录","Session-linked":"关联会话","Git metadata":"Git 元数据","Source file":"源文件","Missing source":"缺少来源信息",Start:"开始日期",End:"结束日期",Sort:"排序",Direction:"方向",Ascending:"升序",Descending:"降序","Loading...":"正在加载…","Refreshing...":"正在刷新…","Loading more...":"正在加载更多…","Loading evidence":"正在加载证据","Updating focused rows":"正在更新聚焦记录","Loading focused rows":"正在加载聚焦记录","Focused paged API":"聚焦分页 API","Focused endpoints":"聚焦接口","Partial endpoint evidence":"部分接口证据","Multiple searches use loaded snapshot":"多个搜索条件将使用已加载的快照","Preset uses loaded snapshot":"预设将使用已加载的快照","Source filter uses loaded snapshot":"来源筛选将使用已加载的快照","Risk filter uses loaded snapshot":"风险筛选将使用已加载的快照","This sort uses loaded snapshot":"此排序将使用已加载的快照","Date range invalid":"日期范围无效","Custom date range":"自定义日期范围","not available in filtered view":"筛选后的视图中不可用","not available in payload":"数据中不可用","filtered aggregate rows":"筛选后的聚合记录","local pricing config":"本地定价配置","privacy-safe estimate":"隐私安全估算","loaded calls matching filters":"符合筛选条件的已加载调用","legacy shell filters":"旧版全局筛选条件","active history":"活动记录","all history":"全部历史记录","call rows":"调用记录","settings rows":"设置记录","complete selected scope":"完整的所选范围","healthy cache reuse":"缓存复用良好","cache risk":"缓存风险","static snapshot":"静态快照","no cap":"不设上限","Click opens full investigator. Hover or press Space previews details.":"单击打开完整分析器；悬停或按空格键可预览详情。","Click to inspect details. Double-click or press Enter open full investigator.":"单击查看详情；双击或按 Enter 键打开完整分析器。","Click or press Enter open the full investigator.":"单击或按 Enter 键打开完整分析器。","Local API token present for refresh actions.":"已提供本机 API 令牌，可执行刷新操作。","Static embedded snapshot; live refresh is unavailable.":"当前为静态内嵌快照，无法实时刷新。","Codex credit rates":"Codex 点数费率","Rate-card error":"费率表错误","Credit rates loaded":"已加载点数费率","No local allowance windows are configured.":"尚未配置本地限额窗口。","cwd redacted":"工作目录已脱敏","project names redacted":"项目名称已脱敏","git remote hidden":"Git 远程地址已隐藏","relative cwd hidden":"相对工作目录已隐藏","git branch hidden":"Git 分支已隐藏","tags hidden":"标签已隐藏","Estimated Credits":"估算点数","Estimated Cost":"估算成本","Usage Remaining":"剩余用量","Cache Hit Rate":"缓存命中率","Cache hit rate":"缓存命中率","Cache state":"缓存状态","Cache read":"缓存读取量","Cache/context":"缓存/上下文",mostly_codex:"主要由 Codex 发起",mostly_user:"主要由用户发起",mixed:"混合发起","Stop and summarize the failure mode before retrying commands.":"再次尝试命令前，请先停止操作并总结失败模式。","Usage summary":"用量摘要",Recommendations:"建议","Selected scope usage metrics":"所选范围的用量指标","No rule-based usage issue stands out":"未发现明显的规则型用量问题","Load calls to establish a usage baseline":"加载调用以建立用量基线","The Overview needs aggregate calls before it can rank evidence or build token accounting.":"“概览”需要先获得聚合调用，才能对证据排序并生成token统计。","Continue monitoring and investigate any workflow that feels unexpectedly expensive.":"继续监控，并调查任何成本异常偏高的工作流。","Load recent calls or all history.":"加载近期调用或全部历史记录。","Review the loaded aggregate evidence in Investigate.":"在“调查分析”中查看已加载的聚合证据。","Focused summary unavailable; showing loaded call rows.":"聚焦摘要不可用，当前显示已加载的调用记录。","Daily token movement":"每日token变化","Scope accounting":"范围统计","Loaded accounting":"已加载数据统计","calls in selected scope":"所选范围内的调用","loaded calls":"已加载调用","Token accounting in scope":"范围内token统计","The four reported token categories across the complete selected data scope.":"完整所选数据范围内日志报告的四类token统计。","Reported type":"报告类型","Input accounting":"输入统计","Generated accounting":"生成内容统计","calls in the selected scope":"所选范围内的调用","One ranked call supports this pattern.":"有 1 次已排序调用支持此模式。","all-history scope":"全部历史记录范围","active-history scope":"活动记录范围","No loaded calls are available for the usage constellation.":"没有可用于用量星图的已加载调用。","Unassigned thread":"未归属线程","Other models":"其他模型","Overview calls":"概览调用","Overview calls display controls":"概览调用显示控件","Overview calls ranked list":"概览调用排序列表",Calls:"调用","Evidence explorer":"证据浏览器","Find expensive, cold, or context-heavy calls and move directly into their evidence.":"查找高成本、冷缓存或上下文负载较高的调用，并直接查看相关证据。","Copy view":"复制视图链接","Model calls":"模型调用","Call filters":"调用筛选器","Search calls":"搜索调用","Search calls, cwd, projects, models...":"搜索调用、工作目录、项目和模型…",Confidence:"置信度","Confidence filter":"置信度筛选器","Time filter":"时间筛选器",Source:"来源","Source filter":"来源筛选器","Start date":"开始日期","End date":"结束日期","Sort calls":"调用排序","Sort direction":"排序方向","Newest calls":"最新调用","Longest duration":"耗时最长","Longest gap":"间隔最长","Needs attention":"需要关注","Thread name":"线程名称","Usage Over Time":"用量趋势","Cost by Model":"按模型统计成本","Estimated USD":"估算美元成本","Cache Hit Rate Over Time":"缓存命中率趋势","Cache %":"缓存比例","Usage patterns":"用量模式","Raw context gated":"原始上下文受控","Call Drill-Down":"调用深入分析","No matching call":"没有匹配的调用","Not available":"不可用","Not reported":"未报告","No aggregate row matches the active filters.":"没有符合当前筛选条件的聚合记录。","Aggregate only":"仅聚合数据","Call drill-down sections":"调用深入分析区域","Total tokens":"token总数","fresh billed input":"新增计费输入","Fresh share":"新增输入占比","Loaded thread calls":"已加载的线程调用","Thread tokens":"线程token数","loaded aggregate rows":"已加载的聚合记录","Thread cost":"线程成本","estimated aggregate":"聚合估算","Avg cache":"平均缓存比例","Initiated by":"发起方","Initiator reason":"发起原因","Previous gap":"与上次调用的间隔","Project path":"项目路径","Working directory":"工作目录","Git remote":"Git 远程地址","Git hash":"Git 哈希","Token composition":"token构成","Cache delta readout":"缓存变化解读","Accounting Snapshot":"统计快照","pricing, credits, and cache savings":"定价、点数与缓存节省","Use this readout to decide whether the aggregate call needs deeper raw-context investigation.":"根据此解读判断是否需要进一步调查该聚合调用的原始上下文。","Call Narrative":"调用解读","Call Source":"调用来源","Direct thread":"直接线程","No model mix":"没有模型构成数据","no model mix":"没有模型构成数据","not reported":"未报告","no parent session":"没有父会话","aggregate inference":"聚合推断","estimated pricing":"估算定价","configured pricing":"已配置定价","fast candidate":"可快速处理","normal throughput":"吞吐量正常","Investigation Readout":"调查解读","Aggregate + on-demand evidence":"聚合数据与按需证据","No aggregate recommendation":"没有聚合建议","Compared previous call":"已与上一次调用比较","This call is outside the loaded snapshot. Serve the dashboard with its localhost API token to hydrate it.":"此调用不在已加载的快照中。请使用本机 API 令牌运行仪表盘，以补载其数据。","Loading call detail from localhost...":"正在从本机服务加载调用详情…","Selected call is not present in the loaded dashboard rows.":"已加载的仪表盘记录中没有所选调用。","No aggregate call rows are loaded.":"尚未加载聚合调用记录。","Hydrated live":"已实时补载","Hydrated from /api/call":"已从 /api/call 补载","Record outside loaded snapshot":"记录位于已加载快照之外","Position: hydrated live record outside loaded snapshot":"位置：已实时补载，记录位于已加载快照之外","Token Accounting":"token统计","Exact aggregate row fields":"精确的聚合记录字段","Cache Accounting":"缓存统计","Derived from adjacent aggregate call":"根据相邻聚合调用推导","Context Attribution":"上下文归因","Local metadata only":"仅本地元数据","Thread Context":"线程上下文","Raw Evidence":"原始证据","Explicit localhost request only":"仅在明确请求本机服务时加载","Context mode":"上下文模式","Context entries":"上下文条目","Side panel context mode":"侧栏上下文模式","Side panel context entries":"侧栏上下文条目","Visible chars":"可见字符数","redacted local text":"已脱敏的本地文本","Visible tokens":"可见token数","Older omitted":"已省略较早条目","entry budget":"条目预算","Thread calls":"线程调用数","Cache risks":"缓存风险","weak reuse or flagged":"复用较弱或已标记","Context pressure":"上下文压力",">=60% context window":"上下文窗口占用不低于 60%","Models in thread":"线程中的模型","Effort mix":"推理强度构成","Enabling localhost context API...":"正在启用本机上下文 API…","Context API enabled. Load this call when ready.":"上下文 API 已启用，可以加载此调用。","Context API did not enable.":"未能启用上下文 API。","Loading selected-turn evidence...":"正在加载所选轮次的证据…","Loading full turn analysis...":"正在加载完整轮次分析…","Loading older context...":"正在加载更早的上下文…","Loading omitted tool output...":"正在加载已省略的工具输出…","Loading compacted replacement...":"正在加载压缩后的替换内容…","local evidence":"本地证据","[no visible text]":"[没有可见文本]","[no visible replacement text]":"[没有可见的替换文本]","Raw context is never embedded in the dashboard HTML. This view reads the selected local JSONL turn only after an explicit request.":"原始上下文绝不会嵌入仪表盘 HTML；只有明确请求后，此视图才会读取本地 JSONL 中所选轮次的内容。","Raw context is read from the local JSONL source only after this explicit action and is not embedded in static dashboard HTML.":"只有执行此明确操作后才会从本地 JSONL 源读取原始上下文，并且不会将其嵌入静态仪表盘 HTML。","No visible evidence entries returned for this call.":"此调用没有返回可见的证据条目。","Static file mode cannot read local JSONL context. Use serve-dashboard with the context API enabled.":"静态文件模式无法读取本地 JSONL 上下文。请运行 serve-dashboard 并启用上下文 API。","Context loading requires the localhost dashboard server API token.":"加载上下文需要本机仪表盘服务器的 API 令牌。","Context API is available but off. Enable it here before loading selected-turn evidence.":"上下文 API 可用但尚未启用；请先在此启用，再加载所选轮次的证据。","Context API is enabled. Load selected-turn evidence from the local JSONL source only when needed.":"上下文 API 已启用；仅在需要时从本地 JSONL 源加载所选轮次的证据。","Local JSONL context loaded on demand.":"已按需加载本地 JSONL 上下文。","No previous call is loaded in resolved thread, call-to-call deltas unavailable.":"解析出的线程中未加载上一次调用，因此无法计算调用间变化。","Token accounting broadly stable compared previous call in resolved thread.":"与解析出的线程中上一次调用相比，token统计整体稳定。","Evidence is not loaded yet. Aggregate token counts are exact, but visible-context attribution needs runtime evidence.":"尚未加载证据。聚合token数是精确值，但可见上下文归因需要运行时证据。","Fast serialized estimate only; full serialized grouping deferred.":"当前仅提供快速序列化估算；完整的序列化分组尚未执行。","Compare previous call, then inspect loaded evidence see fresh context was sent after cache miss.":"先与上一次调用比较，再检查已加载证据，确认缓存未命中后发送了哪些新增上下文。","Inspect most recent evidence entries first; spike is in fresh uncached input, not cached history.":"请先检查最新的证据条目；峰值来自新增的未缓存输入，而不是缓存历史。","Use delta cards to locate whether change came from cached input, uncached input, or output/reasoning.":"使用变化卡片判断差异来自缓存输入、未缓存输入，还是输出/推理。","Use loaded evidence if aggregate totals are not enough understand this isolated call.":"如果聚合总量不足以解释此调用，请查看已加载证据。","visible-token estimate":"可见token估算","Raw context is gated":"原始上下文受控","Include compaction history":"包含压缩历史","Record id":"记录 ID","Entry tokens":"条目token数","Session tokens":"会话token数","Tool output":"工具输出","Evidence entry metadata":"证据条目元数据","Elapsed since selected turn start":"自所选轮次开始后的耗时","Gap since previous evidence entry":"与上一条证据的间隔","Duration reported by this event":"此事件报告的耗时","Token usage reported for this evidence entry":"此证据条目报告的token用量","Cumulative token usage reported by this evidence entry":"此证据条目报告的累计token用量","Compaction replacement history is available for this entry":"此条目有可用的压缩替换历史","Tool output omitted until explicitly requested":"工具输出已省略，明确请求后才会加载","No previous call":"没有上一次调用","No previous call loaded for delta comparison.":"尚未加载可用于变化对比的上一次调用。","No previous aggregate call available for cache delta accounting.":"没有可用于缓存变化统计的上一次聚合调用。","Some prefix reused cache, but a meaningful share of input was fresh or reserialized.":"部分前缀复用了缓存，但仍有相当比例的输入为新增内容或重新序列化内容。","Cache accounting is stable versus the previous aggregate call.":"与上一次聚合调用相比，缓存统计基本稳定。","Compare the previous call, then inspect loaded evidence to see what fresh context was sent after the cache miss.":"先与上一次调用比较，再检查已加载证据，确认缓存未命中后发送了哪些新增上下文。","Use delta cards to locate whether the change came from cached input, uncached input, or output/reasoning.":"使用变化卡片判断差异来自缓存输入、未缓存输入，还是输出/推理。","Use loaded evidence if aggregate totals are not enough to understand this isolated call.":"如果聚合总量不足以解释此调用，请查看已加载证据。","Cache Accounting Delta":"缓存统计变化","Not loaded yet":"尚未加载","Runtime evidence":"运行时证据","exact aggregate row":"精确聚合记录","serialized-breakdown deferred":"序列化明细尚未生成","uncached input minus visible estimate":"未缓存输入减去可见内容估算值","serialized upper bound minus visible estimate":"序列化上限减去可见内容估算值","not covered by serialized upper bound":"序列化上限未覆盖的部分","No serialized evidence groups returned.":"没有返回序列化证据分组。","Configure pricing":"配置定价","Compare fresh input":"比较新增输入","Inspect thread timeline":"查看线程时间线","Review reasoning effort":"检查推理强度","Use aggregate first":"先查看聚合数据","High reported context use.":"报告的上下文占用较高。","Reasoning output exceeds visible output.":"推理输出超过可见输出。","Review cost and credit impact before loading raw context.":"加载原始上下文前，请先检查成本和点数影响。","No aggregate efficiency flag on this row.":"此记录没有聚合效率标记。","Call Decision":"调用决策","cold or weak cache":"缓存未命中或复用较弱","partial cache reuse":"部分缓存复用","No related calls":"没有相关调用","Highest Cost Threads":"成本最高的线程","Context Bloat":"上下文膨胀","Cache Misses":"缓存未命中","Pricing Gaps":"定价缺口","Reasoning Spike":"推理峰值","Output Tokens":"输出token","Est. Cost":"估算成本","Codex Credits":"Codex 点数","Effort Mix":"推理强度构成","Explore workspace":"浏览工作区","File evidence":"文件证据","Tool evidence":"工具证据","File filters":"文件筛选器","Tool filters":"工具筛选器","Search file evidence":"搜索文件证据","Search tool evidence":"搜索工具证据","Search path labels and exact path hashes...":"搜索路径标签和精确路径哈希…","Search tools, categories, and actions...":"搜索工具、类别和操作…","File evidence results":"文件证据结果","Tool evidence results":"工具证据结果","File evidence results display controls":"文件证据结果显示控件","Tool evidence results display controls":"工具证据结果显示控件","File evidence results ranked list":"文件证据结果排序列表","Tool evidence results ranked list":"工具证据结果排序列表","File inspector":"文件检查器","Tool inspector":"工具检查器","No evidence selected":"尚未选择证据","No representative call":"没有代表性调用","Select a file row to inspect its aggregate activity.":"选择一条文件记录以查看其聚合活动。","Select a tool row to inspect its aggregate evidence.":"选择一条工具记录以查看其聚合证据。","Find repeated reads and modifications using local aggregate path labels and stable path hashes.":"利用本地聚合路径标签和稳定路径哈希查找重复读取与修改。","Rank tool and function activity by associated token pressure, then inspect the calls behind each pattern.":"按关联token压力对工具和函数活动排序，再查看每种模式背后的调用。","No file evidence is available in the stored diagnostic snapshots.":"已存储的诊断快照中没有文件证据。","No tool evidence matches the active filters.":"没有符合当前筛选条件的工具证据。","File evidence requires the localhost dashboard server.":"文件证据需要本机仪表盘服务器。","Tool evidence requires the localhost dashboard server.":"工具证据需要本机仪表盘服务器。","Local server required":"需要本机服务器","Updating file snapshots":"正在更新文件快照","Loading file snapshots":"正在加载文件快照","File snapshots unavailable":"文件快照不可用","Stored diagnostic snapshots":"已存储的诊断快照","No file snapshots loaded":"尚未加载文件快照","Updating tool facts":"正在更新工具事实","Loading tool facts":"正在加载工具事实","Tool facts unavailable":"工具事实不可用","Focused diagnostic API":"聚焦诊断 API","No tool facts loaded":"尚未加载工具事实","Path Hash":"路径哈希","Path Label":"路径标签","Read Events":"读取事件数","Read Output":"读取输出","Allocated Read Output Tokens":"分配的读取输出token数","Modification Events":"修改事件数","Path hash":"路径哈希","Read evidence":"读取证据","Modification evidence":"修改证据","Read events":"读取事件数","Read output":"读取输出","Open evidence call":"打开证据调用","Path hashes provide stable local identity for repeated rediscovery without placing raw file content in the aggregate response.":"路径哈希可为重复发现提供稳定的本地标识，同时避免在聚合响应中包含原始文件内容。","Uncached Input Tokens":"未缓存输入token数","Cache Percent":"缓存比例","Largest Call":"最大调用","Associated Calls":"关联调用数","Associated calls":"关联调用","Cache reuse":"缓存复用率","Largest call":"最大调用","Open largest call":"打开最大调用","Supporting calls":"支撑调用","No supporting call rows are loaded for this tool fact.":"尚未加载此工具事实对应的支撑调用记录。","tool activity":"工具活动","Unknown path":"未知路径","Visible columns":"可见列","No evidence matches the current filters.":"没有符合当前筛选条件的证据。",Threads:"线程","Thread Leaderboard":"线程排行榜","Thread leaderboard":"线程排行榜","Compare work units, follow lifecycle pressure, and open supporting calls without leaving the evidence surface.":"比较工作单元、跟踪生命周期压力，并在证据页面中直接打开支撑调用。","Thread filters":"线程筛选器","Search threads":"搜索线程","Search threads, risks, token totals...":"搜索线程、风险和token总量…","Cold risk":"冷恢复风险","All risks":"全部风险","Cache frontier":"缓存效率前沿","Updating thread calls":"正在更新线程调用","Updating focused threads":"正在更新聚焦线程","Loading focused threads":"正在加载聚焦线程","Reset thread view":"重置线程视图","Loading thread summaries and selected calls":"正在加载线程摘要和所选调用","Thread evidence view":"线程证据视图","Thread evidence":"线程证据","Thread evidence display controls":"线程证据显示控件","Thread evidence ranked list":"线程证据排序列表","Export thread calls":"导出线程调用","Reset view":"重置视图","Selected Thread":"所选线程","No matching thread":"没有匹配的线程","No grouped thread matches the active filters.":"没有符合当前筛选条件的分组线程。","Thread Calls":"线程调用","No loaded calls":"没有已加载的调用","Loading more calls":"正在加载更多调用","No loaded aggregate call rows belong to this thread.":"此线程没有已加载的聚合调用记录。","Turns visible":"可见轮次数","Total duration":"总耗时","Average gap":"平均间隔","Cached / uncached input":"缓存 / 未缓存输入","Peak context":"上下文峰值","Risk Mix":"风险构成",Productivity:"生产效率","Thread Status":"线程状态","Pricing status":"定价状态","Credit status":"点数状态","Cache ratio":"缓存比例","Max context use":"最大上下文占用","Thread Impact":"线程影响","Codex credits":"Codex 点数","Allowance impact":"限额影响","Attention score":"关注度评分","Cost per call":"单次调用成本","Thread Lifecycle":"线程生命周期","Subagent before spike":"峰值前出现子代理","Aggregate trend":"聚合趋势","First expensive turn":"首次高成本轮次","Largest token jump":"最大token增幅","Cache trend":"缓存趋势","Context trend":"上下文趋势",Relationships:"关系","Loaded aggregate links":"已加载的聚合关联","Spawned from":"派生自","Subagent calls":"子代理调用","Auto-review calls":"自动审查调用","Attached calls":"附加调用","Spawned threads":"派生线程","Spawned child calls":"派生子调用","Thread Fields":"线程字段","Latest activity":"最近活动","Loaded calls":"已加载调用","Efficiency signals":"效率信号","Model mix":"模型构成","Sort thread calls":"线程调用排序","Sort thread calls direction":"线程调用排序方向",Newest:"最新","Most tokens":"token最多","Highest cost":"成本最高","Lowest cache":"缓存比例最低","Avg Gap":"平均间隔","Cost / Call":"单次调用成本","Cold Resume Risk":"冷恢复风险",Latest:"最近活动",Turns:"轮次",High:"高",Medium:"中",Low:"低","Official match":"官方精确匹配",Mixed:"混合匹配",Configured:"已配置","Estimated mapping":"估算映射","No mapped rate":"没有匹配的费率","No price":"无定价","Cache Drop":"缓存下降","Cache Risk":"缓存风险","Context Heavy":"上下文负载高","Elevated Context":"上下文偏高","Elevated Context Use":"上下文占用偏高","Estimated Pricing":"估算定价","Expensive Low Output Call":"高成本低输出调用","High Context Use":"上下文占用高","High Cost":"高成本","High Estimated Cost":"估算成本高","High Reasoning Share":"推理占比高","Large Thread":"大型线程","Low Cache":"缓存偏低","Low Cache Reuse":"缓存复用率低","Low Output":"输出偏低","Pricing Gap":"定价缺口","Subagent Attribution":"子智能体归因","Review context growth":"检查上下文增长","Check cache drop":"检查缓存下降","Compare subagent calls":"比较子代理调用","Review recommendations":"查看建议","Load thread calls":"加载线程调用","Cache efficiency frontier":"缓存效率前沿","Threads further right carry more input; threads lower on the plot reuse less of it.":"越靠右的线程输入量越大；图中位置越低，缓存复用越少。","No threads match the current scope.":"没有符合当前范围的线程。","Credits and cost remain estimates when exact rate metadata is unavailable.":"如果没有精确费率元数据，点数和成本仍为估算值。","Use arrow keys to move between threads; press Enter to synchronize the selected row.":"使用方向键在线程间移动；按 Enter 键同步所选记录。","Cache efficiency by thread":"各线程缓存效率","35% review floor":"35% 检查阈值","Context pressure and cache reuse across the selected thread.":"所选线程的上下文压力与缓存复用情况。","Context-window evidence is unavailable for this thread.":"此线程没有可用的上下文窗口证据。","No thread selected":"尚未选择线程","Lifecycle labels are inferred from aggregate timing, cache, and context fields.":"生命周期标签根据聚合耗时、缓存和上下文字段推断。","Use left and right arrow keys to move through calls in lifecycle order.":"使用左右方向键按生命周期顺序浏览调用。","Selected thread lifecycle calls":"所选线程的生命周期调用","Lifecycle event":"生命周期事件","Minutes since first call":"距首次调用的分钟数","Context / cache":"上下文 / 缓存","No loaded high-token thread falls below the 35 percent cache review floor.":"没有已加载的高token线程低于 35% 的缓存检查阈值。","the selected thread":"所选线程","Thread start":"线程开始","Cold resume":"冷恢复","Warm continuation":"热缓存延续"},oi=[{pattern:/^(Today|This week|Last 7 days|This month): (\d{4}-\d{2}-\d{2}) to (\d{4}-\d{2}-\d{2})$/u,replace:(e,t,a,n)=>`${li(t)}：${a} 至 ${n}`},{pattern:/^Custom: (\d{4}-\d{2}-\d{2}) to (\d{4}-\d{2}-\d{2})$/u,replace:"自定义：$1 至 $2"},{pattern:/^Custom: from (\d{4}-\d{2}-\d{2})$/u,replace:"自定义：从 $1 开始"},{pattern:/^Custom: through (\d{4}-\d{2}-\d{2})$/u,replace:"自定义：截至 $1"},{pattern:/^Auto refresh every ([\d,.]+)s$/u,replace:"每 $1 秒自动刷新"},{pattern:/^All history includes ([\d,.]+) archived calls$/u,replace:"全部历史记录包含 $1 次归档调用"},{pattern:/^Active sessions only; ([\d,.]+) archived calls hidden$/u,replace:"仅活动会话；已隐藏 $1 次归档调用"},{pattern:/^([\d,.]+) detail rows? cached$/u,replace:"已缓存 $1 条详情记录"},{pattern:/^([\d,.]+) loaded \/ ([\d,.]+) total$/u,replace:"已加载 $1 / 共 $2 条"},{pattern:/^([\d,.]+) of ([\d,.]+) evidence rows loaded$/u,replace:"已加载 $1 / $2 条证据记录"},{pattern:/^([\d,.]+) recent rows$/u,replace:"$1 条近期记录"},{pattern:/^([\d,.]+)% loaded$/u,replace:"已加载 $1%"},{pattern:/^(Loading|Refreshing) (24 hours|7 days|recent rows|all time)\.\.\.$/u,replace:(e,t,a)=>`${t==="Refreshing"?"正在刷新":"正在加载"}${xt(a)}…`},{pattern:/^Refreshing index for (24 hours|7 days|recent rows|all time)\.\.\.$/u,replace:(e,t)=>`正在刷新${xt(t)}的索引…`},{pattern:/^(Cache hit; |Refreshed index; )?[Ll]oaded ([\d,.]+) of ([\d,.]+) calls from (24 hours|7 days|recent rows|all time)$/u,replace:(e,t,a,n,r)=>`${en(t)}已从${xt(r)}加载 ${a} / ${n} 次调用`},{pattern:/^(Cache hit; |Refreshed index; )?(24 hours|7 days|recent rows|all time) analysis ready across ([\d,.]+) calls; ([\d,.]+) detail rows cached$/iu,replace:(e,t,a,n,r)=>`${en(t)}${xt(a.toLowerCase())}分析已就绪，共 ${n} 次调用；已缓存 ${r} 条详情记录`},{pattern:/^(.+) Stored snapshot kept at (.+)$/u,replace:"$1 已保留 $2 的存储快照"},{pattern:/^Metadata mode: (.+)$/u,replace:"元数据模式：$1"},{pattern:/^Config error: (.+)$/u,replace:"配置错误：$1"},{pattern:/^Rate-card error: (.+)$/u,replace:"费率表错误：$1"},{pattern:/^Deduped · ([\d,.]+) copied excluded$/u,replace:"已去重 · 排除 $1 条重复记录"},{pattern:/^Billable totals use ([\d,.]+) canonical rows while preserving ([\d,.]+) physical source rows\.$/u,replace:"计费总量使用 $1 条规范记录，同时保留 $2 条物理来源记录。"},{pattern:/^([\d,.]+) detailed rows available$/u,replace:"有 $1 条详情记录可用"},{pattern:/^([\d,.]+) daily buckets are available, with the visible window favoring the most recent ([\d,.]+)\.$/u,replace:"共有 $1 个每日时间桶，当前视图优先显示最近 $2 个。"},{pattern:/^([\d,.]+) (loaded calls|calls in selected scope|calls in the selected scope)$/u,replace:(e,t,a)=>`${t} 次${a==="loaded calls"?"已加载调用":"所选范围内调用"}`},{pattern:/^([\d,.]+) (loaded calls|calls in selected scope|calls in the selected scope) include ([\d,.]+) percent cached input reuse\.$/u,replace:(e,t,a,n)=>`${a==="loaded calls"?"已加载的":"所选范围内的"} ${t} 次调用中，缓存输入复用率为 ${n}%。`},{pattern:/^([\d,.]+) ranked calls support this pattern\.$/u,replace:"有 $1 次已排序调用支持此模式。"},{pattern:/^((?:low|medium|high|xhigh|ultra|max) x[\d,]+(?:, (?:low|medium|high|xhigh|ultra|max) x[\d,]+)*)$/u,replace:(e,t)=>di(t)},{pattern:/^([\d,.]+(?:[KMBT])?) at (.+)$/iu,replace:"$1，发生于 $2"},{pattern:/^(.+) · Call ([\d,.]+)$/u,replace:"$1 · 第 $2 次调用"},{pattern:/^([\d,.]+(?:\.\d+)?) credits \((Official match|Mixed|Configured|Estimated mapping|No mapped rate|No price)\)$/u,replace:(e,t,a)=>`${t} 点（${ui(a)}）`},{pattern:/^([\d,.]+(?:[KMBT])?) tokens - ([\d,.]+(?:\.\d+)?)% cache - (.+)$/iu,replace:"$1 个token - 缓存 $2% - $3"},{pattern:/^([\d,.]+(?:[KMBT])?) tokens - ([\d,.]+(?:\.\d+)?)% cache$/iu,replace:"$1 个token - 缓存 $2%"},{pattern:/^Context ([\d,.]+(?:\.\d+)?)%$/iu,replace:"上下文 $1%"},{pattern:/^Prev ([\d,.]+)m ([\d,.]+)s$/iu,replace:"距上次 $1 分 $2 秒"},{pattern:/^Prev ([\d,.]+)s$/iu,replace:"距上次 $1 秒"},{pattern:/^Prev (.+)$/iu,replace:"距上次 $1"},{pattern:/^(.+) initiated$/iu,replace:"$1 发起"},{pattern:/^(.+) is the clearest current signal$/u,replace:"当前最明确的信号是：$1"},{pattern:/^([\d,.]+) representative calls from ([\d,.]+) loaded calls$/u,replace:"从 $2 次已加载调用中选取 $1 次代表性调用"},{pattern:/^The constellation plots ([\d,.]+) loaded calls\. The largest plotted call used ([\d,.]+) tokens\. The lowest plotted cache reuse was ([\d,.]+) percent\.$/u,replace:"星图展示了 $1 次已加载调用。图中最大调用使用 $2 个token，最低缓存复用率为 $3%。"},{pattern:/^The constellation plots ([\d,.]+) representative calls from ([\d,.]+) loaded calls\. The largest plotted call used ([\d,.]+) tokens\. The lowest plotted cache reuse was ([\d,.]+) percent\.$/u,replace:"星图从 $2 次已加载调用中展示 $1 次代表性调用。图中最大调用使用 $3 个token，最低缓存复用率为 $4%。"},{pattern:/^Showing ([\d,.]+) of ([\d,.]+) aggregate rows$/u,replace:"显示 $1 / $2 条聚合记录"},{pattern:/^([\d,.]+) project\/cwd rows$/u,replace:"$1 条项目/工作目录记录"},{pattern:/^([\d,.]+) session-linked rows$/u,replace:"$1 条会话关联记录"},{pattern:/^([\d,.]+) git rows$/u,replace:"$1 条 Git 记录"},{pattern:/^([\d,.]+) source-file rows$/u,replace:"$1 条源文件记录"},{pattern:/^([\d,.]+) rows missing source$/u,replace:"$1 条缺少来源信息的记录"},{pattern:/^([\d,.]+) project, ([\d,.]+) session, ([\d,.]+) git$/u,replace:"项目 $1 条，会话 $2 条，Git $3 条"},{pattern:/^Preset: (Highest Cost Threads|Context Bloat|Cache Misses|Pricing Gaps|Codex Credits|Reasoning Spike)$/u,replace:(e,t)=>`预设：${ci(t)}`},{pattern:/^Exported ([\d,.]+) calls$/u,replace:"已导出 $1 次调用"},{pattern:/^Exported ([\d,.]+) loaded calls$/u,replace:"已导出 $1 次已加载调用"},{pattern:/^([\d,.]+) of ([\d,.]+) loaded calls$/u,replace:"第 $1 次，共 $2 次已加载调用"},{pattern:/^([\d,.]+) loaded related calls$/u,replace:"已加载 $1 次相关调用"},{pattern:/^selected ([\d,.]+) of ([\d,.]+)$/u,replace:"已选择第 $1 个，共 $2 个"},{pattern:/^Call ([\d,.]+) of ([\d,.]+)$/u,replace:"调用 $1 / $2"},{pattern:/^Entry ([\d,.]+)$/u,replace:"条目 $1"},{pattern:/^line ([\d,.]+)$/u,replace:"第 $1 行"},{pattern:/^Show first ([\d,.]+) entries$/u,replace:"显示前 $1 个条目"},{pattern:/^Show all ([\d,.]+) returned entries$/u,replace:"显示返回的全部 $1 个条目"},{pattern:/^Replacement item ([\d,.]+)$/u,replace:"替换项 $1"},{pattern:/^([\d,.]+) replacement entries$/u,replace:"$1 个替换条目"},{pattern:/^([\d,.]+(?:[KMBT])?) total · ([\d,.]+(?:[KMBT])?) uncached$/iu,replace:"共 $1 个 · 未缓存 $2 个"},{pattern:/^([\d,.]+) older entries omitted\.$/u,replace:"已省略 $1 个较早条目。"},{pattern:/^([\d,.]+) chars over budget omitted\.$/u,replace:"已省略超出预算的 $1 个字符。"},{pattern:/^Source: (.+)\.$/u,replace:"来源：$1。"},{pattern:/^Evidence request failed: (.+)$/u,replace:"证据请求失败：$1"},{pattern:/^Evidence analyzed: ([\d,.]+) selected-turn entries, ([\d,.]+) visible redacted chars, ([\d,.]+) visible tokens\.(.*)$/u,replace:"已分析证据：所选轮次包含 $1 个条目、$2 个可见脱敏字符和 $3 个可见token。$4"},{pattern:/^Serialized local upper bound: ([\d,.]+) tokens\.$/u,replace:"本地序列化上限：$1 个token。"},{pattern:/^Position: (.+)$/u,replace:"位置：$1"},{pattern:/^([\d,.]+) analyzed chars$/u,replace:"已分析 $1 个字符"},{pattern:/^([\d,.]+) raw JSON chars$/u,replace:"$1 个原始 JSON 字符"},{pattern:/^([\d,.]+) raw lines$/u,replace:"$1 行原始内容"},{pattern:/^([\d,.]+) credits counted$/u,replace:"计入 $1 点"},{pattern:/^([\d,.]+) credits$/u,replace:"$1 点"},{pattern:/^([\d,.]+(?:[KMBT])?) uncached input with weak cache reuse\.$/iu,replace:"$1 个未缓存输入token，缓存复用较弱。"},{pattern:/^Fresh input rose by ([\d,.]+) while cached input fell by ([\d,.]+); classic cache-drop profile\.$/u,replace:"新增输入增加 $1，而缓存输入减少 $2；这是典型的缓存下降特征。"},{pattern:/^Fresh input increased by ([\d,.]+) from previous call; inspect evidence new files, tool results, or rewritten context\.$/u,replace:"与上一次调用相比，新增输入增加 $1；请检查证据中的新文件、工具结果或重写的上下文。"},{pattern:/^Fresh input fell by ([\d,.]+) while cached input increased, so this call reused context more efficiently previous one\.$/u,replace:"新增输入减少 $1，同时缓存输入增加，因此此调用比上一次更高效地复用了上下文。"},{pattern:/^Cache reuse is healthy; focus on ([\d,.]+) uncached tokens (?:were|that were) still billed as fresh input\.$/u,replace:"缓存复用良好；但仍有 $1 个未缓存token按新增输入计费，建议重点检查。"},{pattern:/^Uncached input: ([+\-\d,.]+)\. Cached input: ([+\-\d,.]+)\. Cache ratio: ([+\-\d,.]+pp)\.$/u,replace:"未缓存输入：$1。缓存输入：$2。缓存比例：$3。"},{pattern:/^Uncached input rose by ([\d,.]+) while cached input fell by ([\d,.]+)\.$/u,replace:"未缓存输入增加 $1，同时缓存输入减少 $2。"},{pattern:/^Uncached input increased by ([\d,.]+) versus the previous aggregate call\.$/u,replace:"与上一次聚合调用相比，未缓存输入增加 $1。"},{pattern:/^Uncached input decreased by ([\d,.]+) while cached input increased\.$/u,replace:"未缓存输入减少 $1，同时缓存输入增加。"},{pattern:/^Signals: (.+)$/u,replace:"信号：$1"},{pattern:/^Open call row in investigator for (.+)$/u,replace:"在分析器中打开调用记录：$1"},{pattern:/^Open investigator for latest call in (.+)$/u,replace:"在分析器中打开该线程的最新调用：$1"},{pattern:/^Copy link for latest call in (.+)$/u,replace:"复制该线程最新调用的链接：$1"},{pattern:/^No loaded call available for (.+)$/u,replace:"没有可用于以下对象的已加载调用：$1"},{pattern:/^Open investigator for thread call (.+)$/u,replace:"在分析器中打开线程调用：$1"},{pattern:/^Copy link for thread call (.+)$/u,replace:"复制线程调用链接：$1"},{pattern:/^Context use (.+)$/u,replace:"上下文占用：$1"},{pattern:/^([\d,.]+) reads · ([\d,.]+(?:[KMBT])?) output · ([\d,.]+) modifications$/iu,replace:"读取 $1 次 · 输出 $2 个token · 修改 $3 次"},{pattern:/^([\d,.]+(?:[KMBT])?) uncached · ([\d,.]+) calls · ([\d,.]+)% cache$/iu,replace:"未缓存输入 $1 · 调用 $2 次 · 缓存 $3%"},{pattern:/^([\d,.]+) loaded$/u,replace:"已加载 $1 条"},{pattern:/^Load ([\d,.]+) more$/u,replace:"再加载 $1 条"},{pattern:/^Inspect (.+) file evidence$/u,replace:"检查文件证据：$1"},{pattern:/^Inspect (.+) tool evidence$/u,replace:"检查工具证据：$1"},{pattern:/^Open evidence call for (.+)$/u,replace:"打开以下对象的证据调用：$1"},{pattern:/^Copy evidence call link for (.+)$/u,replace:"复制以下对象的证据调用链接：$1"},{pattern:/^Open largest call for (.+)$/u,replace:"打开以下对象的最大调用：$1"},{pattern:/^Copy largest call link for (.+)$/u,replace:"复制以下对象的最大调用链接：$1"},{pattern:/^Showing ([\d,.]+) of ([\d,.]+) grouped threads$/u,replace:"显示 $1 / $2 个分组线程"},{pattern:/^([\d,.]+) selected calls$/u,replace:"已选择 $1 次调用"},{pattern:/^([\d,.]+) calls · ([\d,.]+(?:[KMBT])?) tokens · ([\d,.]+)% cache$/iu,replace:"$1 次调用 · $2 个token · 缓存 $3%"},{pattern:/^([\d,.]+) of ([\d,.]+) loaded$/u,replace:"已加载 $1 / $2 次"},{pattern:/^Show ([\d,.]+) more calls$/u,replace:"再显示 $1 次调用"},{pattern:/^Show first ([\d,.]+)$/u,replace:"显示前 $1 条"},{pattern:/^([\d,.]+) more available$/u,replace:"还有 $1 条可用"},{pattern:/^([\d,.]+) spawned$/u,replace:"已派生 $1 个"},{pattern:/^([\d,.]+) signals$/u,replace:"$1 个信号"},{pattern:/^Call ([\d,.]+)$/u,replace:"调用 $1"},{pattern:/^([\d,.]+) loaded threads$/u,replace:"已加载 $1 个线程"},{pattern:/^([\d,.]+) loaded threads combine at least 50,000 tokens with less than 35 percent cache reuse\.$/u,replace:"有 $1 个已加载线程的token数不低于 50,000，且缓存复用率低于 35%。"},{pattern:/^No loaded calls are available for (.+)\.$/u,replace:(e,t)=>`没有可用于${t==="the selected thread"?"所选线程":`“${t}”`}的已加载调用。`},{pattern:/^([\d,.]+) calls are available for (.+); peak observed context use is ([\d,.]+) percent\.$/u,replace:"“$2”有 $1 次调用可用；观察到的上下文占用峰值为 $3%。"}];function xt(e){return e==="24 hours"?"过去 24 小时":e==="7 days"?"过去 7 天":e==="recent rows"?"近期记录":"全部时间范围"}function en(e){return e==="Cache hit; "?"命中缓存；":e==="Refreshed index; "?"索引已刷新；":""}function ci(e){return e==="Highest Cost Threads"?"成本最高的线程":e==="Context Bloat"?"上下文膨胀":e==="Cache Misses"?"缓存未命中":e==="Pricing Gaps"?"定价缺口":e==="Codex Credits"?"Codex 点数":"推理峰值"}function li(e){return e==="Today"?"今天":e==="This week"?"本周":e==="Last 7 days"?"过去 7 天":"本月"}function di(e){const t={low:"低",medium:"中",high:"高",xhigh:"超高",ultra:"极高",max:"最大"};return e.split(", ").map(a=>a.replace(/^(low|medium|high|xhigh|ultra|max) x([\d,]+)$/u,(n,r,s)=>`${t[String(r)]} ×${s}`)).join("、")}function ui(e){return{"Official match":"官方精确匹配",Mixed:"混合匹配",Configured:"已配置","Estimated mapping":"估算映射","No mapped rate":"没有匹配的费率","No price":"无定价"}[e]??e}const Gn={Action:"操作",Ascending:"升序",Blocked:"受阻",Cached:"已缓存","Cached %":"缓存占比",Calls:"调用",Category:"类别",Copy:"复制",Credits:"点数",Descending:"降序",Effort:"推理强度",Evidence:"证据",Fallback:"回退数据",Finding:"发现",High:"高",Input:"输入",Largest:"最大调用",Latest:"最近时间",Loading:"正在加载",Low:"低",Medium:"中",Model:"模型",Occurrences:"出现次数",Open:"打开",Output:"输出",Planned:"计划中",Ready:"就绪",Reasoning:"推理",Reports:"报告",Stale:"已过期",Static:"静态",Thread:"线程",Threads:"线程",Time:"时间",Total:"总计",Uncached:"未缓存",Unknown:"未知",fallback:"回退数据",high:"高",low:"低",medium:"中",missing:"缺失",ready:"就绪",review:"需复核",snapshots:"快照",facts:"事实",Showing:"已显示",Show:"再显示",of:"/",more:"条",loaded:"条已加载","loaded facts":"条已加载事实",matched:"条匹配","evidence rows":"条证据记录","calls -":"次调用 ·","tokens -":"token ·","cache -":"缓存 ·","Dashboard rows:":"仪表盘记录：","Diagnostics Notebook":"诊断工作台","Technical report system behavior usage patterns.":"关于系统行为与用量模式的技术报告。","Local Only":"仅限本地","Loading diagnostic fact sources":"正在加载诊断事实来源","Executive Findings":"核心发现","Top observations aggregate telemetry":"基于聚合遥测数据的主要观察结果","Notebook Index":"笔记本目录","Jump to section":"跳转到章节","Evidence Calls":"证据调用","No matching calls":"没有匹配的调用","No loaded aggregate call rows match diagnostic section.":"已加载的聚合调用中，没有记录与此诊断章节匹配。","Static fallback facts":"静态回退事实","Static aggregate fallback":"静态聚合回退数据","Diagnostic fact type and name are required.":"必须提供诊断事实的类型和名称。","Diagnostic facts require localhost dashboard server.":"诊断事实需要本机仪表盘服务器。","Diagnostic facts require localhost dashboard API token.":"诊断事实需要本机仪表盘 API 令牌。","Diagnostic snapshot refresh":"诊断快照刷新","Diagnostic refresh status":"诊断刷新状态","Structured Diagnostic Facts":"结构化诊断事实","Top Diagnostic Facts":"主要诊断事实","top diagnostic facts":"主要诊断事实","Top Facts":"主要事实","Tool and Function Activity":"工具与函数活动","Compaction Activity":"上下文压缩活动",Compactions:"上下文压缩",compactions:"上下文压缩",Tools:"工具",tools:"工具","Diagnostic fact modules":"诊断事实模块","Sort facts":"事实排序","Sort diagnostic facts":"诊断事实排序","Sort diagnostic facts ascending":"按升序排列诊断事实","Sort diagnostic facts descending":"按降序排列诊断事实","Uncached input":"未缓存输入","Total tokens":"总token数","Cached input":"缓存输入","Output tokens":"输出token数","Largest call":"最大调用","Associated calls":"关联调用","Cache %":"缓存占比","Latest time":"最近时间","Fact name":"事实名称","uncached input":"未缓存输入","total tokens":"总token数","cached input":"缓存输入","output tokens":"输出token数","largest call":"最大调用","associated calls":"关联调用","cache %":"缓存占比","latest time":"最近时间",occurrences:"出现次数","fact name":"事实名称",uncached:"未缓存",cache:"缓存",fact:"事实",unknown:"未知",uncategorized:"未分类","No diagnostic facts matched the current aggregate data.":"当前聚合数据中没有匹配的诊断事实。","Loading more facts...":"正在加载更多事实…","Load more live facts":"加载更多实时事实","Diagnostic Fact Calls":"诊断事实关联调用","Diagnostic fact calls":"诊断事实关联调用","No fact selected":"尚未选择事实","No loaded rows":"没有已加载记录","Sort calls":"调用排序","Sort diagnostic fact calls":"诊断事实关联调用排序","Sort diagnostic fact calls ascending":"按升序排列诊断事实关联调用","Sort diagnostic fact calls descending":"按降序排列诊断事实关联调用","Input tokens":"输入token数","Reasoning tokens":"推理token数","Loading fact calls...":"正在加载事实关联调用…","Load more fact calls":"加载更多事实关联调用","Loading rows...":"正在加载记录…","Load more dashboard rows":"加载更多仪表盘记录","Load all dashboard rows":"加载全部仪表盘记录","No aggregate calls are associated with the selected diagnostic fact.":"没有聚合调用与所选诊断事实关联。","Static aggregate fact calls":"静态聚合事实关联调用","Waiting for live diagnostics":"正在等待实时诊断数据","Loading calls for selected fact...":"正在加载所选事实的关联调用…","Select a diagnostic fact":"请选择一项诊断事实","Open associated aggregate calls in the full Call Investigator.":"在完整的调用分析器中打开关联的聚合调用。","Diagnostics Snapshot Matrix":"诊断快照矩阵","Refreshing diagnostic snapshots":"正在刷新诊断快照","Loading diagnostic snapshots":"正在加载诊断快照","Refreshing diagnostic snapshots...":"正在刷新诊断快照…","Loading diagnostic snapshots...":"正在加载诊断快照…","Refresh snapshots":"刷新快照",Refreshing:"正在刷新",Reload:"重新加载",Reloading:"正在重新加载","Static fallback snapshots":"静态回退快照","Live diagnostic snapshots unavailable:":"实时诊断快照不可用：","No aggregate rows in this snapshot.":"此快照中没有聚合记录。","Show fewer":"收起",Overview:"概览","Tool Output":"工具输出","Git Interactions":"Git 交互","File Reads":"文件读取","File Modifications":"文件修改","Read Productivity":"读取成效",Concentration:"集中度","What Is Driving Usage?":"是什么在推高用量？","Usage Drain":"用量消耗","Usage rows":"用量记录","Cache ratio":"缓存比率","Distinct aggregate thread labels":"聚合数据中的不同线程标签数","Distinct model labels":"不同模型标签数","Function calls":"函数调用","Function outputs":"函数输出","Original tokens":"原始token数","Shell calls":"Shell 调用",Roots:"根命令数","Missing root":"缺失根命令","No child commands":"没有子命令","Git calls":"Git 调用","Git commands":"Git 命令","GitHub CLI":"GitHub CLI","Read events":"读取事件",Readers:"读取工具数",Events:"事件数","Unique paths":"唯一路径数","Largest event":"最大事件","Modification events":"修改事件","Modified later":"后续被修改",Rate:"比率","Top thread share":"头部线程占比",Groups:"分组数","largest impact":"影响最大","Estimated cost":"预估成本","Usage credits":"点数","Computed unknown time":"计算时间未知","Aggregate fallback module":"聚合回退模块","Report pack":"报告包","Reports pack":"报告包","Database error while building report pack":"构建报告包时发生数据库错误","Live report pack requires the localhost dashboard server.":"实时报告包需要本机仪表盘服务器。","Live report pack requires localhost dashboard API token.":"实时报告包需要本机仪表盘 API 令牌。","Reports pack returned an unsupported schema.":"报告包返回了不受支持的数据结构。","Live localhost report pack":"本机实时报告包","Loaded dashboard aggregates":"已加载的仪表盘聚合数据","Server timestamp unavailable":"服务器时间戳不可用","Current dashboard snapshot":"当前仪表盘快照","Refreshing selected report…":"正在刷新所选报告…","Selected report refreshed":"所选报告已刷新","Focused local research snapshots with their methods, limits, and investigator-linked evidence.":"聚焦本地数据的研究快照，附带分析方法、适用限制和可跳转至调用分析器的证据。","Export selected":"导出所选报告","Live report refresh requires the localhost server.":"实时刷新报告需要本机服务器。","Refresh report":"刷新报告","Live refresh unavailable":"实时刷新不可用","Loading full-scope report pack":"正在加载完整范围的报告包","Live report pack":"实时报告包","No report available":"暂无可用报告","No owner":"无负责人","Select report":"选择报告","Report evidence":"报告证据","Report Evidence Calls":"报告证据调用","Investigator linked":"已关联调用分析器","Research Notes":"研究说明","Interpretation boundary":"解读边界",Method:"方法",Caveat:"限制说明","Evidence privacy":"证据隐私","Raw context is not included here; inspect an explicitly linked call in Call Investigator.":"此处不包含原始上下文；如需查看，请在调用分析器中打开明确关联的调用。","Generation Metadata":"生成元数据","Provenance for this view":"此视图的数据来源",Source:"来源",Generated:"生成时间",Schema:"数据结构",Matched:"匹配记录","dashboard aggregate model":"仪表盘聚合模型","Static mode: using the loaded aggregate snapshot.":"静态模式：正在使用已加载的聚合快照。","Loading live report pack…":"正在加载实时报告包…","Refreshing live report pack…":"正在刷新实时报告包…","Cached live report pack is stale; refresh is available.":"缓存的实时报告包已过期，可以刷新。","Live report pack ready.":"实时报告包已就绪。","No loaded aggregate calls match this selected report.":"已加载的聚合调用中，没有记录与所选报告匹配。","Selected report evidence calls":"所选报告的证据调用","loaded rows":"条已加载记录","Est. Cost":"预估成本","Speed proxy":"速度代理指标","Filter fast-tagged and low-effort calls, then order by shortest duration and credit impact.":"筛选带有快速标签或低推理强度的调用，再按耗时从短到长及点数影响排序。","Aggregate timing cannot distinguish model latency from tool, network, or queue time.":"聚合耗时无法区分模型延迟、工具耗时、网络耗时或排队时间。","Fast/low-effort candidates · shortest duration first · top 8":"快速/低推理强度候选 · 耗时最短优先 · 前 8 项","Cost concentration":"成本集中度","Rank aggregate calls by estimated cost, breaking ties with total token volume.":"按预估成本对聚合调用排序，成本相同时以token总量决定顺序。","Estimated local cost may differ from billing and excludes costs not represented in loaded rows.":"本地预估成本可能与实际账单不同，且不包含已加载记录未覆盖的费用。","Highest estimated cost · token volume tie-break · top 8":"预估成本最高优先 · token量决定同分顺序 · 前 8 项","Usage trajectory":"用量走势","Rank aggregate calls by estimated Codex credit impact and compare the selected time series.":"按预估的 Codex 点数影响对聚合调用排序，并对比所选时间序列。","Allowance and credit projections are local observations, not universal account limits.":"额度和点数预测仅基于本地观察，并非适用于所有账户的统一上限。","Highest credit impact · token volume tie-break · top 8":"点数影响最高优先 · token量决定同分顺序 · 前 8 项",Percent:"百分比","Under 5s":"5 秒以内","5-15s":"5–15 秒","15-30s":"15–30 秒","30s+":"30 秒以上","Selected report":"所选报告","selected report":"所选报告","Speed proxy evidence":"速度代理指标证据","Cost concentration evidence":"成本集中度证据","Usage trajectory evidence":"用量走势证据","Raw context is available only through an explicitly linked Call Investigator record.":"只有通过明确关联的调用分析器记录才能查看原始上下文。","Use left and right arrow keys to inspect chart values, or switch to the table for exact values.":"使用左右方向键查看图表数值，或切换到表格查看精确值。","Observed period":"观察周期","Weekly remaining":"每周剩余用量","Observed drain":"观察到的消耗","Predicted baseline":"预测基线","Usage remaining":"剩余用量","Allowance guide":"额度参考线","Loaded-row baseline":"已加载记录基线","Projected weekly credits":"预计每周点数","Loaded-row credits":"已加载记录点数","Cost Curves":"成本曲线","Usage Drain Model":"用量消耗模型","Fast Mode Proxy":"快速模式代理指标","Weekly Credits":"每周点数","Usage Remaining":"剩余用量","Allowance Change":"额度变化","Estimated cost concentration by loaded aggregate thread.":"按已加载聚合线程统计的预估成本集中度。","Highest estimated credit-impact calls from loaded aggregate rows.":"已加载聚合记录中，预估点数影响最高的调用。","Low-effort and fast-call candidates inferred from aggregate rows.":"根据聚合记录推断出的低推理强度和快速调用候选。","Cache Misses (Large Inputs)":"缓存未命中（大输入）","High Model Effort":"高模型推理强度","Tool Output Volume":"工具输出量","Cache Behavior":"缓存行为","Thread Efficiency":"线程效率","Tool And Command Activity":"工具与命令活动","Projected weekly credits declined from the baseline and partially recovered in the latest window.":"预计每周点数较基线下降，并在最近一个窗口中部分回升。","Cache hit rate is healthy overall, with spikes aligned to large cache misses and cold resumes.":"总体缓存命中率良好，波动峰值与大规模缓存未命中及冷恢复相吻合。","Long threads account for most estimated cost and are the clearest optimization target.":"长线程占据大部分预估成本，是最明确的优化目标。","Command volume is stable with a slight upward trend; read and shell commands dominate.":"命令量总体稳定但略有上升，其中读取命令和 Shell 命令占主导。","Plan-specific weekly credits, trend lines, and confidence intervals.":"按套餐展示每周点数、趋势线和置信区间。","Observed remaining usage over time with reset handling.":"展示经过重置处理的剩余用量时间变化。","Cumulative estimated cost by thread and concentration metrics.":"按线程统计累计预估成本及集中度指标。","Actual-vs-predicted drain and feature group comparisons.":"实际与预测用量消耗及特征分组对比。","Candidate detection, speedup histogram, and confidence breakdowns.":"候选检测、加速幅度直方图和置信度明细。","Week-to-week allowance estimate changes with careful language.":"以审慎表述展示逐周额度估算变化。","Local configuration":"本地配置",Settings:"设置","Inspect dashboard behavior and configuration truth without changing server-owned settings.":"查看仪表盘行为和实际配置状态，不会修改由服务器管理的设置。","Live API available":"实时 API 可用","Static snapshot":"静态快照","Content access enabled":"内容访问已启用","Content access gated":"内容访问受限","Settings sections":"设置分类",Data:"数据","Loaded history and local runtime state.":"已加载的历史记录和本地运行状态。",Estimates:"估算","Pricing and allowance inputs used for local estimates.":"用于本地估算的定价与额度输入。","Content Access":"内容访问","Privacy boundaries and explicit raw-context gates.":"隐私边界与显式原始上下文访问门控。",Application:"应用","Dashboard refresh, API, and language visibility.":"仪表盘刷新、API 与语言显示状态。","Source Health":"数据源健康状态","Configuration and parser diagnostics.":"配置与解析器诊断。","Loaded Data":"已加载数据","Served shell payload":"服务器提供的外壳载荷","Embedded payload":"内嵌载荷","Data window":"数据窗口","Evidence rows":"证据记录","Session scope":"会话范围","Include archived":"包含已归档会话","Usage index":"用量索引","served shell":"服务器外壳数据","embedded payload":"内嵌载荷","Estimate Inputs":"估算输入","Read-only local configuration":"只读本地配置",Pricing:"定价",Allowance:"额度","Rate card":"费率表",Loaded:"已加载","Not loaded":"未加载","local pricing config":"本地定价配置","local allowance config":"本地额度配置","Allowance Windows":"额度窗口","Allowance config":"额度配置",Usage:"用量",Window:"窗口","No allowance windows configured":"尚未配置额度窗口","Observed usage available":"可用观察用量数据","Configured allowance window":"已配置的额度窗口","Manual allowance windows and live observed usage":"手动额度窗口与实时观察用量","Privacy Boundary":"隐私边界","Payload mode":"载荷模式","Project metadata":"项目元数据","Raw context":"原始上下文","Explicit localhost request, selected call only":"仅通过本机显式请求访问所选调用","Disabled until context API is enabled":"启用上下文 API 前保持禁用","Live requests":"实时请求","Local API token present":"已提供本地 API 令牌","Content Access Rules":"内容访问规则","Local and explicit":"仅限本地且必须显式触发","Aggregate payloads avoid prompts, assistant text, and raw tool output.":"聚合载荷不包含提示词、助手文本和原始工具输出。","Raw context actions remain gated behind explicit Call Investigator controls.":"原始上下文操作仍须通过调用分析器中的显式控件触发。","Live refresh and context requests stay local and require the dashboard API token.":"实时刷新和上下文请求仅在本机进行，并且需要仪表盘 API 令牌。","Dashboard Runtime":"仪表盘运行状态","Data connection":"数据连接",Enabled:"已启用",Paused:"已暂停","Interface language":"界面语言","English (en)":"英语（en）","Configuration Checks":"配置检查","Configuration and ingestion facts":"配置与数据导入状态","Pricing snapshot":"定价快照",Configured:"已配置","Not configured":"未配置","Parser diagnostics":"解析器诊断","No parser warnings":"没有解析器警告","Usage deduplication":"用量去重","Normal metadata":"普通元数据","aggregate-only snapshot":"仅聚合数据快照","Last 24 hours":"过去 24 小时","Thread concentration":"线程集中度","Review whether this thread still needs its full accumulated context.":"检查此线程是否仍需要保留全部累积上下文。","Model mix":"模型构成","Compare model choice against the actual work in the heaviest calls.":"对照最重调用的实际任务，检查模型选择是否合适。","Low cache reuse":"缓存复用率低","Look for repeated file reads, cold resumes, or broad context restatement.":"检查是否存在重复读取文件、冷恢复或大范围重述上下文。","Reasoning-heavy output":"推理输出占比较高","Check whether effort settings match task complexity.":"检查推理强度设置是否与任务复杂度匹配。","Subagent activity":"子代理活动","Separate direct work from delegated work when explaining usage growth.":"解释用量增长时，应区分直接执行与委派给子代理的工作。","Context pressure":"上下文压力","Inspect high-context threads before deciding whether to split work.":"决定是否拆分任务前，先检查上下文占用较高的线程。","Command activity":"命令活动","Use the Commands panel to see whether repetitive tooling is driving usage.":"使用“命令”面板检查重复工具操作是否在推高用量。","Tool output volume":"工具输出量","Trim noisy command output or use narrower file reads where possible.":"尽量精简冗长的命令输出，或缩小文件读取范围。","Visible usage movement":"可见用量变化","Use Usage Drain for allowance projection caveats and trend context.":"在“用量消耗”中查看额度预测的限制说明和趋势背景。","Top thread by tokens":"token量最高的线程","Compare this thread against newer handoff threads before changing workflow.":"调整工作流前，将此线程与较新的交接线程进行比较。","Top model bucket":"token量最高的模型分组","Check whether the model choice matches the work that dominates usage.":"检查模型选择是否与占用量最大的工作相匹配。","Top effort bucket":"token量最高的推理强度分组","Compare effort mix with task complexity before changing defaults.":"更改默认值前，对照任务复杂度检查推理强度构成。","Uncached input share":"未缓存输入占比","High uncached share is a good place to look for repeated context loading.":"未缓存占比较高时，应优先排查重复加载上下文。","Top review signal":"首要复核信号","unknown thread":"未知线程","Large calls produced little output":"大型调用的输出很少","Large input/context usage with low output is a strong candidate for cold resumes, stale thread continuation, or low-value continuation.":"输入或上下文用量很大但输出很少，通常提示冷恢复、继续使用陈旧线程或低价值续接。","Open the top calls, check whether a smaller fresh thread or preserved handoff would avoid resending large context.":"打开排名靠前的调用，检查改用较小的新线程或保留交接摘要能否避免重复发送大量上下文。","Aggregate token/activity counts only; no raw fragments or command output.":"仅包含聚合token数和活动计数，不含原始片段或命令输出。","The aggregate report cannot prove why output was low without a thread trace or explicit raw-context inspection.":"缺少线程轨迹或显式原始上下文检查时，聚合报告无法证明输出偏低的具体原因。","Repeated shell command churn":"Shell 命令反复空转","Repeated shell roots, failures, or adjacent retries can waste turns and inflate tool-output/context pressure.":"反复使用相同 Shell 根命令、持续失败或相邻重试会浪费轮次，并加剧工具输出和上下文压力。","Turn repeated probes into a small script, narrower command, or targeted test command.":"将重复探测整理成小型脚本、范围更窄的命令或有针对性的测试命令。","Command roots and bounded labels only; raw command output is omitted.":"仅包含根命令和受限标签，省略原始命令输出。","Strict aggregate evidence cannot always recover the exact shell intent or full command arguments.":"严格聚合证据不一定能还原确切的 Shell 意图或完整命令参数。","Repeated file rediscovery":"重复查找同一文件","Repeated safe file identities can indicate the agent keeps rediscovering the same context instead of using a durable summary or targeted helper.":"反复出现相同的安全文件标识，可能说明代理一直在重新查找同一上下文，而没有使用持久摘要或专用辅助工具。","Summarize stable facts into project docs or build a small helper command for recurring lookups.":"将稳定信息整理到项目文档中，或为重复查询构建小型辅助命令。","Safe path hashes, basenames, and aggregates only; full paths are omitted.":"仅包含安全的路径哈希、文件基本名和聚合数据，省略完整路径。","The report can rank repeated safe file identities, but cannot tell whether each reread was necessary without task intent.":"报告可以对重复的安全文件标识排序，但缺少任务意图时无法判断每次重读是否必要。","Ranked aggregate usage recommendations":"已排序的聚合用量建议","Existing recommendation scoring combines aggregate cost, cache, context, and pricing signals.":"现有建议评分综合了聚合成本、缓存、上下文和定价信号。","Start with the highest recommendation score, then verify with the specific diagnostic tool.":"从评分最高的建议开始，再使用相应诊断工具进行验证。","Aggregate recommendations only; no prompt or tool-output text.":"仅包含聚合建议，不含提示词或工具输出文本。","Recommendation scores do not know whether an expensive call produced high-value work.":"建议评分无法判断高成本调用是否产出了高价值结果。","Local Codex logs only; this is not an official OpenAI usage ledger.":"仅基于本地 Codex 日志，并非 OpenAI 官方用量账本。","Archived sessions are excluded unless include_archived is true.":"除非 include_archived 为 true，否则不包含已归档会话。","Run weekly evidence-graded allowance diagnostics before interpreting 5-hour noise.":"解读 5 小时窗口的噪声前，先运行带证据等级的每周额度诊断。","Create strict local evidence bundle when the user wants to share allowance-change evidence.":"用户需要分享额度变化证据时，创建严格隐私模式的本地证据包。","Weekly allowance evidence is the primary signal; 5-hour counters are rolling-window context.":"每周额度证据是主要信号；5 小时计数器仅提供滚动窗口背景。","Confirm index freshness and row counts.":"确认索引新鲜度和记录数。","Rank projects, threads, models, or dates depending on the user's next question.":"根据用户接下来的问题，对项目、线程、模型或日期进行排序。","Open dashboard-shaped evidence cards for top aggregate drivers.":"打开与仪表盘一致的证据卡片，查看主要聚合驱动因素。","No strong local signal at default thresholds":"默认阈值下没有明显的本地信号","The current aggregate diagnostics did not find a clear candidate at the default threshold.":"当前聚合诊断在默认阈值下没有发现明确候选。","Lower thresholds, widen the time window, include archived sessions, or inspect top aggregate calls.":"降低阈值、扩大时间窗口、纳入已归档会话，或检查排名靠前的聚合调用。","No raw context needed for this follow-up.":"此后续检查无需原始上下文。","No supported aggregate signal was found at the selected thresholds.":"所选阈值下未发现受支持的聚合信号。"},hi=[{pattern:/^Live (.+): ([\d,.]+)$/u,replace:(e,t,a)=>`实时${E(t)}：${a}`},{pattern:/^Live (.+) unavailable: (.+)$/u,replace:(e,t,a)=>`实时${E(t)}不可用：${a}`},{pattern:/^(.+) module - ([\d,.]+) loaded \/ ([\d,.]+) matched - (.+)$/u,replace:(e,t,a,n,r)=>`${E(t)}模块 · 已加载 ${a} / 匹配 ${n} · ${Qt(r)}`},{pattern:/^(.+) module - ([\d,.]+) matched - (.+)$/u,replace:(e,t,a,n)=>`${E(t)}模块 · 匹配 ${a} 条 · 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po(e,t=3){const n=fo([e.signal,...e.efficiencyFlags]).map((r,s)=>({key:`${r}-${s}`,label:dr(r),shortLabel:mo(r)}));return{visible:n.slice(0,t),hidden:n.slice(t)}}function go({call:e}){const t=wa(),{visible:a,hidden:n}=po(e);if(!a.length)return c.jsx("span",{className:"muted",children:"None"});const r=a.map(o=>({...o,label:t.translateText(o.label),shortLabel:t.translateText(o.shortLabel)})),s=n.map(o=>({...o,label:t.translateText(o.label),shortLabel:t.translateText(o.shortLabel)})),i=s.map(o=>o.label).join("、");return c.jsxs("span",{className:"flags compact-flags","aria-label":t.language==="zh-Hans"?`信号：${[...r,...s].map(o=>o.label).join("、")}`:`Signals: ${[...a,...n].map(o=>o.label).join(", ")}`,children:[r.map(o=>c.jsx("span",{className:"flag signal-puck",title:o.label,children:o.shortLabel},o.key)),s.length?c.jsxs("span",{className:"flag signal-puck more",title:i,children:["+",s.length]}):null]})}function fo(e){const t=new Set;return e.map(a=>a.trim()).filter(a=>a&&a!=="aggregate").filter(a=>{const n=a.toLowerCase();return t.has(n)?!1:(t.add(n),!0)})}function dr(e){return e.replace(/[-_]+/g," ").replace(/\b\w/g,t=>t.toUpperCase())}function mo(e){const t=e.toLowerCase().replace(/[_\s]+/g,"-"),a={"cache-drop":"CACHE","cache-risk":"CACHE","context-bloat":"CTX","context-heavy":"CTX","elevated-context":"CTX","elevated-context-use":"CTX","estimated-pricing":"EST","expensive-low-output-call":"LO","high-context-use":"CTX","high-cost":"$","high-estimated-cost":"$","high-reasoning-share":"RSN","large-thread":"BIG","low-cache":"CACHE","low-cache-reuse":"CACHE","low-output":"LO","pricing-gap":"PRICE","reasoning-spike":"RSN","subagent-attribution":"SUB"};if(a[t])return a[t];const n=dr(e).split(/\s+/).filter(Boolean);return n.length?n.length===1?n[0].slice(0,4).toUpperCase():n.slice(0,3).map(r=>r[0]).join("").toUpperCase():"?"}function gd(e,t=""){return`Open call row in investigator for ${ur(e,t)}`}function fd(e){return e.latestCallId?`Open thread row latest call in investigator for ${e.name}`:`No loaded call available for ${e.name}`}function md({onOpenInvestigator:e,onCopyCallLink:t,labelPrefix:a=""}){return{id:"investigate",header:"Investigate",size:260,enableSorting:!1,cell:n=>c.jsx(vo,{call:n.row.original,labelPrefix:a,onCopyCallLink:t,onOpenInvestigator:e})}}function vo({call:e,labelPrefix:t,onCopyCallLink:a,onOpenInvestigator:n}){const r=wa(),s=r.t("button.open_investigator","Open investigator"),i=r.t("button.copy_link","Copy link"),o=ur(e,t);return c.jsxs("div",{className:"table-action-group",children:[c.jsxs("button",{className:"table-action-button",type:"button","aria-label":`${s} for ${o}`,onKeyDown:Nt,onClick:u=>{u.stopPropagation(),n(e.id)},children:[c.jsx(Wn,{size:14}),s]}),a?c.jsxs("button",{className:"table-action-button",type:"button","aria-label":`${i} for ${o}`,onKeyDown:Nt,onClick:u=>{u.stopPropagation(),a(e.id)},children:[c.jsx(ma,{size:14}),i]}):null]})}function 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diff --git a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/CacheContextPage.js b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/CacheContextPage.js
index 5bbe6c67..8ebdf4fc 100644
--- a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/CacheContextPage.js
+++ b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/CacheContextPage.js
@@ -1 +1 @@
-import{r as f,j as a}from"./dashboard-react.js";import{L as B}from"./LineChart.js";import{D as H}from"./DataTable.js";import{o as I,M as Q}from"./overviewQueries.js";import{S as T,P as b}from"./Panel.js";import{P as U}from"./PageLoadProgress.js";import"./Primitives.js";import{k as O,l as z,f as k,a as v,p as w,n as _,e as V,g as G,d as J,m as $,s as L,S as X,b as Y}from"./App.js";import{u as K}from"./useQuery.js";import{u as Z}from"./useInfiniteQuery.js";import{t as q,b as ee}from"./exploreQueries.js";import{t as ae}from"./threadSummaryAdapter.js";import"./index2.js";import"./gauge.js";import"./queryOptions.js";import"./dashboardRouter.js";import"./router.js";import"./useBaseQuery.js";import"./infiniteQueryOptions.js";function se(e){var N,S,x,F;const s=e.enabled&&!e.runtime.fileMode&&!!e.runtime.apiToken,t=K({...I({runtime:e.runtime,includeArchived:e.includeArchived,since:e.scopeSince??void 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summaries",s,n),...R?[D("Selected thread calls",s,l)]:[]],C=O(g.map(i=>i.status)),p=t.error??n.error??l.error,r=g.find(i=>i.status==="error");return{cacheSeries:u?ne(u.rows):e.model.cacheSeries,cards:u?ce(u.rows):e.model.cards.slice(2,5),heatmap:c?d.map(i=>({thread:i.name,values:[i.cachePct],labels:["All time"]})):e.model.cacheHeatmap,selectedCalls:((S=l.data)==null?void 0:S.rows)??y,selectedThread:h,threads:d,totalThreads:((F=(x=n.data)==null?void 0:x.pages[0])==null?void 0:F.totalMatchedRows)??d.length,usingFocusedEndpoints:c,progress:{active:s&&(t.isFetching||n.isFetching||l.isFetching),completed:C.ready,total:C.total,error:p?`${(r==null?void 0:r.label)??"Focused evidence"} unavailable: ${te(p)}`:null,modules:g,updating:g.some(i=>i.status==="updating")}}}function D(e,s,t){return{label:e,status:z({enabled:s,hasData:!!t.data,isError:t.isError,isFetching:t.isFetching,isPending:t.isPending})}}function te(e){return e instanceof Error?e.message:String(e)}function ne(e){return _(e.map(s=>({timestamp:Date.parse(s.groupKey)||Date.parse(s.latestEvent),input:s.inputTokens,cached:s.cachedInputTokens,output:s.outputTokens,cost:0}))).cacheSeries}function ce(e){const s=e.reduce((n,o)=>({calls:n.calls+o.modelCalls,input:n.input+o.inputTokens,cached:n.cached+o.cachedInputTokens,uncached:n.uncached+o.uncachedInputTokens,tokens:n.tokens+o.totalTokens}),{calls:0,input:0,cached:0,uncached:0,tokens:0}),t=s.input>0?s.cached/s.input*100:0;return[{label:"Total Calls",value:k(s.calls),trend:"complete selected scope",detail:"server-side aggregate",tone:"blue"},{label:"Cache Reuse",value:w(t),trend:t>=80?"healthy cache reuse":"review cache reuse",detail:`${v(s.cached)} cached input`,tone:t>=80?"green":"orange"},{label:"Uncached Input",value:v(s.uncached),trend:`${v(s.tokens)} total tokens`,detail:"complete selected scope",tone:"purple"}]}function re(e,s){return s?e.filter(t=>oe(t.thread,s.name)).sort((t,n)=>Date.parse(n.rawTime||n.time)-Date.parse(t.rawTime||t.time)):[]}function 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recommendations."})]}),a.jsxs("div",{className:"toolbar",children:[a.jsx(T,{label:l.usingFocusedEndpoints?"Full-scope endpoints":"Snapshot fallback",tone:l.usingFocusedEndpoints?"green":"orange"}),a.jsx(T,{label:"Context safe",tone:"blue"})]})]}),a.jsx(U,{active:l.progress.active,completed:l.progress.completed,total:l.progress.total,label:"Loading cache and context evidence",error:l.progress.error,modules:l.progress.modules,updating:l.progress.updating}),a.jsx("div",{className:"metric-grid span-all",children:l.cards.map(r=>a.jsx(Q,{card:r},r.label))}),a.jsx(b,{title:"Cache Hit Rate & Context Window Over Time",subtitle:"Cache reuse and context pressure",children:a.jsx(B,{series:[...l.cacheSeries,e.usageRemainingSeries[0]].filter(Boolean),yLabel:"Percent",valueFormatter:r=>`${r}%`})}),a.jsx(b,{title:"Cache Reuse Heatmap",subtitle:p.length?`${p.length} cache windows`:"No cache heatmap rows",children:p.length?a.jsx("div",{className:"heatmap-scroll",tabIndex:0,"aria-label":"Scrollable cache reuse heatmap",children:a.jsxs("div",{className:"heatmap",role:"table","aria-label":"Cache reuse heatmap",style:{"--heatmap-columns":p.length},children:[a.jsxs("div",{className:"heatmap-head",role:"row",children:[a.jsx("span",{className:"sticky-column",role:"columnheader",children:"Thread"}),p.map(r=>a.jsx("span",{role:"columnheader",children:r},r))]}),l.heatmap.map(r=>a.jsxs("div",{className:"heatmap-row",role:"row",children:[a.jsx("strong",{className:"sticky-column",role:"rowheader",children:r.thread}),p.map((N,S)=>{const x=r.values[S];return a.jsx("span",{role:"cell",style:{"--intensity":(x??0)/100},children:typeof x=="number"?`${x}%`:"-"},`${r.thread}-${N}`)})]},r.thread))]})}):a.jsx("p",{className:"empty-state",children:"No cache heatmap rows in the current aggregate snapshot."})}),a.jsxs(b,{title:"Threads Overview",subtitle:u?`Selected ${u.name}: ${w(u.cachePct)} cache`:"Cold resume and cache efficiency signals",className:"span-all",action:a.jsx(T,{label:"Hover previews; rows 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Profile"}),a.jsxs("span",{children:[e.coldResumeRisk," risk"]})]}),a.jsxs("div",{className:"evidence-list",children:[a.jsxs("span",{children:["Turns ",a.jsx("strong",{children:k(e.turns)})]}),a.jsxs("span",{children:["Tokens ",a.jsx("strong",{children:v(e.totalTokens)})]}),a.jsxs("span",{children:["Cache hit ",a.jsx("strong",{children:w(e.cachePct)})]}),a.jsxs("span",{children:["Est. cost ",a.jsx("strong",{children:$(e.cost)})]}),a.jsxs("span",{children:["Cost/call ",a.jsx("strong",{children:$(e.costPerCall)})]})]})]}),a.jsxs("div",{className:"finding-module",children:[a.jsxs("div",{className:"section-heading compact",children:[a.jsx("h3",{children:"Cache Windows"}),a.jsx("span",{children:s?"Weekly reuse":"No heatmap row"})]}),s?a.jsx("div",{className:"cache-window-strip","aria-label":`Cache windows for ${e.name}`,children:ge(s,t).map((c,d)=>{const h=s.values[d];return a.jsxs("span",{style:{"--intensity":(h??0)/100},children:[a.jsx("small",{children:c}),a.jsx("strong",{children:typeof h=="number"?`${h}%`:"-"})]},`${e.name}-window-${c}`)})}):a.jsx("p",{className:"empty-state",children:"No weekly cache heatmap row matches this selected thread."})]}),a.jsxs("div",{className:"finding-module",children:[a.jsxs("div",{className:"section-heading compact",children:[a.jsx("h3",{children:"Thread Calls"}),a.jsx("span",{children:n.length?`${n.length} loaded`:"No loaded calls"})]}),n.length?a.jsx("ol",{className:"thread-mini-timeline",children:n.slice(0,5).map(c=>a.jsxs("li",{className:"thread-call-row has-row-action",tabIndex:0,"aria-label":`Open investigator for cache thread call ${c.thread} ${c.model}`,onClick:()=>o(c.id),onKeyDown:d=>{(d.key==="Enter"||d.key===" ")&&(d.preventDefault(),o(c.id))},children:[a.jsx("span",{children:c.time}),a.jsxs("strong",{children:[c.model," / ",c.effort]}),a.jsxs("em",{children:[v(c.totalTokens)," tokens - ",w(c.cachedPct)," cache"]}),a.jsxs("div",{className:"thread-call-actions table-action-group",children:[a.jsxs("button",{className:"table-action-button",type:"button","aria-label":`Open investigator for cache thread call ${c.thread} ${c.model}`,onKeyDown:L,onClick:d=>{d.stopPropagation(),o(c.id)},children:[a.jsx(X,{size:14}),"Open"]}),a.jsxs("button",{className:"table-action-button",type:"button","aria-label":`Copy link for cache thread call ${c.thread} ${c.model}`,onKeyDown:L,onClick:d=>{d.stopPropagation(),m(c.id)},children:[a.jsx(Y,{size:14}),"Copy"]})]})]},c.id))}):a.jsx("p",{className:"empty-state",children:"No loaded aggregate call rows match this selected thread."})]}),a.jsxs("div",{className:"finding-module",children:[a.jsx("h3",{children:"Diagnosis Basis"}),a.jsxs("ul",{className:"compact-list",children:[a.jsxs("li",{children:["Risk: ",e.coldResumeRisk," cold-resume score"]}),a.jsxs("li",{children:["Cache: ",w(e.cachePct)," hit rate; action threshold below 35%"]}),a.jsxs("li",{children:["Cost: ",$(e.costPerCall)," per call; inspect threshold above $1.00"]}),a.jsxs("li",{children:["Evidence: ",n.length," loaded calls, ",s?`${s.values.length} cache windows`:"no heatmap row"]})]})]}),a.jsxs("div",{className:"finding-module",children:[a.jsx("h3",{children:"Suggested Actions"}),a.jsx("ul",{className:"compact-list",children:ie(e).map(c=>a.jsx("li",{children:c},c))})]})]})}):a.jsx("aside",{className:"side-panel",children:a.jsx(b,{title:"Selected Thread Diagnosis",subtitle:"No matching thread",children:a.jsx("p",{className:"empty-state",children:"No grouped thread is available in the current aggregate snapshot."})})})}function ie(e){const s=[];return e.coldResumeRisk==="High"&&s.push("Summarize before the next work session."),e.cachePct<35&&s.push("Split completed topics or reduce repeated uncached context."),e.costPerCall>1&&s.push("Open a related call and inspect whether model effort was justified."),s.length||s.push("Keep the thread warm and continue monitoring cache reuse."),s}function de(e,s){return s?e.filter(t=>A(t.thread,s.name)).sort(pe):[]}function he(e){const s=M();return s&&e.some(t=>t.name===s)?s:null}function M(){var e;return((e=new URLSearchParams(window.location.search).get("cache_thread"))==null?void 0:e.trim())||null}function me(e){const s=he(e);return s?e.find(t=>t.name===s)??null:null}function ue(e){const s=new URL(window.location.href);s.searchParams.set("view","cache-context"),s.searchParams.set("cache_thread",e),window.history.replaceState(null,"",s)}function pe(e,s){return Date.parse(s.rawTime||s.time)-Date.parse(e.rawTime||e.time)}function A(e,s){const t=e.trim(),n=s.trim();return t===n||t.startsWith(n)||n.startsWith(t)}function E(e){const s=e.find(n=>{var o;return(o=n.labels)==null?void 0:o.length}),t=e.reduce((n,o)=>{var m;return Math.max(n,o.values.length,((m=o.labels)==null?void 0:m.length)??0)},0);return Array.from({length:t},(n,o)=>{var m;return((m=s==null?void 0:s.labels)==null?void 0:m[o])??`Window ${o+1}`})}function ge(e,s){var n;if((n=e.labels)!=null&&n.length)return E([e]);const t=Math.max(e.values.length,s.length);return Array.from({length:t},(o,m)=>s[m]??`Window ${m+1}`)}export{Ae as CacheContextPage,Me as cacheContextCallsForCurrentUrl};
+import{r as b,j as a}from"./dashboard-react.js";import{k as I,l as H,f as T,a as w,p as y,n as Q,u as M,e as U,g as O,d as z,m as P,s as L,S as _,b as V}from"./App.js";import{L as G}from"./LineChart.js";import{D as J}from"./DataTable.js";import{o as X,M as Y}from"./overviewQueries.js";import{S as D,P as C}from"./Panel.js";import{P as Z}from"./PageLoadProgress.js";import"./Primitives.js";import{u as K}from"./useQuery.js";import{u as q}from"./useInfiniteQuery.js";import{t as ee,b as ae}from"./exploreQueries.js";import{t as se}from"./threadSummaryAdapter.js";import"./dashboardRouter.js";import"./router.js";import"./index2.js";import"./gauge.js";import"./queryOptions.js";import"./useBaseQuery.js";import"./infiniteQueryOptions.js";function te(e){var l,$,k,j;const s=e.enabled&&!e.runtime.fileMode&&!!e.runtime.apiToken,t=K({...X({runtime:e.runtime,includeArchived:e.includeArchived,since:e.scopeSince??void 0,sourceKey:e.sourceKey,sourceRevision:e.sourceRevision}),enabled:s,placeholderData:d=>d}),n=q({...ee({runtime:e.runtime,includeArchived:e.includeArchived,sourceKey:e.sourceKey,sourceRevision:e.sourceRevision,sort:"tokens",direction:"desc",pageSize:250}),enabled:s,placeholderData:d=>d}),r=b.useMemo(()=>new Map(e.model.threads.map(d=>[d.name,d])),[e.model.threads]),h=b.useMemo(()=>{var d;return((d=n.data)==null?void 0:d.pages.flatMap(B=>B.rows.map(R=>se(R,r.get(R.threadLabel)??r.get(R.threadKey)))))??[]},[r,n.data]),m=s&&!!n.data,c=m?h:e.model.threads,i=c.find(d=>d.name===e.selectedThreadName)??c[0]??null,g=b.useMemo(()=>le(e.model.calls,i),[e.model.calls,i]),v=(i==null?void 0:i.threadKey)||((l=g[0])==null?void 0:l.threadKey)||(i==null?void 0:i.name)||"",x=K({...ae({runtime:e.runtime,includeArchived:e.includeArchived,sourceKey:e.sourceKey,sourceRevision:e.sourceRevision,threadKey:v}),enabled:s&&!!v,placeholderData:d=>d}),o=t.data,u=!!v,f=[F("Usage summary",s,t),F("Thread summaries",s,n),...u?[F("Selected thread calls",s,x)]:[]],N=I(f.map(d=>d.status)),S=t.error??n.error??x.error,p=f.find(d=>d.status==="error");return{cacheSeries:o?ce(o.rows):e.model.cacheSeries,cards:o?re(o.rows):e.model.cards.slice(2,5),heatmap:m?c.map(d=>({thread:d.name,values:[d.cachePct],labels:["All time"]})):e.model.cacheHeatmap,selectedCalls:(($=x.data)==null?void 0:$.rows)??g,selectedThread:i,threads:c,totalThreads:((j=(k=n.data)==null?void 0:k.pages[0])==null?void 0:j.totalMatchedRows)??c.length,usingFocusedEndpoints:m,progress:{active:s&&(t.isFetching||n.isFetching||x.isFetching),completed:N.ready,total:N.total,error:S?`${(p==null?void 0:p.label)??"Focused evidence"} unavailable: ${ne(S)}`:null,modules:f,updating:f.some(d=>d.status==="updating")}}}function F(e,s,t){return{label:e,status:H({enabled:s,hasData:!!t.data,isError:t.isError,isFetching:t.isFetching,isPending:t.isPending})}}function ne(e){return e instanceof Error?e.message:String(e)}function ce(e){return Q(e.map(s=>({timestamp:Date.parse(s.groupKey)||Date.parse(s.latestEvent),input:s.inputTokens,cached:s.cachedInputTokens,output:s.outputTokens,cost:0}))).cacheSeries}function re(e){const s=e.reduce((n,r)=>({calls:n.calls+r.modelCalls,input:n.input+r.inputTokens,cached:n.cached+r.cachedInputTokens,uncached:n.uncached+r.uncachedInputTokens,tokens:n.tokens+r.totalTokens}),{calls:0,input:0,cached:0,uncached:0,tokens:0}),t=s.input>0?s.cached/s.input*100:0;return[{label:"Total Calls",value:T(s.calls),trend:"complete selected scope",detail:"server-side aggregate",tone:"blue"},{label:"Cache Reuse",value:y(t),trend:t>=80?"healthy cache reuse":"review cache reuse",detail:`${w(s.cached)} cached input`,tone:t>=80?"green":"orange"},{label:"Uncached Input",value:w(s.uncached),trend:`${w(s.tokens)} total tokens`,detail:"complete selected scope",tone:"purple"}]}function le(e,s){return s?e.filter(t=>oe(t.thread,s.name)).sort((t,n)=>Date.parse(n.rawTime||n.time)-Date.parse(t.rawTime||t.time)):[]}function oe(e,s){const t=e.trim(),n=s.trim();return t===n||t.startsWith(n)||n.startsWith(t)}function Ae(e){const s=ue(e.threads)??e.threads[0]??null;return he(e.calls,s)}function Ee({model:e,contextRuntime:s,includeArchived:t=!1,scopeSince:n=null,sourceKey:r,sourceRevision:h="",focusedEndpointsEnabled:m=!0,onOpenInvestigator:c,onCopyCallLink:i}){const g=M(),[v,x]=b.useState(A),o=te({model:e,runtime:s,includeArchived:t,scopeSince:n,selectedThreadName:v,sourceKey:r,sourceRevision:h,enabled:m}),u=o.selectedThread,f=b.useMemo(()=>[...U,O({onOpenInvestigator:c,onCopyCallLink:i})],[i,c]),N=o.selectedCalls,S=u?o.heatmap.find(l=>E(l.thread,u.name)):null,p=b.useMemo(()=>W(o.heatmap),[o.heatmap]);return a.jsxs("div",{className:"cache-layout",children:[a.jsxs("div",{className:"page-title-row span-all",children:[a.jsxs("div",{children:[a.jsx("h1",{children:"Cache And Context Lab"}),a.jsx("p",{children:"Cache behavior, cold resumes, context pressure, optimization recommendations."})]}),a.jsxs("div",{className:"toolbar",children:[a.jsx(D,{label:o.usingFocusedEndpoints?"Full-scope endpoints":"Snapshot fallback",tone:o.usingFocusedEndpoints?"green":"orange"}),a.jsx(D,{label:"Context safe",tone:"blue"})]})]}),a.jsx(Z,{active:o.progress.active,completed:o.progress.completed,total:o.progress.total,label:"Loading cache and context evidence",error:o.progress.error,modules:o.progress.modules,updating:o.progress.updating}),a.jsx("div",{className:"metric-grid span-all",children:o.cards.map(l=>a.jsx(Y,{card:l},l.label))}),a.jsx(C,{title:"Cache Hit Rate & Context Window Over Time",subtitle:"Cache reuse and context pressure",children:a.jsx(G,{series:[...o.cacheSeries,e.usageRemainingSeries[0]].filter(Boolean),yLabel:"Percent",valueFormatter:l=>`${l}%`})}),a.jsx(C,{title:"Cache Reuse Heatmap",subtitle:p.length?`${p.length} cache windows`:"No cache heatmap rows",children:p.length?a.jsx("div",{className:"heatmap-scroll",tabIndex:0,"aria-label":"Scrollable cache reuse heatmap",children:a.jsxs("div",{className:"heatmap",role:"table","aria-label":"Cache reuse heatmap",style:{"--heatmap-columns":p.length},children:[a.jsxs("div",{className:"heatmap-head",role:"row",children:[a.jsx("span",{className:"sticky-column",role:"columnheader",children:"Thread"}),p.map(l=>a.jsx("span",{role:"columnheader",children:l},l))]}),o.heatmap.map(l=>a.jsxs("div",{className:"heatmap-row",role:"row",children:[a.jsx("strong",{className:"sticky-column",role:"rowheader",children:l.thread}),p.map(($,k)=>{const j=l.values[k];return a.jsx("span",{role:"cell",style:{"--intensity":(j??0)/100},children:typeof j=="number"?`${j}%`:"-"},`${l.thread}-${$}`)})]},l.thread))]})}):a.jsx("p",{className:"empty-state",children:"No cache heatmap rows in the current aggregate snapshot."})}),a.jsxs(C,{title:"Threads Overview",subtitle:u?`Selected ${u.name}: ${y(u.cachePct)} cache`:"Cold resume and cache efficiency signals",className:"span-all",action:a.jsx(D,{label:"Hover previews; rows open latest call",tone:"green"}),children:[a.jsx(J,{columns:f,data:o.threads,compact:!0,getRowId:l=>l.name,getRowActionLabel:z,selectedRowId:u==null?void 0:u.name,onRowSelect:l=>{x(l.name),pe(l.name)},onRowActivate:l=>{l.latestCallId&&c(l.latestCallId)},activateOnClick:!0,selectOnHover:!0,ariaLabel:"Cache context threads overview"}),a.jsx("p",{className:"table-caption",children:g.translateText(`Showing ${T(o.threads.length)} of ${T(o.totalThreads)} full-scope thread summaries.`)})]}),a.jsx(ie,{selectedThread:u,heatmap:S,heatmapWindowLabels:p,calls:N,onOpenInvestigator:c,onCopyCallLink:i})]})}function ie({selectedThread:e,heatmap:s,heatmapWindowLabels:t,calls:n,onOpenInvestigator:r,onCopyCallLink:h}){const m=M();return e?a.jsx("aside",{className:"side-panel",children:a.jsxs(C,{title:"Selected Thread Diagnosis",subtitle:e.name,children:[a.jsxs("div",{className:"finding-module",children:[a.jsxs("div",{className:"section-heading compact",children:[a.jsx("h3",{children:"Efficiency Profile"}),a.jsx("span",{children:m.translateText(`${e.coldResumeRisk} risk`)})]}),a.jsxs("div",{className:"evidence-list",children:[a.jsxs("span",{children:["Turns ",a.jsx("strong",{children:T(e.turns)})]}),a.jsxs("span",{children:["Tokens ",a.jsx("strong",{children:w(e.totalTokens)})]}),a.jsxs("span",{children:["Cache hit ",a.jsx("strong",{children:y(e.cachePct)})]}),a.jsxs("span",{children:["Est. cost ",a.jsx("strong",{children:P(e.cost)})]}),a.jsxs("span",{children:["Cost/call ",a.jsx("strong",{children:P(e.costPerCall)})]})]})]}),a.jsxs("div",{className:"finding-module",children:[a.jsxs("div",{className:"section-heading compact",children:[a.jsx("h3",{children:"Cache Windows"}),a.jsx("span",{children:s?"Weekly reuse":"No heatmap row"})]}),s?a.jsx("div",{className:"cache-window-strip","aria-label":`Cache windows for ${e.name}`,children:xe(s,t).map((c,i)=>{const g=s.values[i];return a.jsxs("span",{style:{"--intensity":(g??0)/100},children:[a.jsx("small",{children:c}),a.jsx("strong",{children:typeof g=="number"?`${g}%`:"-"})]},`${e.name}-window-${c}`)})}):a.jsx("p",{className:"empty-state",children:"No weekly cache heatmap row matches this selected thread."})]}),a.jsxs("div",{className:"finding-module",children:[a.jsxs("div",{className:"section-heading compact",children:[a.jsx("h3",{children:"Thread Calls"}),a.jsx("span",{children:n.length?`${n.length} loaded`:"No loaded calls"})]}),n.length?a.jsx("ol",{className:"thread-mini-timeline",children:n.slice(0,5).map(c=>a.jsxs("li",{className:"thread-call-row has-row-action",tabIndex:0,"aria-label":`Open investigator for cache thread call ${c.thread} ${c.model}`,onClick:()=>r(c.id),onKeyDown:i=>{(i.key==="Enter"||i.key===" ")&&(i.preventDefault(),r(c.id))},children:[a.jsx("span",{children:c.time}),a.jsxs("strong",{children:[c.model," / ",c.effort]}),a.jsxs("em",{children:[w(c.totalTokens)," tokens - ",y(c.cachedPct)," cache"]}),a.jsxs("div",{className:"thread-call-actions table-action-group",children:[a.jsxs("button",{className:"table-action-button",type:"button","aria-label":`Open investigator for cache thread call ${c.thread} ${c.model}`,onKeyDown:L,onClick:i=>{i.stopPropagation(),r(c.id)},children:[a.jsx(_,{size:14}),"Open"]}),a.jsxs("button",{className:"table-action-button",type:"button","aria-label":`Copy link for cache thread call ${c.thread} ${c.model}`,onKeyDown:L,onClick:i=>{i.stopPropagation(),h(c.id)},children:[a.jsx(V,{size:14}),"Copy"]})]})]},c.id))}):a.jsx("p",{className:"empty-state",children:"No loaded aggregate call rows match this selected thread."})]}),a.jsxs("div",{className:"finding-module",children:[a.jsx("h3",{children:"Diagnosis Basis"}),a.jsxs("ul",{className:"compact-list",children:[a.jsx("li",{children:m.translateText(`Risk: ${e.coldResumeRisk} cold-resume score`)}),a.jsx("li",{children:m.translateText(`Cache: ${y(e.cachePct)} hit rate; action threshold below 35%`)}),a.jsx("li",{children:m.translateText(`Cost: ${P(e.costPerCall)} per call; inspect threshold above $1.00`)}),a.jsx("li",{children:m.translateText(`Evidence: ${n.length} loaded calls, ${s?`${s.values.length} cache windows`:"no heatmap row"}`)})]})]}),a.jsxs("div",{className:"finding-module",children:[a.jsx("h3",{children:"Suggested Actions"}),a.jsx("ul",{className:"compact-list",children:de(e).map(c=>a.jsx("li",{children:c},c))})]})]})}):a.jsx("aside",{className:"side-panel",children:a.jsx(C,{title:"Selected Thread Diagnosis",subtitle:"No matching thread",children:a.jsx("p",{className:"empty-state",children:"No grouped thread is available in the current aggregate snapshot."})})})}function de(e){const s=[];return e.coldResumeRisk==="High"&&s.push("Summarize before the next work session."),e.cachePct<35&&s.push("Split completed topics or reduce repeated uncached context."),e.costPerCall>1&&s.push("Open a related call and inspect whether model effort was justified."),s.length||s.push("Keep the thread warm and continue monitoring cache reuse."),s}function he(e,s){return s?e.filter(t=>E(t.thread,s.name)).sort(ge):[]}function me(e){const s=A();return s&&e.some(t=>t.name===s)?s:null}function A(){var e;return((e=new URLSearchParams(window.location.search).get("cache_thread"))==null?void 0:e.trim())||null}function ue(e){const s=me(e);return s?e.find(t=>t.name===s)??null:null}function pe(e){const s=new URL(window.location.href);s.searchParams.set("view","cache-context"),s.searchParams.set("cache_thread",e),window.history.replaceState(null,"",s)}function ge(e,s){return Date.parse(s.rawTime||s.time)-Date.parse(e.rawTime||e.time)}function E(e,s){const t=e.trim(),n=s.trim();return t===n||t.startsWith(n)||n.startsWith(t)}function W(e){const s=e.find(n=>{var r;return(r=n.labels)==null?void 0:r.length}),t=e.reduce((n,r)=>{var h;return Math.max(n,r.values.length,((h=r.labels)==null?void 0:h.length)??0)},0);return Array.from({length:t},(n,r)=>{var h;return((h=s==null?void 0:s.labels)==null?void 0:h[r])??`Window ${r+1}`})}function xe(e,s){var n;if((n=e.labels)!=null&&n.length)return W([e]);const t=Math.max(e.values.length,s.length);return Array.from({length:t},(r,h)=>s[h]??`Window ${h+1}`)}export{Ee as CacheContextPage,Ae as cacheContextCallsForCurrentUrl};
diff --git a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/CallsPage.js b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/CallsPage.js
index 5c29e219..2eddd55d 100644
--- a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/CallsPage.js
+++ b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/CallsPage.js
@@ -13,4 +13,4 @@ import{j as t,r as c}from"./dashboard-react.js";import{u as Lt}from"./useInfinit
  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const Fn=Re("PanelRightOpen",[["rect",{width:"18",height:"18",x:"3",y:"3",rx:"2",key:"afitv7"}],["path",{d:"M15 3v18",key:"14nvp0"}],["path",{d:"m10 15-3-3 3-3",key:"1pgupc"}]]);function Nn(e){const n=[],s=[e.localQuery.trim(),e.globalQuery.trim()].filter(Boolean);s.length&&n.push(`Search ${s.map(i=>`"${i}"`).join(" + ")}`),e.modelFilter!=="all"&&n.push(`Model ${e.modelFilter}`),e.effortFilter!=="all"&&n.push(`Effort ${e.effortFilter}`),e.confidenceFilter!=="all"&&n.push(`Confidence ${Pn(e.confidenceFilter)}`),e.sourceFilter!=="all"&&n.push(`Source ${_n(e.sourceFilter)}`),e.dateRangeStatus.invalid?n.push("Date range invalid"):(e.dateRangeStatus.active||e.timeFilter!=="all")&&n.push(e.dateRangeStatus.label||Ln(e.timeFilter)),e.activePresetLabel&&n.push(`Preset ${e.activePresetLabel}`);const a=`Showing ${e.shownCount.toLocaleString()} of ${e.totalCount.toLocaleString()} aggregate rows`;return n.length?`${a} - Filters: ${n.join("; ")}`:a}function En(e,n){return n==="project"?`${e.project.toLocaleString()} project/cwd rows`:n==="session"?`${e.session.toLocaleString()} session-linked rows`:n==="git"?`${e.git.toLocaleString()} git rows`:n==="source-file"?`${e.sourceFile.toLocaleString()} source-file rows`:n==="missing"?`${e.missing.toLocaleString()} rows missing source`:`${e.project.toLocaleString()} project, ${e.session.toLocaleString()} session, ${e.git.toLocaleString()} git`}function Tn(e,n){return n==="all"?!0:n==="project"?Be(e):n==="session"?Ve(e):n==="git"?He(e):n==="source-file"?Ke(e):!ft(e)}function Mn(e,n){if(n==="all")return!0;if(n==="cost-exact")return!e.pricingEstimated&&Number.isFinite(e.cost)&&e.cost>0;if(n==="cost-estimated")return e.pricingEstimated;if(n==="cost-unpriced")return!e.pricingEstimated&&(!Number.isFinite(e.cost)||e.cost<=0);const s=e.usageCreditConfidence.toLowerCase();return n==="credit-exact"?s.includes("exact"):n==="credit-override"?s.includes("override"):n==="credit-estimated"?s.includes("estimated"):s.includes("missing")||s.includes("unpriced")}function Dn(e){return e.reduce((n,s)=>({project:n.project+(Be(s)?1:0),session:n.session+(Ve(s)?1:0),git:n.git+(He(s)?1:0),sourceFile:n.sourceFile+(Ke(s)?1:0),missing:n.missing+(ft(s)?0:1),total:n.total+1}),{project:0,session:0,git:0,sourceFile:0,missing:0,total:0})}function Be(e){return!!(e.project||e.projectRelativeCwd||e.cwd||e.projectTags.length)}function Ve(e){return!!(e.sessionId||e.turnId||e.parentSessionId)}function He(e){return!!(e.gitBranch||e.gitRemoteLabel||e.gitRemoteHash)}function Ke(e){return!!(e.sourceFile||e.lineNumber!==null)}function ft(e){return Be(e)||Ve(e)||He(e)||Ke(e)}function Pn(e){return e==="cost-exact"?"exact cost":e==="cost-estimated"?"estimated cost":e==="cost-unpriced"?"unpriced cost":e==="credit-exact"?"exact credit rate":e==="credit-estimated"?"estimated credit 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tokens"}),t.jsx("option",{value:"cached",children:"Cached"}),t.jsx("option",{value:"uncached",children:"Uncached"}),t.jsx("option",{value:"output",children:"Output"}),t.jsx("option",{value:"reasoning",children:"Reasoning output"}),t.jsx("option",{value:"cost",children:"Highest estimated cost"}),t.jsx("option",{value:"usage",children:"Highest Codex credits"}),t.jsx("option",{value:"cache",children:"Lowest cache ratio"}),t.jsx("option",{value:"context",children:"Highest context use"})]})]}),t.jsxs("label",{className:"filter-field",children:[t.jsx("span",{children:"Direction"}),t.jsxs("select",{"aria-label":"Sort direction",value:b,onChange:u=>L(u.target.value),children:[t.jsx("option",{value:"desc",children:"Descending"}),t.jsx("option",{value:"asc",children:"Ascending"})]})]})]})]}),t.jsxs("button",{className:"toolbar-button",type:"button",onClick:v,children:[t.jsx(Ht,{size:16}),"Clear filters"]})]})}function Es({workspaceSwitcher:e,canExport:n,onExport:s,onCopyView:a,onRefresh:i}){return t.jsxs("header",{className:$.pageHeader,children:[t.jsxs("div",{children:[t.jsx("p",{className:$.eyebrow,children:"Evidence explorer"}),t.jsx("h1",{children:"Calls"}),t.jsx("p",{children:"Find expensive, cold, or context-heavy calls and move directly into their evidence."})]}),t.jsxs("div",{className:$.headerActions,children:[e,t.jsxs("button",{className:"toolbar-button",type:"button",onClick:s,disabled:!n,children:[t.jsx(Kt,{size:16}),"Export"]}),t.jsxs("button",{className:"toolbar-button",type:"button",onClick:a,children:[t.jsx(dt,{size:16}),"Copy view"]}),t.jsxs("button",{className:"primary-button",type:"button",onClick:i,children:[t.jsx(zt,{size:16}),"Refresh"]})]})]})}const Ft="codexUsageDetailPanel";function Ms(e=!1){var n;try{const s=(n=window.sessionStorage)==null?void 0:n.getItem(Ft);return s?s==="expanded":e}catch{return e}}function Ds(e){var n;try{(n=window.sessionStorage)==null||n.setItem(Ft,e?"expanded":"collapsed")}catch{}}const B=250;function Ps(e,n){const s=T("density"),[a,i]=c.useState(()=>T("call_q")),[o,r]=c.useState(()=>T("model")||"all"),[h,F]=c.useState(()=>T("effort")||"all"),[d,b]=c.useState(()=>gt()),[j,C]=c.useState(()=>jt()),[D,N]=c.useState(()=>vt()),[y,m]=c.useState(()=>le("from")),[l,p]=c.useState(()=>le("to")),[w,g]=c.useState(()=>Pe()),[_,E]=c.useState(()=>Ct(Pe())),x=Zt("codexUsageCallsEvidenceGrid",{density:On()==="dense"?"compact":"comfortable",columnVisibility:{}},s==="roomy"?"comfortable":s==="dense"?"compact":void 0),L=x.density==="compact"?"dense":"roomy",v=c.useMemo(()=>An(),[]),[u,te]=c.useState(v),[G,R]=c.useState(()=>Bn(B)),[ne,Q]=c.useState(""),[de,ue]=c.useState(""),[W,he]=c.useState(()=>Ms(!!v)),me=c.useRef(null),se=c.useRef(n),xe=c.useMemo(()=>Ze(e.calls.map(f=>f.model)),[e.calls]),pe=c.useMemo(()=>Ze(e.calls.map(f=>f.effort)),[e.calls]),fe=c.useMemo(()=>Dn(e.calls),[e.calls]),Y=c.useMemo(()=>ze(D,y,l,new Date),[l,y,D]);c.useEffect(()=>{se.current!==n&&(se.current=n,R(B))},[n]);function I(){R(B)}function ge(f){i(f),I()}function je(f){r(f),I()}function ve(f){F(f),I()}function be(f){b(f),I()}function Ce(f){C(f),I()}function ye(f){N(f),I()}function Se(f){m(Le(f)),N("custom"),I()}function we(f){p(Le(f)),N("custom"),I()}function Fe(f){const A=bt(f);g(A),E(U(A)),I()}function Ne(f){E(f==="asc"?"asc":"desc"),I()}function Te(){i(""),r("all"),F("all"),b("all"),C("all"),N("all"),m(""),p(""),g("time"),E(U("time")),x.setDensity("compact"),x.setColumnVisibility({}),te(null),R(B),window.history.replaceState(null,"",_e({localQuery:"",modelFilter:"all",effortFilter:"all",confidenceFilter:"all",sourceFilter:"all",timeFilter:"all",dateStart:"",dateEnd:"",sortKey:"time",sortDirection:U("time"),density:"dense",selectedRecordId:"",visibleRowCount:B,pageSize:B})),ue("Calls filters cleared")}function Ee(){he(f=>{const A=!f;return Ds(A),A})}return{localQuery:a,modelFilter:o,effortFilter:h,confidenceFilter:d,sourceFilter:j,timeFilter:D,dateStart:y,dateEnd:l,sortKey:w,setSortKey:g,sortDirection:_,setSortDirection:E,gridPreferences:x,density:L,initialSelectedCallId:v,selectedCallId:u,setSelectedCallId:te,visibleCallRows:G,setVisibleCallRows:R,exportStatus:ne,setExportStatus:Q,filterStatus:de,detailsExpanded:W,searchInputRef:me,modelOptions:xe,effortOptions:pe,sourceCoverage:fe,dateRangeStatus:Y,resetCallTablePage:I,updateLocalQuery:ge,updateModelFilter:je,updateEffortFilter:ve,updateConfidenceFilter:be,updateSourceFilter:Ce,updateTimeFilter:ye,updateDateStart:Se,updateDateEnd:we,updateSortKey:Fe,updateSortDirection:Ne,clearCallFilters:Te,toggleCallDetails:Ee}}function _s({model:e,header:n,filters:s,table:a,inspector:i}){var F;const o=ce(),r=o.t("dashboard.model_calls","Model Calls"),h=o.t("dashboard.model_calls","Model calls");return t.jsxs("div",{className:`${$.page} page-grid`,children:[t.jsx(Es,{...n}),t.jsx(Ts,{...s}),t.jsxs("div",{className:$.tableHeading,children:[t.jsxs("div",{children:[t.jsx("h2",{children:r}),t.jsx("p",{children:a.exportStatus||a.filterStatus||a.subtitle})]}),t.jsxs("div",{className:$.tableActions,children:[t.jsx(re,{label:Ls(a.isFetching,a.focused,a.focusedReason),tone:a.focused?"green":"blue"}),t.jsx(re,{label:a.activePreset?`Preset: ${mt(a.activePreset)}`:"Raw context gated",tone:a.activePreset?"green":"blue"}),t.jsxs("button",{className:"toolbar-button",type:"button","aria-expanded":a.detailsExpanded,onClick:a.onToggleDetails,children:[a.detailsExpanded?t.jsx(wn,{size:16}):t.jsx(Fn,{size:16}),a.detailsExpanded?o.t("button.hide_details","Hide details"):o.t("dashboard.call_details","Call Details")]})]})]}),t.jsxs("div",{className:a.detailsExpanded?"table-detail-layout":"table-detail-layout detail-collapsed",children:[t.jsxs("div",{className:$.gridColumn,children:[t.jsx(en,{ariaLabel:h,columns:a.columns,data:a.calls,identityColumnId:"thread",lockedColumnIds:["investigate"],getRowId:d=>d.id,mobile:{primary:d=>d.thread,secondary:d=>o.translateText(`${d.time} · ${d.model} · ${ee(d.totalTokens)} tokens · ${q(d.cachedPct)} cache`),actionLabel:d=>Ut(d)},sorting:a.sorting,onSortingChange:a.onSortingChange,manualSorting:!0,columnVisibility:a.gridPreferences.columnVisibility,onColumnVisibilityChange:a.gridPreferences.setColumnVisibility,density:a.gridPreferences.density,onDensityChange:a.gridPreferences.setDensity,onRestoreDefaults:a.gridPreferences.restoreDefaults,selectedRowId:(F=a.selectedCall)==null?void 0:F.id,onRowSelect:d=>a.onSelectCall(d.id),onRowActivate:d=>i.onOpenInvestigator(d.id),activateOnClick:!0,selectOnHover:!0,viewportHeight:560,emptyLabel:"No rows match current filters."}),t.jsxs("div",{className:$.gridFooter,"aria-live":"polite",children:[t.jsx("span",{children:o.translateText(`${a.calls.length.toLocaleString()} loaded / ${a.totalMatchedCalls.toLocaleString()} matched`)}),a.focused&&a.hasNextPage?t.jsx("button",{className:"toolbar-button",type:"button",onClick:a.onLoadMore,disabled:a.isFetchingNextPage,children:a.isFetchingNextPage?"Loading more...":`Load ${B.toLocaleString()} more`}):null]})]}),a.detailsExpanded?t.jsx(ls,{call:a.selectedCall,calls:e.calls,...i}):null]}),t.jsxs("details",{className:$.patternsDisclosure,children:[t.jsxs("summary",{children:[t.jsx(ut,{size:17}),"Usage patterns"]}),t.jsxs("div",{className:"dashboard-grid three",children:[t.jsx(Z,{title:"Usage Over Time",subtitle:"Tokens",children:t.jsx(et,{series:e.tokenSeries,yLabel:"Tokens",height:220})}),t.jsx(Z,{title:"Cost by Model",subtitle:"Estimated USD",children:t.jsx(ss,{data:e.modelCosts,valueLabel:Ae})}),t.jsx(Z,{title:"Cache Hit Rate Over Time",subtitle:o.translateText("Daily"),children:t.jsx(et,{series:e.cacheSeries,yLabel:"Cache %",height:220,valueFormatter:d=>`${d}%`})})]})]})]})}function Ls(e,n,s){return e&&n?"Updating focused rows":e?"Loading focused rows":n?"Focused paged API":s||"Stored snapshot"}function Zs(e,n="",s=""){const a=Pe();return ke(yt(e,{globalQuery:n,localQuery:T("call_q"),modelFilter:T("model")||"all",effortFilter:T("effort")||"all",confidenceFilter:gt(),sourceFilter:jt(),timeFilter:vt(),dateStart:le("from"),dateEnd:le("to"),activePreset:s}),a,Ct(a))}const Nt={time:"time",duration:"duration",gap:"previousCallGap",attention:"signal",thread:"thread",initiator:"initiator",model:"model",effort:"effort",total:"totalTokens",cached:"cachedInput",uncached:"uncachedInput",output:"output",reasoning:"reasoningOutput",cost:"cost",usage:"credits",cache:"cachedPct",context:"contextWindowPct"},ks=Object.fromEntries(Object.entries(Nt).map(([e,n])=>[n,e]));function ea({model:e,globalQuery:n,activePreset:s,onRefresh:a,contextRuntime:i,onContextApiEnabledChange:o,onOpenInvestigator:r,onCopyCallLink:h,includeArchived:F=!1,sourceKey:d,sourceRevision:b="",scopeSince:j=null,focusedEndpointsEnabled:C=!0,workspaceSwitcher:D}){var We,Ye;const N=Ps(e,n),{localQuery:y,modelFilter:m,effortFilter:l,confidenceFilter:p,sourceFilter:w,timeFilter:g,dateStart:_,dateEnd:E,sortKey:x,setSortKey:L,sortDirection:v,setSortDirection:u,gridPreferences:te,density:G,selectedCallId:R,setSelectedCallId:ne,visibleCallRows:Q,setVisibleCallRows:de,exportStatus:ue,setExportStatus:W,filterStatus:he,detailsExpanded:me,searchInputRef:se,modelOptions:xe,effortOptions:pe,sourceCoverage:fe,dateRangeStatus:Y,resetCallTablePage:I,updateLocalQuery:ge,updateModelFilter:je,updateEffortFilter:ve,updateConfidenceFilter:be,updateSourceFilter:Ce,updateTimeFilter:ye,updateDateStart:Se,updateDateEnd:we,updateSortKey:Fe,updateSortDirection:Ne,clearCallFilters:Te,toggleCallDetails:Ee}=N,f=c.useMemo(()=>[...qt,Gt({onOpenInvestigator:r,onCopyCallLink:h})],[h,r]),A=c.useMemo(()=>Zn({runtime:i,enabled:C,activePreset:s,sourceFilter:w,sortKey:x,scopeSince:j,timeFilter:g,dateStart:_,dateEnd:E,confidenceFilter:p,globalQuery:n,localQuery:y,modelFilter:m,effortFilter:l}),[s,p,i,E,_,l,C,n,y,m,x,w,j,g]),V=Lt({...It({runtime:i,includeArchived:F,sourceKey:d,sourceRevision:b,filters:A.filters,sort:A.sort,direction:v,pageSize:B}),enabled:A.enabled,placeholderData:M=>M}),Ue=c.useMemo(()=>yt(e.calls,{globalQuery:n,localQuery:y,modelFilter:m,effortFilter:l,confidenceFilter:p,sourceFilter:w,timeFilter:g,dateStart:_,dateEnd:E,activePreset:s}),[s,p,E,_,l,n,y,e.calls,m,w,g]),qe=c.useMemo(()=>ke(Ue,x,v),[Ue,v,x]),Ge=c.useMemo(()=>{var M;return((M=V.data)==null?void 0:M.pages.flatMap(J=>J.rows))??[]},[V.data]),ae=A.enabled&&!!V.data,H=c.useMemo(()=>ae?ke(Ge,x,v):qe,[Ge,qe,v,x,ae]),Me=ae?((Ye=(We=V.data)==null?void 0:We.pages[0])==null?void 0:Ye.totalMatchedRows)??H.length:e.calls.length,Tt=c.useMemo(()=>Nn({shownCount:H.length,totalCount:Me,localQuery:y,globalQuery:n,modelFilter:m,effortFilter:l,confidenceFilter:p,sourceFilter:w,timeFilter:g,dateRangeStatus:Y,activePresetLabel:s?mt(s):""}),[s,p,Y,l,n,y,m,H.length,w,g,Me]),Qe=c.useMemo(()=>[{id:Nt[x],desc:v==="desc"}],[v,x]),ie=R===oe?H[0]??null:H.find(M=>M.id===R)??H[0]??null,z=ie&&(ie.id===R||R===oe)?ie.id:"";c.useEffect(()=>{R===oe&&z&&ne(z)},[R,z]),c.useEffect(()=>{const M=_e({localQuery:y,modelFilter:m,effortFilter:l,confidenceFilter:p,sourceFilter:w,timeFilter:g,dateStart:_,dateEnd:E,sortKey:x,sortDirection:v,density:G,selectedRecordId:z,visibleRowCount:Q,pageSize:B});M.toString()!==window.location.href&&window.history.replaceState(null,"",M)},[p,E,_,G,l,y,m,z,v,x,w,g,Q]);function Et(){Qt(`codex-calls-${Jt()}.csv`,Wt(H,Yt)),W(`Exported ${H.length} calls`)}async function Mt(){try{const M=_e({localQuery:y,modelFilter:m,effortFilter:l,confidenceFilter:p,sourceFilter:w,timeFilter:g,dateStart:_,dateEnd:E,sortKey:x,sortDirection:v,density:G,selectedRecordId:z,visibleRowCount:Q,pageSize:B});if(!await ht(M.toString()))throw new Error("Clipboard unavailable");W("Copied Calls view link")}catch{W("Copy unavailable in browser")}}function Dt(M){var Je,Xe;const J=typeof M=="function"?M(Qe):M,De=ks[((Je=J[0])==null?void 0:Je.id)??""]??"time",_t=De!==x;L(De),u(_t?U(De):(Xe=J[0])!=null&&Xe.desc?"desc":"asc"),I()}async function Pt(){!V.hasNextPage||V.isFetchingNextPage||(await V.fetchNextPage(),de(M=>M+B))}return t.jsx(_s,{model:e,header:{workspaceSwitcher:D,canExport:!!H.length,onExport:Et,onCopyView:Mt,onRefresh:a},filters:{searchInputRef:se,localQuery:y,modelFilter:m,effortFilter:l,confidenceFilter:p,sourceFilter:w,timeFilter:g,dateStart:_,dateEnd:E,sortKey:x,sortDirection:v,modelOptions:xe,effortOptions:pe,sourceCoverage:fe,dateRangeStatus:Y,onLocalQueryChange:ge,onModelFilterChange:je,onEffortFilterChange:ve,onConfidenceFilterChange:be,onSourceFilterChange:Ce,onTimeFilterChange:ye,onDateStartChange:Se,onDateEndChange:we,onSortKeyChange:Fe,onSortDirectionChange:Ne,onClear:Te},table:{activePreset:s,exportStatus:ue,filterStatus:he,subtitle:Tt,focused:ae,focusedReason:A.reason,isFetching:V.isFetching,isFetchingNextPage:V.isFetchingNextPage,hasNextPage:!!V.hasNextPage,detailsExpanded:me,calls:H,totalMatchedCalls:Me,columns:f,sorting:Qe,gridPreferences:te,selectedCall:ie,onSortingChange:Dt,onSelectCall:ne,onLoadMore:Pt,onToggleDetails:Ee},inspector:{contextRuntime:i,includeArchived:F,sourceRevision:b,hydrateThreadCalls:C,onContextApiEnabledChange:o,onOpenInvestigator:r,onCopyCallLink:h}})}export{ea as CallsPage,Zs as callsForCurrentUrl};
diff --git a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/DataTable.js b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/DataTable.js
index 503a76fc..610059be 100644
--- a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/DataTable.js
+++ b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/DataTable.js
@@ -1,11 +1,11 @@
-import{r as D,j as e}from"./dashboard-react.js";import{u as X,f as h,g as Y,a as Z}from"./index2.js";import{c as w,I as _}from"./App.js";/**
+import{r as T,j as t}from"./dashboard-react.js";import{u as Y,f as N,g as Z,a as O}from"./index2.js";import{c as I,u as R,I as A}from"./App.js";/**
  * @license lucide-react v0.468.0 - ISC
  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const O=w("ArrowDown",[["path",{d:"M12 5v14",key:"s699le"}],["path",{d:"m19 12-7 7-7-7",key:"1idqje"}]]);/**
+ */const tt=I("ArrowDown",[["path",{d:"M12 5v14",key:"s699le"}],["path",{d:"m19 12-7 7-7-7",key:"1idqje"}]]);/**
  * @license lucide-react v0.468.0 - ISC
  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const R=w("ChevronsUpDown",[["path",{d:"m7 15 5 5 5-5",key:"1hf1tw"}],["path",{d:"m7 9 5-5 5 5",key:"sgt6xg"}]]),A=250,ee=250;function le({columns:i,data:M,compact:N=!1,emptyLabel:S="No rows match current filters.",getRowId:f,getRowActionLabel:u,selectedRowId:E,onRowSelect:o,onRowActivate:a,activateOnClick:p=!1,selectOnHover:V,ariaLabel:I,columnVisibility:b,onColumnVisibilityChange:z,sorting:B,onSortingChange:H,manualSorting:L=!1,initialVisibleRows:T=A,visibleRowsIncrement:x=ee,visibleRowCount:U,onVisibleRowCountChange:C}){const[q,K]=D.useState([]),[P,$]=D.useState(T),F=B??q,G=H??K,j=U??P,m=X({columns:i,data:M,state:{sorting:F,...b?{columnVisibility:b}:{}},onSortingChange:G,onColumnVisibilityChange:z,getCoreRowModel:Z(),getSortedRowModel:Y(),enableSortingRemoval:!1,manualSorting:L,...f?{getRowId:f}:{}}),r=m.getRowModel().rows,g=r.slice(0,j),k=Math.max(0,r.length-g.length);function J(){const s=Math.min(r.length,j+x);if(C){C(s);return}$(s)}return e.jsxs("div",{className:"table-window",children:[e.jsx("div",{className:"table-scroll",children:e.jsxs("table",{className:N?"data-table compact":"data-table","aria-label":I,children:[e.jsx("thead",{children:m.getHeaderGroups().map(s=>e.jsx("tr",{children:s.headers.map(t=>{const l=t.column.getIsSorted();return e.jsx("th",{className:y(t.column.id),"aria-sort":l==="asc"?"ascending":l==="desc"?"descending":"none",children:t.isPlaceholder?null:t.column.getCanSort()?e.jsxs("button",{className:"sort-header",type:"button",onClick:t.column.getToggleSortingHandler(),"aria-label":`Sort by ${te(t.column.columnDef.header)}`,children:[h(t.column.columnDef.header,t.getContext()),l==="asc"?e.jsx(_,{size:13}):l==="desc"?e.jsx(O,{size:13}):e.jsx(R,{size:13})]}):h(t.column.columnDef.header,t.getContext())},t.id)})},s.id))}),e.jsx("tbody",{children:r.length?g.map(s=>{const t=s.id===E,l=!!(o||a),Q=!!(a&&(!o||p)),v=u==null?void 0:u(s.original),d=()=>o==null?void 0:o(s.original),c=()=>{var n;return(n=a??o)==null?void 0:n(s.original)},W=()=>{if(Q){d(),c();return}o?d():c()};return e.jsx("tr",{className:[l?"is-clickable":"",a?"is-activatable":"",t?"selected-row":""].filter(Boolean).join(" "),"aria-label":v,"aria-selected":t||void 0,tabIndex:l?0:void 0,title:v??(a?o?p?"Click opens full investigator. Hover or press Space previews details.":"Click to inspect details. Double-click or press Enter open full investigator.":"Click or press Enter open the full investigator.":void 0),onClick:l?W:void 0,onMouseEnter:V&&o?d:void 0,onDoubleClick:a?c:void 0,onKeyDown:l?n=>{n.key==="Enter"&&(n.preventDefault(),c()),n.key===" "&&(n.preventDefault(),o?d():c())}:void 0,children:s.getVisibleCells().map(n=>e.jsx("td",{className:y(n.column.id),children:h(n.column.columnDef.cell,n.getContext())},n.id))},s.id)}):e.jsx("tr",{children:e.jsx("td",{colSpan:Math.max(m.getVisibleLeafColumns().length,1),className:"empty-cell",children:S})})})]})}),k?e.jsxs("div",{className:"table-window-footer",children:[e.jsxs("span",{children:["Showing ",g.length.toLocaleString()," of ",r.length.toLocaleString()," table rows"]}),e.jsxs("button",{type:"button",className:"inline-button",onClick:J,children:["Show ",Math.min(x,k).toLocaleString()," more rows"]})]}):null]})}function te(i){return typeof i=="string"?i:"column"}function y(i){return i==="thread"||i==="name"?"sticky-column":void 0}export{le as D};
+ */const et=I("ChevronsUpDown",[["path",{d:"m7 15 5 5 5-5",key:"1hf1tw"}],["path",{d:"m7 9 5-5 5 5",key:"sgt6xg"}]]),st=250,nt=250,ot=new Set(["branch","command","cwd","file","model","name","path","project","record_id","remote","session","thread"]);function dt({columns:e,data:m,compact:g=!1,emptyLabel:E="No rows match current filters.",getRowId:p,getRowActionLabel:f,selectedRowId:V,onRowSelect:l,onRowActivate:r,activateOnClick:b=!1,selectOnHover:z,ariaLabel:C,columnVisibility:j,onColumnVisibilityChange:H,sorting:U,onSortingChange:$,manualSorting:B=!1,initialVisibleRows:L=st,visibleRowsIncrement:k=nt,visibleRowCount:q,onVisibleRowCountChange:v}){const a=R(),[K,P]=T.useState([]),[_,F]=T.useState(L),G=U??K,J=$??P,D=q??_,x=Y({columns:e,data:m,state:{sorting:G,...j?{columnVisibility:j}:{}},onSortingChange:J,onColumnVisibilityChange:H,getCoreRowModel:O(),getSortedRowModel:Z(),enableSortingRemoval:!1,manualSorting:B,...p?{getRowId:p}:{}}),c=x.getRowModel().rows,h=c.slice(0,D),w=Math.max(0,c.length-h.length);function Q(){const o=Math.min(c.length,D+k);if(v){v(o);return}F(o)}return t.jsxs("div",{className:"table-window",children:[t.jsx("div",{className:"table-scroll",children:t.jsxs("table",{className:g?"data-table compact":"data-table","aria-label":C?a.translateText(C):void 0,children:[t.jsx("thead",{children:x.getHeaderGroups().map(o=>t.jsx("tr",{children:o.headers.map(s=>{const i=s.column.getIsSorted();return t.jsx("th",{className:M(s.column.id),"aria-sort":i==="asc"?"ascending":i==="desc"?"descending":"none",children:s.isPlaceholder?null:s.column.getCanSort()?t.jsxs("button",{className:"sort-header",type:"button",onClick:s.column.getToggleSortingHandler(),"aria-label":a.translateText(`Sort by ${a.translateText(at(s.column.columnDef.header))}`),children:[S(s.column.columnDef.header,s.getContext(),a.translateText),i==="asc"?t.jsx(A,{size:13}):i==="desc"?t.jsx(tt,{size:13}):t.jsx(et,{size:13})]}):S(s.column.columnDef.header,s.getContext(),a.translateText)},s.id)})},o.id))}),t.jsx("tbody",{children:c.length?h.map(o=>{const s=o.id===V,i=!!(l||r),W=!!(r&&(!l||b)),y=f==null?void 0:f(o.original),u=()=>l==null?void 0:l(o.original),d=()=>{var n;return(n=r??l)==null?void 0:n(o.original)},X=()=>{if(W){u(),d();return}l?u():d()};return t.jsx("tr",{className:[i?"is-clickable":"",r?"is-activatable":"",s?"selected-row":""].filter(Boolean).join(" "),"aria-label":y,"aria-selected":s||void 0,tabIndex:i?0:void 0,title:y??(r?l?b?a.translateText("Click opens full investigator. Hover or press Space previews details."):a.translateText("Click to inspect details. Double-click or press Enter open full investigator."):a.translateText("Click or press Enter open the full investigator."):void 0),onClick:i?X:void 0,onMouseEnter:z&&l?u:void 0,onDoubleClick:r?d:void 0,onKeyDown:i?n=>{n.key==="Enter"&&(n.preventDefault(),d()),n.key===" "&&(n.preventDefault(),l?u():d())}:void 0,children:o.getVisibleCells().map(n=>t.jsx("td",{className:M(n.column.id),"data-localization-skip":lt(n.column.id)?"true":void 0,children:N(n.column.columnDef.cell,n.getContext())},n.id))},o.id)}):t.jsx("tr",{children:t.jsx("td",{colSpan:Math.max(x.getVisibleLeafColumns().length,1),className:"empty-cell",children:a.translateText(E)})})})]})}),w?t.jsxs("div",{className:"table-window-footer",children:[t.jsx("span",{children:a.translateText(`Showing ${h.length.toLocaleString()} of ${c.length.toLocaleString()} table rows`)}),t.jsx("button",{type:"button",className:"inline-button",onClick:Q,children:a.translateText(`Show ${Math.min(k,w).toLocaleString()} more rows`)})]}):null]})}function at(e){return typeof e=="string"?e:"column"}function S(e,m,g){return typeof e=="string"?g(e):e?N(e,m):null}function lt(e){return ot.has(e)}function M(e){return e==="thread"||e==="name"?"sticky-column":void 0}export{dt as D};
diff --git a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/DiagnosticsPage.js b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/DiagnosticsPage.js
index 0605049d..560434e9 100644
--- a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/DiagnosticsPage.js
+++ b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/DiagnosticsPage.js
@@ -1 +1 @@
-import{r as j,j as t}from"./dashboard-react.js";import{f as _,a as C,p as q,S as H,b as W,s as G,o as Oe,q as U,l as me,k as pe,v as Ae,w as ze,R as fe,x as I,m as Be}from"./App.js";import{L as Qe}from"./LineChart.js";import{P as O,S as Q}from"./Panel.js";import{P as be}from"./PageLoadProgress.js";import"./Primitives.js";import{u as Ve,d as xe,f as Je,s as Ge,a as He,b as We}from"./diagnosticsQueries.js";import{u as Ke}from"./useQuery.js";import{u as Ye}from"./useInfiniteQuery.js";import"./dashboardRouter.js";import"./router.js";import"./useBaseQuery.js";import"./queryOptions.js";import"./infiniteQueryOptions.js";const Ze=8;function R(e){return`${e.fact_type??""}\0${e.fact_name??""}`}function je(e){return Math.max(e.calls.length,Number(e.rawPayload.total_matched_rows??e.calls.length))}function Xe(e){return!!e.rawPayload.truncated&&e.calls.length<je(e)}function qe(e,s){const a=[...e.calls],i=new Set(a.map(l=>l.id).filter(Boolean));s.calls.forEach(l=>{i.has(l.id)||(i.add(l.id),a.push(l))});const n=[...e.rawPayload.rows??[]],c=new Set(n.map(l=>l.record_id).filter(Boolean));(s.rawPayload.rows??[]).forEach(l=>{const f=l.record_id;f&&c.has(f)||(f&&c.add(f),n.push(l))});const o=Math.max(a.length,Number(s.rawPayload.total_matched_rows??e.rawPayload.total_matched_rows??a.length));return{calls:a,rawPayload:{...s.rawPayload,rows:n,row_count:a.length,total_matched_rows:o,truncated:a.length<o}}}const ye=[{key:"uncached",label:"Uncached input"},{key:"total",label:"Total tokens"},{key:"cached",label:"Cached input"},{key:"output",label:"Output tokens"},{key:"largest",label:"Largest call"},{key:"calls",label:"Associated calls"},{key:"cache",label:"Cache %"},{key:"latest",label:"Latest time"},{key:"occurrences",label:"Occurrences"},{key:"fact",label:"Fact name"}],ke=[{key:"tokens",label:"Total tokens"},{key:"input",label:"Input tokens"},{key:"cached",label:"Cached input"},{key:"uncached",label:"Uncached input"},{key:"output",label:"Output tokens"},{key:"reasoning",label:"Reasoning tokens"},{key:"cache",label:"Cache %"},{key:"time",label:"Time"},{key:"thread",label:"Thread"},{key:"model",label:"Model"},{key:"effort",label:"Effort"}];function k(e){const s=Number(e??0);return Number.isFinite(s)?s:0}function et(e){return e==="fact"?"asc":"desc"}function tt(e){return e==="effort"||e==="model"||e==="thread"?"asc":"desc"}function st(e){var a;return`sorted by ${(((a=ke.find(i=>i.key===e.key))==null?void 0:a.label)??"Total tokens").toLowerCase()} ${e.direction==="desc"?"descending":"ascending"}`}function at(e){var a;return`sorted by ${(((a=ye.find(i=>i.key===e.key))==null?void 0:a.label)??"Uncached input").toLowerCase()} ${e.direction==="desc"?"descending":"ascending"}`}function nt(e,s,a){const i=a==="asc"?1:-1;return[...e].sort((n,c)=>Z(n,c,s)*i||Z(n,c,"uncached")*-1||Z(n,c,"fact"))}function Z(e,s,a){return a==="fact"?`${e.fact_type??""}/${e.fact_name??""}`.localeCompare(`${s.fact_type??""}/${s.fact_name??""}`):ne(e,a)-ne(s,a)}function ne(e,s){return s==="calls"?k(e.associated_calls):s==="cached"?k(e.associated_cached_input_tokens):s==="cache"?_e(e):s==="largest"?k(e.largest_call_tokens):s==="latest"?Date.parse(e.latest_event_timestamp??"")||0:k(s==="occurrences"?e.occurrences:s==="output"?e.associated_output_tokens:s==="total"?e.associated_total_tokens:e.associated_uncached_input_tokens)}function it(e,s,a){const i=a==="asc"?1:-1;return[...e].sort((n,c)=>ie(n,c,s)*i||ie(n,c,"tokens")*-1||n.id.localeCompare(c.id))}function ie(e,s,a){return a==="thread"||a==="model"||a==="effort"?String(e[a]).localeCompare(String(s[a])):ce(e,a)-ce(s,a)}function ce(e,s){return s==="cache"?e.cachedPct:s==="cached"?e.cachedInput:s==="input"?e.input:s==="output"?e.output:s==="reasoning"?e.reasoningOutput:s==="time"?Date.parse(e.rawTime)||0:s==="uncached"?e.uncachedInput:e.totalTokens}function _e(e){const s=k(e.avg_cache_ratio);return s<=1?s*100:s}const P=6,X="codexUsageDiagnosticsFactVisibleCounts";function ct({sources:e,activeSourceKey:s,facts:a,selectedFact:i,factState:n,factSort:c,onFactSortChange:o,onSelectSource:l,onSelectFact:f,canLoadMoreFacts:r,loadingMoreFacts:g,onLoadMoreFacts:N,onOpenInvestigator:F,onCopyCallLink:$}){const[p,v]=j.useState(()=>oe(s,c)),L=e.find(d=>d.key===s),T=(L==null?void 0:L.title)??"Structured Diagnostic Facts",u=j.useMemo(()=>nt(a,c.key,c.direction),[a,c]).slice(0,p),b=Math.max(a.length-u.length,0),y=a.length,x=n.status==="loaded"?Math.max(k(n.payload.total_matched_rows),y):y,A=x>y?`${_(y)} loaded / ${_(x)} matched`:`${_(y)} matched`,z=at(c),B=n.status==="error"?`Live ${T.toLowerCase()} unavailable: ${n.message}`:n.status==="loading"?n.message:`${T} module - ${A} - ${z}`;return j.useEffect(()=>{v(oe(s,c))},[s,c]),j.useEffect(()=>{u.length&&!u.some(d=>i&&R(d)===R(i))&&f(u[0])},[f,i,u]),t.jsxs(O,{title:"Structured Diagnostic 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facts...":"Load more live facts"}):null]}):null]})}function ot({selectedFact:e,calls:s,status:a,usingLiveFacts:i,liveResult:n,factCallSort:c,rowLoadControls:o,onFactCallSortChange:l,onLoadMore:f,onOpenInvestigator:r,onCopyCallLink:g}){const N=e?`${e.fact_type||"fact"} / ${e.fact_name||"unknown"}`:"No fact selected",F=n?je(n):s.length,$=i&&n?Xe(n):!1,p=a.status==="appending",v=o.canLoadMoreRows||o.canLoadAllRows||o.totalAvailableRows>o.loadedRowCount,L=j.useMemo(()=>it(s,c.key,c.direction),[s,c]),T=st(c),M=a.status==="loading"?a.message:a.status==="error"?`Live calls unavailable: ${a.message}`:i?`${_(s.length)} of ${_(F)} live fact calls`:`${s.length} fallback aggregate calls`;return t.jsxs(O,{title:"Diagnostic Fact Calls",subtitle:M,children:[t.jsxs("div",{className:"section-heading compact",children:[t.jsx("h3",{children:N}),t.jsx("span",{children:s.length?`Showing ${_(s.length)} of ${_(F)} calls - ${T}`:"No loaded rows"})]}),s.length?t.jsxs(t.Fragment,{children:[t.jsxs("div",{className:"diagnostic-fact-controls diagnostic-call-controls",children:[t.jsxs("label",{className:"mini-select-field",children:["Sort calls",t.jsx("select",{"aria-label":"Sort diagnostic fact calls",value:c.key,onChange:u=>{const b=u.target.value;l({key:b,direction:tt(b)})},children:ke.map(u=>t.jsx("option",{value:u.key,children:u.label},u.key))})]}),t.jsx("button",{className:"pager-button",type:"button","aria-label":`Sort diagnostic fact calls ${c.direction==="desc"?"ascending":"descending"}`,onClick:()=>l({...c,direction:c.direction==="desc"?"asc":"desc"}),children:c.direction==="desc"?"Descending":"Ascending"})]}),t.jsx("div",{className:"table-scroll diagnostic-fact-call-scroll",children:t.jsxs("table",{className:"data-table compact diagnostic-fact-call-table","aria-label":"Diagnostic fact 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ve(e){return[{fact_type:"cache",fact_name:"large_uncached_input",calls:e.filter(a=>a.signal==="cache-risk"||a.cachedPct<35||a.uncachedInput>5e4)},{fact_type:"model",fact_name:"high_effort",calls:e.filter(a=>a.effort.toLowerCase()==="high")},{fact_type:"tool",fact_name:"file_heavy_or_subagent",calls:e.filter(a=>a.tags.some(i=>["file-heavy","subagent","large"].includes(i)))},{fact_type:"usage",fact_name:"high_credit_call",calls:[...e].sort((a,i)=>i.credits-a.credits).slice(0,5)}].filter(a=>a.calls.length).map(a=>xt(a.fact_type,a.fact_name,a.calls)).sort((a,i)=>J(i.associated_uncached_input_tokens)-J(a.associated_uncached_input_tokens)||J(i.associated_total_tokens)-J(a.associated_total_tokens))}function we(e,s){const a=String(e.fact_name??""),i=`${e.fact_type??""} ${e.fact_name??""}`.toLowerCase();if(a==="large_uncached_input"||i.includes("cache")||i.includes("uncached"))return s.filter(n=>n.signal==="cache-risk"||n.cachedPct<35||n.uncachedInput>5e4).sort((n,c)=>c.uncachedInput-n.uncachedInput).slice(0,5);if(a==="high_effort"||i.includes("effort")||i.includes("model"))return s.filter(n=>n.effort.toLowerCase()==="high").sort((n,c)=>c.totalTokens-n.totalTokens).slice(0,5);if(a==="file_heavy_or_subagent"||i.includes("tool")||i.includes("function")||i.includes("file")||i.includes("subagent")||i.includes("command")){const n=s.filter(c=>c.tags.some(o=>["file-heavy","subagent","large"].includes(o)));return(n.length?n:s).sort((c,o)=>o.input-c.input).slice(0,5)}return[...s].sort((n,c)=>c.credits-n.credits||c.totalTokens-n.totalTokens).slice(0,5)}function Ct(){const e=new URLSearchParams(window.location.search).get("diagnostic_source"),s=I.find(a=>a.key===e);return(s==null?void 0:s.key)??"facts"}function Se(e){var o;const s=(o=new URLSearchParams(window.location.search).get("diagnostic_fact"))==null?void 0:o.trim();if(!s)return null;const a=e.find(l=>Ce(l)===s||R(l)===s);if(a)return a;const[i,...n]=s.split(":"),c=n.join(":");return i||c?{fact_type:i,fact_name:c||"unknown"}:null}function Ce(e){return`${e.fact_type??""}:${e.fact_name??""}`}function he(e,s){const a=new URL(window.location.href);a.searchParams.set("view","diagnostics"),e==="facts"?a.searchParams.delete("diagnostic_source"):a.searchParams.set("diagnostic_source",e),s?a.searchParams.set("diagnostic_fact",Ce(s)):a.searchParams.delete("diagnostic_fact"),window.history.replaceState(null,"",a)}function ge(){return{status:"idle",message:"Static aggregate fallback"}}function Ft(){return vt}export{Vt as DiagnosticsPage,Qt as diagnosticsCallsForCurrentUrl};
+import{r as j,j as t}from"./dashboard-react.js";import{f as _,a as C,p as q,S as H,b as W,s as G,o as Oe,q as I,l as me,k as pe,v as Ae,w as ze,R as fe,u as Be,x as U,m as Qe}from"./App.js";import{L as Ve}from"./LineChart.js";import{P as O,S as Q}from"./Panel.js";import{P as be}from"./PageLoadProgress.js";import"./Primitives.js";import{u as Je,d as xe,f as Ge,s as He,a as We,b as Ke}from"./diagnosticsQueries.js";import{u as Ye}from"./useQuery.js";import{u as Ze}from"./useInfiniteQuery.js";import"./dashboardRouter.js";import"./router.js";import"./useBaseQuery.js";import"./queryOptions.js";import"./infiniteQueryOptions.js";const Xe=8;function T(e){return`${e.fact_type??""}\0${e.fact_name??""}`}function je(e){return Math.max(e.calls.length,Number(e.rawPayload.total_matched_rows??e.calls.length))}function qe(e){return!!e.rawPayload.truncated&&e.calls.length<je(e)}function et(e,s){const a=[...e.calls],i=new 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input"},{key:"uncached",label:"Uncached input"},{key:"output",label:"Output tokens"},{key:"reasoning",label:"Reasoning tokens"},{key:"cache",label:"Cache %"},{key:"time",label:"Time"},{key:"thread",label:"Thread"},{key:"model",label:"Model"},{key:"effort",label:"Effort"}];function k(e){const s=Number(e??0);return Number.isFinite(s)?s:0}function tt(e){return e==="fact"?"asc":"desc"}function st(e){return e==="effort"||e==="model"||e==="thread"?"asc":"desc"}function at(e){var a;return`sorted by ${(((a=ke.find(i=>i.key===e.key))==null?void 0:a.label)??"Total tokens").toLowerCase()} ${e.direction==="desc"?"descending":"ascending"}`}function nt(e){var a;return`sorted by ${(((a=ye.find(i=>i.key===e.key))==null?void 0:a.label)??"Uncached input").toLowerCase()} ${e.direction==="desc"?"descending":"ascending"}`}function it(e,s,a){const i=a==="asc"?1:-1;return[...e].sort((n,c)=>Z(n,c,s)*i||Z(n,c,"uncached")*-1||Z(n,c,"fact"))}function Z(e,s,a){return a==="fact"?`${e.fact_type??""}/${e.fact_name??""}`.localeCompare(`${s.fact_type??""}/${s.fact_name??""}`):ne(e,a)-ne(s,a)}function ne(e,s){return s==="calls"?k(e.associated_calls):s==="cached"?k(e.associated_cached_input_tokens):s==="cache"?_e(e):s==="largest"?k(e.largest_call_tokens):s==="latest"?Date.parse(e.latest_event_timestamp??"")||0:k(s==="occurrences"?e.occurrences:s==="output"?e.associated_output_tokens:s==="total"?e.associated_total_tokens:e.associated_uncached_input_tokens)}function ct(e,s,a){const i=a==="asc"?1:-1;return[...e].sort((n,c)=>ie(n,c,s)*i||ie(n,c,"tokens")*-1||n.id.localeCompare(c.id))}function ie(e,s,a){return a==="thread"||a==="model"||a==="effort"?String(e[a]).localeCompare(String(s[a])):ce(e,a)-ce(s,a)}function ce(e,s){return s==="cache"?e.cachedPct:s==="cached"?e.cachedInput:s==="input"?e.input:s==="output"?e.output:s==="reasoning"?e.reasoningOutput:s==="time"?Date.parse(e.rawTime)||0:s==="uncached"?e.uncachedInput:e.totalTokens}function _e(e){const s=k(e.avg_cache_ratio);return s<=1?s*100:s}const P=6,X="codexUsageDiagnosticsFactVisibleCounts";function ot({sources:e,activeSourceKey:s,facts:a,selectedFact:i,factState:n,factSort:c,onFactSortChange:o,onSelectSource:l,onSelectFact:f,canLoadMoreFacts:r,loadingMoreFacts:m,onLoadMoreFacts:w,onOpenInvestigator:S,onCopyCallLink:L}){const[D,g]=j.useState(()=>oe(s,c)),F=e.find(d=>d.key===s),R=(F==null?void 0:F.title)??"Structured Diagnostic Facts",u=j.useMemo(()=>it(a,c.key,c.direction),[a,c]).slice(0,D),b=Math.max(a.length-u.length,0),y=a.length,x=n.status==="loaded"?Math.max(k(n.payload.total_matched_rows),y):y,A=x>y?`${_(y)} loaded / ${_(x)} matched`:`${_(y)} matched`,z=nt(c),B=n.status==="error"?`Live ${R.toLowerCase()} unavailable: ${n.message}`:n.status==="loading"?n.message:`${R} module - ${A} - ${z}`;return j.useEffect(()=>{g(oe(s,c))},[s,c]),j.useEffect(()=>{u.length&&!u.some(d=>i&&T(d)===T(i))&&f(u[0])},[f,i,u]),t.jsxs(O,{title:"Structured Diagnostic Facts",subtitle:B,children:[t.jsx("div",{className:"drilldown-tabs diagnostic-source-tabs",role:"tablist","aria-label":"Diagnostic fact modules",children:e.map(d=>t.jsxs("button",{type:"button",role:"tab","aria-selected":d.key===s,className:d.key===s?"active":"",onClick:()=>l(d.key),children:[t.jsx("span",{children:d.label}),t.jsx("small",{children:dt(d.state)})]},d.key))}),t.jsxs("div",{className:"diagnostic-fact-controls",children:[t.jsxs("label",{className:"mini-select-field",children:["Sort facts",t.jsx("select",{"aria-label":"Sort diagnostic facts",value:c.key,onChange:d=>{const N=d.target.value;o({key:N,direction:tt(N)})},children:ye.map(d=>t.jsx("option",{value:d.key,children:d.label},d.key))})]}),t.jsx("button",{className:"pager-button",type:"button","aria-label":`Sort diagnostic facts 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cache"]})]}),t.jsxs("div",{className:"diagnostic-fact-meta",children:[t.jsxs("span",{children:[t.jsx("b",{children:"Category"}),d.fact_category||"uncategorized"]}),t.jsxs("span",{children:[t.jsx("b",{children:"Occurrences"}),_(k(d.occurrences))]}),t.jsxs("span",{children:[t.jsx("b",{children:"Total"}),C(k(d.associated_total_tokens))]}),t.jsxs("span",{children:[t.jsx("b",{children:"Input"}),C(k(d.associated_input_tokens))]}),t.jsxs("span",{children:[t.jsx("b",{children:"Cached"}),C(k(d.associated_cached_input_tokens))]}),t.jsxs("span",{children:[t.jsx("b",{children:"Output"}),C(k(d.associated_output_tokens))]}),t.jsxs("span",{children:[t.jsx("b",{children:"Reasoning"}),C(k(d.associated_reasoning_output_tokens))]}),t.jsxs("span",{children:[t.jsx("b",{children:"Largest"}),C(k(d.largest_call_tokens))]}),t.jsxs("span",{children:[t.jsx("b",{children:"Latest"}),ht(d.latest_event_timestamp)]})]}),d.largest_record_id?t.jsxs("div",{className:"table-action-group",children:[t.jsxs("button",{className:"table-action-button",type:"button","aria-label":`Open investigator largest diagnostic fact call ${d.fact_type} ${d.fact_name}`,onClick:()=>S(String(d.largest_record_id)),children:[t.jsx(H,{size:14})," Largest"]}),t.jsxs("button",{className:"table-action-button",type:"button","aria-label":`Copy link for largest diagnostic fact call ${d.fact_type} ${d.fact_name}`,onClick:()=>L(String(d.largest_record_id)),children:[t.jsx(W,{size:14})," Copy"]})]}):null]},T(d))}):t.jsx("p",{className:"empty-state",children:"No diagnostic facts matched the current aggregate data."})}),a.length>P||r?t.jsxs("div",{className:"child-load-more diagnostics-fact-load-more",children:[t.jsxs("span",{children:["Showing ",_(u.length)," of ",_(y)," loaded facts",x>y?` / ${_(x)} matched`:""]}),b?t.jsxs("button",{className:"pager-button",type:"button",onClick:()=>g(d=>{const N=Math.min(d+P,a.length);return ut(s,c,N),N}),children:["Show ",_(Math.min(P,b))," more"]}):null,r?t.jsx("button",{className:"pager-button",type:"button",onClick:w,disabled:m,children:m?"Loading more facts...":"Load more live facts"}):null]}):null]})}function rt({selectedFact:e,calls:s,status:a,usingLiveFacts:i,liveResult:n,factCallSort:c,rowLoadControls:o,onFactCallSortChange:l,onLoadMore:f,onOpenInvestigator:r,onCopyCallLink:m}){const w=e?`${e.fact_type||"fact"} / ${e.fact_name||"unknown"}`:"No fact selected",S=n?je(n):s.length,L=i&&n?qe(n):!1,D=a.status==="appending",g=o.canLoadMoreRows||o.canLoadAllRows||o.totalAvailableRows>o.loadedRowCount,F=j.useMemo(()=>ct(s,c.key,c.direction),[s,c]),R=at(c),M=a.status==="loading"?a.message:a.status==="error"?`Live calls unavailable: ${a.message}`:i?`${_(s.length)} of ${_(S)} live fact calls`:`${s.length} fallback aggregate calls`;return t.jsxs(O,{title:"Diagnostic Fact Calls",subtitle:M,children:[t.jsxs("div",{className:"section-heading compact",children:[t.jsx("h3",{children:w}),t.jsx("span",{children:s.length?`Showing ${_(s.length)} of ${_(S)} calls - ${R}`:"No loaded rows"})]}),s.length?t.jsxs(t.Fragment,{children:[t.jsxs("div",{className:"diagnostic-fact-controls diagnostic-call-controls",children:[t.jsxs("label",{className:"mini-select-field",children:["Sort calls",t.jsx("select",{"aria-label":"Sort diagnostic fact calls",value:c.key,onChange:u=>{const b=u.target.value;l({key:b,direction:st(b)})},children:ke.map(u=>t.jsx("option",{value:u.key,children:u.label},u.key))})]}),t.jsx("button",{className:"pager-button",type:"button","aria-label":`Sort diagnostic fact calls ${c.direction==="desc"?"ascending":"descending"}`,onClick:()=>l({...c,direction:c.direction==="desc"?"asc":"desc"}),children:c.direction==="desc"?"Descending":"Ascending"})]}),t.jsx("div",{className:"table-scroll diagnostic-fact-call-scroll",children:t.jsxs("table",{className:"data-table compact diagnostic-fact-call-table","aria-label":"Diagnostic fact calls",children:[t.jsx("thead",{children:t.jsxs("tr",{children:[t.jsx("th",{children:"Time"}),t.jsx("th",{className:"sticky-column",children:"Thread"}),t.jsx("th",{children:"Model"}),t.jsx("th",{children:"Effort"}),t.jsx("th",{className:"numeric",children:"Input"}),t.jsx("th",{className:"numeric",children:"Total"}),t.jsx("th",{className:"numeric",children:"Cached"}),t.jsx("th",{className:"numeric",children:"Uncached"}),t.jsx("th",{className:"numeric",children:"Output"}),t.jsx("th",{className:"numeric",children:"Reasoning"}),t.jsx("th",{className:"numeric",children:"Cache %"}),t.jsx("th",{children:"Action"})]})}),t.jsx("tbody",{children:F.map(u=>t.jsxs("tr",{className:"is-clickable is-activatable",tabIndex:0,"aria-label":`Open investigator diagnostic fact call ${u.thread} ${u.model}`,onClick:()=>r(u.id),onKeyDown:b=>{(b.key==="Enter"||b.key===" ")&&(b.preventDefault(),r(u.id))},children:[t.jsx("td",{children:u.time}),t.jsx("td",{className:"sticky-column",children:t.jsx("strong",{children:u.thread})}),t.jsx("td",{children:u.model}),t.jsx("td",{children:u.effort}),t.jsx("td",{className:"numeric",children:C(u.input)}),t.jsx("td",{className:"numeric",children:C(u.totalTokens)}),t.jsx("td",{className:"numeric",children:C(u.cachedInput)}),t.jsx("td",{className:"numeric",children:C(u.uncachedInput)}),t.jsx("td",{className:"numeric",children:C(u.output)}),t.jsx("td",{className:"numeric",children:C(u.reasoningOutput)}),t.jsx("td",{className:"numeric",children:q(u.cachedPct)}),t.jsx("td",{children:t.jsxs("div",{className:"table-action-group",children:[t.jsxs("button",{className:"table-action-button",type:"button","aria-label":`Open investigator diagnostic fact call ${u.thread} ${u.model}`,onKeyDown:G,onClick:b=>{b.stopPropagation(),r(u.id)},children:[t.jsx(H,{size:14})," Open"]}),t.jsxs("button",{className:"table-action-button",type:"button","aria-label":`Copy link for diagnostic fact call ${u.thread} ${u.model}`,onKeyDown:G,onClick:b=>{b.stopPropagation(),m(u.id)},children:[t.jsx(W,{size:14})," Copy"]})]})})]},`${w}-${u.id}`))})]})}),i||g?t.jsxs("div",{className:"child-load-more diagnostics-call-load-more",children:[t.jsxs("div",{children:[t.jsxs("span",{children:["Showing ",_(s.length)," of ",_(S)," calls"]}),g?t.jsxs("small",{children:["Dashboard rows: ",_(o.loadedRowCount)," of ",_(o.totalAvailableRows)," loaded"]}):null]}),t.jsxs("div",{className:"panel-action-group",children:[L?t.jsx("button",{className:"pager-button",type:"button",onClick:f,disabled:D,children:D?"Loading fact calls...":"Load more fact calls"}):null,g?t.jsxs(t.Fragment,{children:[t.jsx("button",{className:"pager-button",type:"button",onClick:o.onLoadMoreRows,disabled:!o.canLoadMoreRows||o.refreshing,children:o.refreshing?"Loading rows...":"Load more dashboard 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ht(e){if(!e)return"Unknown";const s=Date.parse(e);return Number.isFinite(s)?new Intl.DateTimeFormat("en-US",{month:"short",day:"numeric",hour:"numeric",minute:"2-digit"}).format(new Date(s)):e}function gt(e){const s=Oe(),[a,i]=j.useState(null),n=Je({queries:I.map(r=>({...xe({runtime:e.contextRuntime,includeArchived:e.includeArchived,sourceKey:e.sourceKey,sourceRevision:e.sourceRevision,snapshotKey:r.key}),enabled:e.canUseLive}))}),c=j.useMemo(()=>Object.fromEntries(n.flatMap((r,m)=>r.data?[[I[m].key,r.data]]:[])),[n]),o=I.map((r,m)=>({label:r.title,status:me({enabled:e.canUseLive,hasData:!!n[m].data,isError:n[m].isError,isFetching:n[m].isFetching,isPending:n[m].isPending})}));async function l(){i(null);const r=await ze(e.contextRuntime,{onProgress:i});for(const m of I){const w=r[m.key];w&&s.setQueryData(re(e,m),w)}return r}async function f(r){i(null);const m=await Ae(r,e.contextRuntime,{onProgress:i});return s.setQueryData(re(e,r),m),m}return{snapshots:c,modules:o,progress:pe(o.map(r=>r.status)),progressError:mt(n),loading:n.some(r=>r.isFetching),refreshJob:a,refreshAll:l,refreshOne:f}}function re(e,s){return xe({runtime:e.contextRuntime,includeArchived:e.includeArchived,sourceKey:e.sourceKey,sourceRevision:e.sourceRevision,snapshotKey:s.key}).queryKey}function mt(e){const s=e.findIndex(a=>a.isError&&!a.data);return s<0?null:`${I[s].title} unavailable: ${pt(e[s].error)}`}function pt(e){return e instanceof Error?e.message:String(e)}const le=4;function ft({model:e,contextRuntime:s,includeArchived:a,sourceKey:i,sourceRevision:n,onOpenInvestigator:c,onCopyCallLink:o}){const l=j.useMemo(()=>Ge(e),[e]),f=!!s.apiToken&&!s.fileMode,r=gt({canUseLive:f,contextRuntime:s,includeArchived:a,sourceKey:i,sourceRevision:n}),[m,w]=j.useState(!1),[S,L]=j.useState(""),[D,g]=j.useState({}),[F,R]=j.useState({}),M=Object.keys(r.snapshots).length>0,u=f&&M?r.snapshots:l,b=bt({canUseLiveDiagnostics:f,hasLiveSnapshots:M,liveSnapshotCount:Object.keys(r.snapshots).length,progressError:r.progressError,refreshingAll:m}),y=m&&r.refreshJob?r.refreshJob.progress:null,x=(y==null?void 0:y.completed_units)??r.progress.ready,A=(y==null?void 0:y.total_units)??r.progress.total,z=m?"Refreshing diagnostic snapshots":"Loading diagnostic snapshots",B=y?r.modules.map((p,v)=>({...p,status:v<y.completed_units?"ready":"updating"})):r.modules;async function d(){if(!(!f||r.loading||m)){w(!0),L("");try{await r.refreshAll(),g({})}catch(p){L(ue(p))}finally{w(!1)}}}async function N(p){if(!(!f||r.loading||m||D[p.key]==="refreshing")){L(""),g(v=>({...v,[p.key]:"refreshing"}));try{await r.refreshOne(p),g(v=>({...v,[p.key]:"ready"}))}catch(v){L(`Snapshot refresh failed: ${ue(v)}`),g(E=>({...E,[p.key]:"error"}))}}}return t.jsxs(O,{title:"Diagnostics Snapshot Matrix",subtitle:b,className:"span-all",action:t.jsxs("button",{className:"toolbar-button",type:"button",onClick:d,disabled:!f||r.loading||m,children:[t.jsx(fe,{size:15})," ",m?"Refreshing":"Refresh snapshots"]}),children:[t.jsx(be,{active:f&&(r.loading||m),completed:x,total:A,label:z,error:f?S||r.progressError:null,modules:B,updating:m||r.modules.some(p=>p.status==="updating")}),t.jsx("div",{className:"diagnostics-snapshot-grid",children:I.map(p=>t.jsx(xt,{cardKey:p.key,card:He(p,u[p.key]??l[p.key]),canRefresh:f,refreshStatus:D[p.key],expanded:!!F[p.key],onExpandedChange:v=>R(E=>({...E,[p.key]:v})),onRefresh:()=>N(p),onOpenInvestigator:c,onCopyCallLink:o},p.key))}),S?t.jsxs("p",{className:"context-state-note error",children:["Live diagnostic snapshots unavailable: ",S]}):null]})}function bt({canUseLiveDiagnostics:e,hasLiveSnapshots:s,liveSnapshotCount:a,progressError:i,refreshingAll:n}){return n?"Refreshing diagnostic snapshots...":s?`Live snapshots: ${a}`:i||!e?"Static fallback snapshots":"Loading diagnostic snapshots..."}function xt({cardKey:e,card:s,canRefresh:a,refreshStatus:i,expanded:n,onExpandedChange:c,onRefresh:o,onOpenInvestigator:l,onCopyCallLink:f}){const r=Be(),m=i==="refreshing",w=m?"Reloading":i==="error"?"Retry":"Reload",S=n?s.rows:s.rows.slice(0,le),L=Math.max(s.rows.length-S.length,0),D=`diagnostics-snapshot-${e}-rows`;return t.jsxs("article",{className:"diagnostics-snapshot-card",children:[t.jsxs("div",{className:"diagnostics-snapshot-card-head",children:[t.jsxs("div",{children:[t.jsx("h3",{children:r.translateText(s.title)}),t.jsx("p",{children:r.translateText(s.subtitle)})]}),t.jsxs("div",{className:"diagnostics-snapshot-card-actions",children:[t.jsx(Q,{label:s.status,tone:s.status==="ready"?"green":s.status==="fallback"?"blue":"orange"}),a?t.jsxs("button",{className:"toolbar-button diagnostics-section-refresh",type:"button","aria-label":`Reload ${s.title} diagnostic snapshot`,onClick:o,disabled:m,children:[t.jsx(fe,{size:13})," ",w]}):null]})]}),t.jsx("div",{className:"diagnostics-snapshot-metrics",children:s.metrics.map(g=>t.jsxs("span",{children:[t.jsx("small",{children:r.translateText(g.label)}),t.jsx("strong",{children:r.translateText(g.value)})]},`${s.title}-${g.label}`))}),t.jsx("ol",{className:"diagnostics-snapshot-rows",id:D,children:s.rows.length?S.map(g=>t.jsx("li",{className:g.recordId?"has-row-action":void 0,children:g.recordId?t.jsxs(t.Fragment,{children:[t.jsxs("button",{className:"diagnostics-snapshot-row-button",type:"button","aria-label":`Open investigator for diagnostic snapshot ${s.title} ${g.label}`,onClick:()=>l(String(g.recordId)),children:[t.jsxs("span",{children:[t.jsx("strong",{children:g.label}),t.jsx("em",{children:g.detail})]}),t.jsx("b",{children:g.value}),t.jsxs("span",{className:"diagnostics-snapshot-row-open",children:[t.jsx(H,{size:14})," Open"]})]}),t.jsxs("button",{className:"diagnostics-snapshot-row-copy",type:"button","aria-label":`Copy link for diagnostic snapshot ${s.title} ${g.label}`,onClick:()=>f(String(g.recordId)),children:[t.jsx(W,{size:14})," Copy"]}),t.jsx(de,{row:g})]}):t.jsxs(t.Fragment,{children:[t.jsxs("span",{children:[t.jsx("strong",{children:g.label}),t.jsx("em",{children:g.detail})]}),t.jsx("b",{children:g.value}),t.jsx(de,{row:g})]})},`${s.title}-${g.label}-${g.value}`)):t.jsx("li",{className:"empty-state",children:"No aggregate rows in this snapshot."})}),s.rows.length>le?t.jsxs("div",{className:"diagnostics-snapshot-row-depth",children:[t.jsx("span",{children:n?`Showing all ${s.rows.length.toLocaleString()} rows`:`Showing ${S.length.toLocaleString()} of ${s.rows.length.toLocaleString()} rows`}),t.jsx("button",{className:"inline-button",type:"button","aria-controls":D,"aria-expanded":n,onClick:()=>c(!n),children:n?"Show fewer":`Show ${L.toLocaleString()} more`})]}):null]})}function de({row:e}){var a;if(!((a=e.children)!=null&&a.length))return null;const s=e.children.length;return t.jsxs("details",{className:"diagnostics-snapshot-row-children",children:[t.jsx("summary",{children:`Show ${s.toLocaleString()} child ${s===1?"command":"commands"}`}),t.jsx("ul",{children:e.children.map(i=>t.jsxs("li",{children:[t.jsx("span",{children:i.label}),t.jsx("b",{children:i.value})]},`${e.label}-${i.label}-${i.value}`))})]})}function ue(e){return e instanceof Error?e.message:String(e)}function jt(e,s,a){const i=[...a].sort((o,l)=>l.totalTokens-o.totalTokens)[0],n=a.reduce((o,l)=>o+l.input,0),c=a.reduce((o,l)=>o+Math.round(l.input*(l.cachedPct/100)),0);return{fact_type:e,fact_name:s,fact_category:"react-fallback",occurrences:a.length,associated_calls:a.length,associated_input_tokens:n,associated_cached_input_tokens:c,associated_uncached_input_tokens:a.reduce((o,l)=>o+l.uncachedInput,0),associated_output_tokens:a.reduce((o,l)=>o+l.output,0),associated_reasoning_output_tokens:a.reduce((o,l)=>o+l.reasoningOutput,0),associated_total_tokens:a.reduce((o,l)=>o+l.totalTokens,0),avg_cache_ratio:n?c/n:0,largest_call_tokens:(i==null?void 0:i.totalTokens)??0,largest_record_id:(i==null?void 0:i.id)??null,latest_event_timestamp:(i==null?void 0:i.rawTime)||(i==null?void 0:i.time)||null,action_hint:"Open associated aggregate calls in the full Call Investigator."}}function J(e){const s=Number(e??0);return Number.isFinite(s)?s:0}const yt={key:"uncached",direction:"desc"};function kt(e){const s=U.find(l=>l.key===e.activeSourceKey)??U[0],a=e.sorts[s.key]??yt,i=Ye({...We({runtime:e.contextRuntime,includeArchived:e.includeArchived,sourceKey:e.sourceKey,sourceRevision:e.sourceRevision,factSourceKey:s.key,limit:e.limits[s.key],sort:a.key,direction:a.direction}),enabled:e.canUseLive}),n=Nt(i,s.title,e.canUseLive),c={[s.key]:n},o=[{label:s.title,status:me({enabled:e.canUseLive,hasData:!!i.data,isError:i.isError,isFetching:i.isFetching,isPending:i.isPending})}];return{states:c,modules:o,progress:pe(o.map(l=>l.status)),progressError:i.isError&&!i.data?`${s.title} unavailable: ${ee(i.error)}`:null,sourceIsUpdating:l=>l===s.key&&i.isFetching&&!!i.data}}function _t(e){const s=e.canUseLive&&e.usingLiveFacts&&!!e.fact,a=Ze({...Ke({runtime:e.contextRuntime,includeArchived:e.includeArchived,sourceKey:e.sourceKey,sourceRevision:e.sourceRevision,fact:e.fact??{},pageSize:e.pageSize,sort:e.factCallSort.key,direction:e.factCallSort.direction}),enabled:s}),i=j.useMemo(()=>{var o;const c=((o=a.data)==null?void 0:o.pages)??[];return c.length?c.slice(1).reduce(et,c[0]):null},[a.data]),n=vt(s,a,i);return{query:a,result:i,state:n,loadMore:()=>{a.hasNextPage&&!a.isFetchingNextPage&&a.fetchNextPage()}}}function Nt(e,s,a){return e.data?{status:"loaded",payload:e.data}:a?e.isError?{status:"error",message:ee(e.error)}:e.isFetching||e.isPending?{status:"loading",message:`Loading ${s.toLowerCase()}...`}:{status:"idle",message:"Waiting for live diagnostics"}:{status:"idle",message:"Static aggregate fallback"}}function vt(e,s,a){return e?s.isError?{status:"error",message:ee(s.error),result:a??void 0}:a&&s.isFetchingNextPage?{status:"appending",result:a}:a?{status:"loaded",result:a}:s.isPending?{status:"loading",message:"Loading calls for selected fact..."}:{status:"idle",message:"Select a diagnostic fact"}:{status:"idle",message:"Static aggregate fact calls"}}function ee(e){return e instanceof Error?e.message:String(e)}const wt={key:"uncached",direction:"desc"};function Vt(e){const s=ve(e.calls),a=Se(s)??s[0]??null;return a?we(a,e.calls):[]}function Jt({model:e,contextRuntime:s,includeArchived:a,sourceKey:i,sourceRevision:n,rowLoadControls:c,onOpenInvestigator:o,onCopyCallLink:l,globalFilters:f}){var se;const[r,m]=j.useState(()=>Ft()),[w,S]=j.useState({}),[L,D]=j.useState({}),[g,F]=j.useState(""),[R,M]=j.useState({key:"tokens",direction:"desc"}),u=!!s.apiToken&&!s.fileMode,b=kt({activeSourceKey:r,canUseLive:u,contextRuntime:s,includeArchived:a,sourceKey:i,sourceRevision:n,limits:L,sorts:w}),y=b.states,x=y[r]??ge(),A=w[r]??$t(),z=j.useMemo(()=>U.map(h=>({key:h.key,label:h.label,title:h.title,state:y[h.key]??ge()})),[y]),B=j.useMemo(()=>ve(e.calls),[e.calls]),d=x.status==="loaded"?x.payload.rows??[]:[],N=d.length>0,p=N?d:B,v=p.find(h=>T(h)===g)??p[0]??null,E=_t({canUseLive:u,contextRuntime:s,includeArchived:a,sourceKey:i,sourceRevision:n,fact:v,factCallSort:R,pageSize:Xe,usingLiveFacts:N}),te=E.state,Fe=j.useMemo(()=>v?we(v,e.calls):[],[e.calls,v]),K=lt(te),$e=K&&N?K.calls:Fe,V=U.find(h=>h.key===r)??U[0],Y=x.status==="loaded"?((se=x.payload.rows)==null?void 0:se.length)??0:0,Le=x.status==="loaded"?Number(x.payload.total_matched_rows??Y):Y,De=N&&x.status==="loaded"&&Le>Y,Te=V.key==="facts"?"facts":V.label.toLowerCase(),Re=x.status==="loaded"?`Live ${Te}: ${x.payload.total_matched_rows??p.length}`:x.status==="error"?"Static fallback facts":s.apiToken?x.message:"Static fallback facts",Me=b.modules.some(h=>h.status==="loading"||h.status==="updating");j.useEffect(()=>{if(!p.length){F("");return}const h=Se(p);if(h){const $=T(h);$!==g&&F($);return}p.some($=>T($)===g)||F(T(p[0]))},[p,r,g]);function Pe(){if(!u||x.status!=="loaded"||b.sourceIsUpdating(r))return;const h=x.payload.rows??[],$=Math.max(Number(x.payload.total_matched_rows??h.length),h.length),ae=Math.min(Math.max(h.length+V.limit,V.limit),$);ae<=h.length||D(Ue=>({...Ue,[r]:ae}))}function Ee(h){m(h),F(""),he(h,null)}function Ie(h){F(T(h)),he(r,h)}return t.jsxs("div",{className:"diagnostics-layout",children:[t.jsxs("div",{className:"page-title-row span-all",children:[t.jsxs("div",{children:[t.jsx("h1",{children:"Diagnostics Notebook"}),t.jsx("p",{children:"Technical report system behavior usage patterns."})]}),t.jsxs("div",{className:"toolbar",children:[t.jsx(Q,{label:Re,tone:N?"green":"blue"}),t.jsx(Q,{label:"Local Only",tone:"green"})]})]}),t.jsx(be,{active:u&&Me,completed:b.progress.ready,total:b.progress.total,label:"Loading diagnostic fact sources",error:u?b.progressError:null,modules:b.modules,updating:b.modules.some(h=>h.status==="updating")}),f,t.jsx(O,{title:"Executive Findings",subtitle:"Top observations aggregate telemetry",className:"span-all",children:t.jsx("div",{className:"executive-grid",children:e.diagnostics.slice(0,3).map((h,$)=>t.jsxs("article",{className:`executive-card tone-${$+1}`,children:[t.jsx("span",{children:$+1}),t.jsx("strong",{children:h.title}),t.jsx("p",{children:h.finding})]},h.title))})}),t.jsx(ft,{model:e,contextRuntime:s,includeArchived:a,sourceKey:i,sourceRevision:n,onOpenInvestigator:o,onCopyCallLink:l}),t.jsx("div",{className:"diagnostic-sections",children:e.diagnostics.map(h=>t.jsx(St,{section:h,calls:Ct(h,e.calls),onOpenInvestigator:o,onCopyCallLink:l},h.title))}),t.jsxs("aside",{className:"side-panel",children:[t.jsx(O,{title:"Notebook Index",subtitle:"Jump to section",children:t.jsx("div",{className:"index-list",children:e.diagnostics.map((h,$)=>t.jsxs("span",{children:[t.jsx("i",{children:$+1}),h.title,t.jsx(Q,{label:h.status,tone:h.status==="Ready"?"green":"orange"})]},h.title))})}),t.jsx(ot,{sources:z,activeSourceKey:r,facts:p,selectedFact:v,factState:x,factSort:A,onFactSortChange:h=>S($=>({...$,[r]:h})),onSelectSource:Ee,onSelectFact:Ie,canLoadMoreFacts:De,loadingMoreFacts:b.sourceIsUpdating(r),onLoadMoreFacts:Pe,onOpenInvestigator:o,onCopyCallLink:l}),t.jsx(rt,{selectedFact:v,calls:$e,status:te,usingLiveFacts:N,liveResult:K,factCallSort:R,rowLoadControls:c,onFactCallSortChange:M,onLoadMore:E.loadMore,onOpenInvestigator:o,onCopyCallLink:l})]})]})}function St({section:e,calls:s,onOpenInvestigator:a,onCopyCallLink:i}){return t.jsxs(O,{title:e.title,subtitle:e.metric,children:[t.jsxs("div",{className:"diagnostic-row",children:[t.jsx(Ve,{series:e.series,yLabel:e.title,height:180}),t.jsxs("div",{children:[t.jsx("h3",{children:"Finding"}),t.jsx("p",{children:e.finding}),t.jsx(Q,{label:`${e.confidence} confidence`,tone:e.confidence==="High"?"green":"orange"})]}),t.jsxs("div",{className:"mini-evidence",children:[t.jsx("span",{children:"Evidence"}),t.jsx("strong",{children:e.metric}),t.jsx("small",{children:e.status})]})]}),t.jsxs("div",{className:"diagnostic-call-list",children:[t.jsxs("div",{className:"section-heading compact",children:[t.jsx("h3",{children:"Evidence Calls"}),t.jsx("span",{children:s.length?`${s.length} aggregate rows`:"No matching calls"})]}),s.length?t.jsx("ol",{className:"thread-mini-timeline",children:s.map(n=>t.jsxs("li",{className:"diagnostic-call-row has-row-action",tabIndex:0,"aria-label":`Open investigator for diagnostic call ${n.thread} ${n.model}`,onClick:()=>a(n.id),onKeyDown:c=>{(c.key==="Enter"||c.key===" ")&&(c.preventDefault(),a(n.id))},children:[t.jsx("span",{children:n.time}),t.jsx("strong",{children:n.thread}),t.jsxs("em",{children:[n.model," / ",n.effort," - ",C(n.totalTokens)," tokens - ",q(n.cachedPct)," cache -"," ",Qe(n.cost)]}),t.jsxs("span",{className:"table-action-group",children:[t.jsxs("button",{className:"table-action-button",type:"button","aria-label":`Open investigator for diagnostic call ${n.thread} ${n.model}`,onKeyDown:G,onClick:c=>{c.stopPropagation(),a(n.id)},children:[t.jsx(H,{size:14})," Open"]}),t.jsxs("button",{className:"table-action-button",type:"button","aria-label":`Copy link for diagnostic call ${n.thread} ${n.model}`,onKeyDown:G,onClick:c=>{c.stopPropagation(),i(n.id)},children:[t.jsx(W,{size:14})," Copy"]})]})]},`${e.title}-${n.id}`))}):t.jsx("p",{className:"empty-state",children:"No loaded aggregate call rows match diagnostic section."})]})]})}function Ct(e,s){const a=e.title.toLowerCase(),i=[...s];return a.includes("cache")?i.filter(n=>n.signal==="cache-risk"||n.cachedPct<35||n.uncachedInput>5e4).sort((n,c)=>n.cachedPct-c.cachedPct||c.uncachedInput-n.uncachedInput).slice(0,3):a.includes("thread")?i.sort((n,c)=>c.totalTokens-n.totalTokens||c.cost-n.cost).slice(0,3):a.includes("tool")||a.includes("command")?i.filter(n=>n.tags.some(c=>["file-heavy","subagent","large"].includes(c))).sort((n,c)=>c.input-n.input).slice(0,3):a.includes("usage")||a.includes("drain")?i.sort((n,c)=>c.credits-n.credits||c.totalTokens-n.totalTokens).slice(0,3):i.sort((n,c)=>c.totalTokens-n.totalTokens).slice(0,3)}function ve(e){return[{fact_type:"cache",fact_name:"large_uncached_input",calls:e.filter(a=>a.signal==="cache-risk"||a.cachedPct<35||a.uncachedInput>5e4)},{fact_type:"model",fact_name:"high_effort",calls:e.filter(a=>a.effort.toLowerCase()==="high")},{fact_type:"tool",fact_name:"file_heavy_or_subagent",calls:e.filter(a=>a.tags.some(i=>["file-heavy","subagent","large"].includes(i)))},{fact_type:"usage",fact_name:"high_credit_call",calls:[...e].sort((a,i)=>i.credits-a.credits).slice(0,5)}].filter(a=>a.calls.length).map(a=>jt(a.fact_type,a.fact_name,a.calls)).sort((a,i)=>J(i.associated_uncached_input_tokens)-J(a.associated_uncached_input_tokens)||J(i.associated_total_tokens)-J(a.associated_total_tokens))}function we(e,s){const a=String(e.fact_name??""),i=`${e.fact_type??""} ${e.fact_name??""}`.toLowerCase();if(a==="large_uncached_input"||i.includes("cache")||i.includes("uncached"))return s.filter(n=>n.signal==="cache-risk"||n.cachedPct<35||n.uncachedInput>5e4).sort((n,c)=>c.uncachedInput-n.uncachedInput).slice(0,5);if(a==="high_effort"||i.includes("effort")||i.includes("model"))return s.filter(n=>n.effort.toLowerCase()==="high").sort((n,c)=>c.totalTokens-n.totalTokens).slice(0,5);if(a==="file_heavy_or_subagent"||i.includes("tool")||i.includes("function")||i.includes("file")||i.includes("subagent")||i.includes("command")){const n=s.filter(c=>c.tags.some(o=>["file-heavy","subagent","large"].includes(o)));return(n.length?n:s).sort((c,o)=>o.input-c.input).slice(0,5)}return[...s].sort((n,c)=>c.credits-n.credits||c.totalTokens-n.totalTokens).slice(0,5)}function Ft(){const e=new URLSearchParams(window.location.search).get("diagnostic_source"),s=U.find(a=>a.key===e);return(s==null?void 0:s.key)??"facts"}function Se(e){var o;const s=(o=new URLSearchParams(window.location.search).get("diagnostic_fact"))==null?void 0:o.trim();if(!s)return null;const a=e.find(l=>Ce(l)===s||T(l)===s);if(a)return a;const[i,...n]=s.split(":"),c=n.join(":");return i||c?{fact_type:i,fact_name:c||"unknown"}:null}function Ce(e){return`${e.fact_type??""}:${e.fact_name??""}`}function he(e,s){const a=new URL(window.location.href);a.searchParams.set("view","diagnostics"),e==="facts"?a.searchParams.delete("diagnostic_source"):a.searchParams.set("diagnostic_source",e),s?a.searchParams.set("diagnostic_fact",Ce(s)):a.searchParams.delete("diagnostic_fact"),window.history.replaceState(null,"",a)}function ge(){return{status:"idle",message:"Static aggregate fallback"}}function $t(){return wt}export{Jt as DiagnosticsPage,Vt as diagnosticsCallsForCurrentUrl};
diff --git a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/EvidenceGrid.js b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/EvidenceGrid.js
index 43f244d7..318d5032 100644
--- a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/EvidenceGrid.js
+++ b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/EvidenceGrid.js
@@ -1,6 +1,6 @@
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+import{r as z,j as p}from"./dashboard-react.js";import{u as ft,g as mt,a as gt,f as U}from"./index2.js";import{al as pt}from"./router.js";import{c as bt,u as St}from"./App.js";/**
  * @license lucide-react v0.468.0 - ISC
  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const gt=mt("ChevronsRight",[["path",{d:"m6 17 5-5-5-5",key:"xnjwq"}],["path",{d:"m13 17 5-5-5-5",key:"17xmmf"}]]);function ot(){try{return typeof globalThis.localStorage>"u"?void 0:globalThis.localStorage}catch{return}}function pt(l,a,t){const e=ot();if(!e)return{...a,density:t??a.density};try{const s=JSON.parse(e.getItem(l)??"{}"),n=s.density==="compact"||s.density==="comfortable"?s.density:a.density,o=t??n,i=s.columnVisibility&&typeof s.columnVisibility=="object"?Object.fromEntries(Object.entries(s.columnVisibility).filter(r=>typeof r[1]=="boolean")):a.columnVisibility;return{density:o,columnVisibility:i}}catch{return a}}function ie(l,a,t){const[e,s]=z.useState(()=>pt(l,a,t));z.useEffect(()=>{var r;(r=ot())==null||r.setItem(l,JSON.stringify(e))},[e,l]);const n=z.useCallback(r=>{s(c=>({...c,density:typeof r=="function"?r(c.density):r}))},[]),o=z.useCallback(r=>{s(c=>({...c,columnVisibility:typeof 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g=this.measurementsCache.slice(0,m),v=new Array(i).fill(void 0);for(let f=0;f<m;f++){const _=g[f];_&&(v[_.lane]=f)}for(let f=m;f<t;f++){const _=n(f),S=this.laneAssignments.get(f);let b,C;const y=r==="estimate"||u.has(_);if(S!==void 0&&this.options.lanes>1){b=S;const M=v[b],k=M!==void 0?g[M]:void 0;C=k?k.end+this.options.gap:e+s}else{const M=this.options.lanes===1?g[f-1]:this.getFurthestMeasurement(g,f);C=M?M.end+this.options.gap:e+s,b=M?M.lane:f%this.options.lanes,this.options.lanes>1&&y&&this.laneAssignments.set(f,b)}const O=u.get(_),j=typeof O=="number"?O:this.options.estimateSize(f),A=C+j;g[f]={index:f,start:C,size:j,end:A,key:_,lane:b},v[b]=f}return 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c=this._flatMeasurements;if(this.options.lanes===1&&c!==null)r=this.options.getItemKey(t),i=c[t*2],o=c[t*2+1];else{const g=this.measurementsCache[t];if(!g)return;r=g.key,i=g.start,o=g.size}const u=this.itemSizeCache.get(r)??o,m=e-u;if(m!==0){const g=this.options.anchorTo==="end"&&((s=this.scrollState)==null?void 0:s.behavior)!=="smooth"&&this.getVirtualDistanceFromEnd()<=this.options.scrollEndThreshold,v=g?this.getTotalSize():0,f=((n=this.scrollState)==null?void 0:n.behavior)!=="smooth"&&(this.shouldAdjustScrollPositionOnItemSizeChange!==void 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this.scrollElement)return this.options.horizontal?this.scrollElement.scrollWidth-this.scrollElement.clientWidth:this.scrollElement.scrollHeight-this.scrollElement.clientHeight;{const t=this.scrollElement.document.documentElement;return this.options.horizontal?t.scrollWidth-this.scrollElement.innerWidth:t.scrollHeight-this.scrollElement.innerHeight}},this.getVirtualDistanceFromEnd=()=>Math.max(this.getTotalSize()-this.getSize()-this.getScrollOffset(),0),this.getDistanceFromEnd=()=>Math.max(this.getMaxScrollOffset()-this.getScrollOffset(),0),this.isAtEnd=(t=this.options.scrollEndThreshold)=>this.getDistanceFromEnd()<=t,this.getOffsetForAlignment=(t,e,s=0)=>{if(!this.scrollElement)return 0;const n=this.getSize(),o=this.getScrollOffset();e==="auto"&&(e=t>=o+n?"end":"start"),e==="center"?t+=(s-n)/2:e==="end"&&(t-=n);const i=this.getMaxScrollOffset();return Math.max(Math.min(i,t),0)},this.getOffsetForIndex=(t,e="auto")=>{t=Math.max(0,Math.min(t,this.options.count-1));const 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this.elementsCache)if(u===i){this.elementsCache.delete(c);break}return}this.shouldMeasureDuringScroll(l)&&this.resizeItem(l,this.options.measureElement(i,n,this))};this.options.useAnimationFrameWithResizeObserver?requestAnimationFrame(o):o()})}));return{disconnect:()=>{var s;(s=e())==null||s.disconnect(),t=null},observe:s=>{var n;return(n=e())==null?void 0:n.observe(s,{box:"border-box"})},unobserve:s=>{var n;return(n=e())==null?void 0:n.unobserve(s)}}})(),this.range=null,this.setOptions=t=>{var e,s;const n={debug:!1,initialOffset:0,overscan:1,paddingStart:0,paddingEnd:0,scrollPaddingStart:0,scrollPaddingEnd:0,horizontal:!1,getItemKey:Ct,rangeExtractor:wt,onChange:()=>{},measureElement:Tt,initialRect:{width:0,height:0},scrollMargin:0,gap:0,indexAttribute:"data-index",initialMeasurementsCache:[],lanes:1,anchorTo:"start",followOnAppend:!1,scrollEndThreshold:1,isScrollingResetDelay:150,enabled:!0,isRtl:!1,useScrollendEvent:!1,useAnimationFrameWithResizeObserver:!1,laneAssignmentMode:"estimate",useCachedMeasurements:!1};for(const g in t){const v=t[g];v!==void 0&&(n[g]=v)}const o=this.options;let i=null,l=null,c=!1;if(o!==void 0&&o.enabled&&n.enabled&&n.anchorTo==="end"&&this.scrollElement!==null){const g=o.count,v=n.count,f=this.getMeasurements(),_=g>0?((e=f[0])==null?void 0:e.key)??o.getItemKey(0):null,b=g>0?((s=f[g-1])==null?void 0:s.key)??o.getItemKey(g-1):null;if(v!==g||g>0&&v>0&&(n.getItemKey(0)!==_||n.getItemKey(v-1)!==b)){c=!0;const y=g>0?this.getVirtualItemForOffset(this.getScrollOffset())??f[0]:null;y&&(i=[y.key,this.getScrollOffset()-y.start]);const O=n.followOnAppend===!0?"auto":n.followOnAppend||null;O&&v>g&&this.isAtEnd(o.scrollEndThreshold)&&(g===0||n.getItemKey(v-1)!==b)&&(l=O)}}this.options=n,c&&(this.pendingMin=0,this.itemSizeCacheVersion++);let u=!1,m=0;if(i&&this.scrollOffset!==null){const[g,v]=i,f=this.getMeasurements(),{count:_,getItemKey:b}=this.options;let S=0;for(;S<_&&b(S)!==g;)S++;if(S<_){const C=f[S];if(C){const y=C.start+v;y!==this.scrollOffset&&(m=y-this.scrollOffset,this.scrollOffset=y,u=!0)}}}(u||l)&&(this.pendingScrollAnchor=[u?i[0]:null,u?i[1]:0,l,m])},this.notify=t=>{var e,s;(s=(e=this.options).onChange)==null||s.call(e,this,t)},this.maybeNotify=R(()=>(this.calculateRange(),[this.isScrolling,this.range?this.range.startIndex:null,this.range?this.range.endIndex:null]),t=>{this.notify(t)},{key:!1,debug:()=>this.options.debug,initialDeps:[this.isScrolling,this.range?this.range.startIndex:null,this.range?this.range.endIndex:null]}),this.cleanup=()=>{this.unsubs.filter(Boolean).forEach(t=>t()),this.unsubs=[],this.observer.disconnect(),this.rafId!=null&&this.targetWindow&&(this.targetWindow.cancelAnimationFrame(this.rafId),this.rafId=null),this.scrollState=null,this.scrollElement=null,this.targetWindow=null},this._didMount=()=>()=>{this.cleanup()},this._willUpdate=()=>{var t;const e=this.options.enabled?this.options.getScrollElement():null;if(this.scrollElement!==e){if(this.cleanup(),!e){this.maybeNotify();return}if(this.scrollElement=e,this.scrollElement&&"ownerDocument"in this.scrollElement?this.targetWindow=this.scrollElement.ownerDocument.defaultView:this.targetWindow=((t=this.scrollElement)==null?void 0:t.window)??null,this.elementsCache.forEach(n=>{this.observer.observe(n)}),this.unsubs.push(this.options.observeElementRect(this,n=>{this.scrollRect=n,this.maybeNotify()})),this.unsubs.push(this.options.observeElementOffset(this,(n,o)=>{if(o&&this._intendedScrollOffset===null&&n===this.scrollOffset)return;this._intendedScrollOffset!==null&&Math.abs(n-this._intendedScrollOffset)<1.5&&(n=this._intendedScrollOffset),this._intendedScrollOffset=null,this.scrollAdjustments=0;const i=this.getScrollOffset();this.scrollDirection=o?i===n?this.scrollDirection:i<n?"forward":"backward":null,this.scrollOffset=n,this.isScrolling=o,this._flushIosDeferredIfReady(),this.scrollState&&this.scheduleScrollReconcile(),this.maybeNotify()})),"addEventListener"in this.scrollElement){const n=this.scrollElement,o=()=>{this._iosTouching=!0,this._iosJustTouchEnded=!1,this._iosTouchEndTimerId!==null&&this.targetWindow!=null&&(this.targetWindow.clearTimeout(this._iosTouchEndTimerId),this._iosTouchEndTimerId=null)},i=()=>{this._iosTouching=!1,!(!G()||this.targetWindow==null)&&(this._iosJustTouchEnded=!0,this._iosTouchEndTimerId=this.targetWindow.setTimeout(()=>{this._iosJustTouchEnded=!1,this._iosTouchEndTimerId=null,this._flushIosDeferredIfReady()},150))};n.addEventListener("touchstart",o,B),n.addEventListener("touchend",i,B),this.unsubs.push(()=>{n.removeEventListener("touchstart",o),n.removeEventListener("touchend",i),this._iosTouchEndTimerId!==null&&this.targetWindow!=null&&(this.targetWindow.clearTimeout(this._iosTouchEndTimerId),this._iosTouchEndTimerId=null)})}this._scrollToOffset(this.getScrollOffset(),{adjustments:void 0,behavior:void 0})}const s=this.pendingScrollAnchor;if(this.pendingScrollAnchor=null,s&&this.scrollElement&&this.options.enabled){const[n,o,i,l]=s;n!==null&&!i&&(G()&&(this.isScrolling||this._iosTouching||this._iosJustTouchEnded)?l!==0&&(this._iosDeferredAdjustment+=l):this._scrollToOffset(this.getScrollOffset(),{adjustments:void 0,behavior:void 0})),i&&this.scrollToEnd({behavior:i})}},this._flushIosDeferredIfReady=()=>{if(this._iosDeferredAdjustment===0||this.isScrolling||this._iosTouching||this._iosJustTouchEnded)return;const t=this.getScrollOffset(),e=this.getMaxScrollOffset();if(t<0||t>e)return;const s=this._iosDeferredAdjustment;this._iosDeferredAdjustment=0,this._scrollToOffset(t,{adjustments:this.scrollAdjustments+=s,behavior:void 0})},this.rafId=null,this.getSize=()=>this.options.enabled?(this.scrollRect=this.scrollRect??this.options.initialRect,this.scrollRect[this.options.horizontal?"width":"height"]):(this.scrollRect=null,0),this.getScrollOffset=()=>this.options.enabled?(this.scrollOffset=this.scrollOffset??(typeof this.options.initialOffset=="function"?this.options.initialOffset():this.options.initialOffset),this.scrollOffset):(this.scrollOffset=null,0),this.getFurthestMeasurement=(t,e)=>{const s=new Map,n=new Map;for(let o=e-1;o>=0;o--){const i=t[o];if(s.has(i.lane))continue;const l=n.get(i.lane);if(l==null||i.end>l.end?n.set(i.lane,i):i.end<l.end&&s.set(i.lane,!0),s.size===this.options.lanes)break}return n.size===this.options.lanes?Array.from(n.values()).sort((o,i)=>o.end===i.end?o.index-i.index:o.end-i.end)[0]:void 0},this.getMeasurementOptions=R(()=>[this.options.count,this.options.paddingStart,this.options.scrollMargin,this.options.getItemKey,this.options.enabled,this.options.lanes,this.options.laneAssignmentMode],(t,e,s,n,o,i,l)=>(this.prevLanes!==void 0&&this.prevLanes!==i&&(this.lanesChangedFlag=!0),this.prevLanes=i,this.pendingMin=null,{count:t,paddingStart:e,scrollMargin:s,getItemKey:n,enabled:o,lanes:i,laneAssignmentMode:l}),{key:!1}),this.getMeasurements=R(()=>[this.getMeasurementOptions(),this.itemSizeCacheVersion],({count:t,paddingStart:e,scrollMargin:s,getItemKey:n,enabled:o,lanes:i,laneAssignmentMode:l},c)=>{const u=this.itemSizeCache;if(!o)return this.measurementsCache=[],this.itemSizeCache.clear(),this.laneAssignments.clear(),[];if(this.laneAssignments.size>t)for(const f of this.laneAssignments.keys())f>=t&&this.laneAssignments.delete(f);this.lanesChangedFlag&&(this.lanesChangedFlag=!1,this.lanesSettling=!0,this.measurementsCache=[],this.itemSizeCache.clear(),this.laneAssignments.clear(),this.pendingMin=null),this.measurementsCache.length===0&&!this.lanesSettling&&(this.measurementsCache=this.options.initialMeasurementsCache,this.measurementsCache.forEach(f=>{this.itemSizeCache.set(f.key,f.size)}));const m=this.lanesSettling?0:this.pendingMin??0;if(this.pendingMin=null,this.lanesSettling&&this.measurementsCache.length===t&&(this.lanesSettling=!1),i===1){const f=this.options.gap,_=t*2;let b=this._flatMeasurements;if(!b||b.length<_){const y=new Float64Array(_);b&&m>0&&y.set(b.subarray(0,m*2)),b=y,this._flatMeasurements=b}let S;if(m===0)S=e+s;else{const y=m-1;S=b[y*2]+b[y*2+1]+f}for(let y=m;y<t;y++){const O=n(y),j=u.get(O),A=typeof j=="number"?j:this.options.estimateSize(y);b[y*2]=S,b[y*2+1]=A,S+=A+f}const C=xt(t,b,n);return this.measurementsCache=C,C}const g=this.measurementsCache.slice(0,m),v=new Array(i).fill(void 0);for(let f=0;f<m;f++){const _=g[f];_&&(v[_.lane]=f)}for(let f=m;f<t;f++){const _=n(f),b=this.laneAssignments.get(f);let S,C;const y=l==="estimate"||u.has(_);if(b!==void 0&&this.options.lanes>1){S=b;const M=v[S],k=M!==void 0?g[M]:void 0;C=k?k.end+this.options.gap:e+s}else{const M=this.options.lanes===1?g[f-1]:this.getFurthestMeasurement(g,f);C=M?M.end+this.options.gap:e+s,S=M?M.lane:f%this.options.lanes,this.options.lanes>1&&y&&this.laneAssignments.set(f,S)}const O=u.get(_),j=typeof O=="number"?O:this.options.estimateSize(f),A=C+j;g[f]={index:f,start:C,size:j,end:A,key:_,lane:S},v[S]=f}return this.measurementsCache=g,g},{key:!1,debug:()=>this.options.debug}),this.calculateRange=R(()=>[this.getMeasurements(),this.getSize(),this.getScrollOffset(),this.options.lanes],(t,e,s,n)=>t.length===0||e===0?(this.range=null,null):(this.range=Lt(t,e,s,n,n===1&&this._flatMeasurements!=null?this._flatMeasurements:null),this.range),{key:!1,debug:()=>this.options.debug}),this.getVirtualIndexes=R(()=>{let t=null,e=null;const s=this.calculateRange();return s&&(t=s.startIndex,e=s.endIndex),this.maybeNotify.updateDeps([this.isScrolling,t,e]),[this.options.rangeExtractor,this.options.overscan,this.options.count,t,e]},(t,e,s,n,o)=>n===null||o===null?[]:t({startIndex:n,endIndex:o,overscan:e,count:s}),{key:!1,debug:()=>this.options.debug}),this.indexFromElement=t=>{const e=this.options.indexAttribute,s=t.getAttribute(e);return s?parseInt(s,10):(console.warn(`Missing attribute name '${e}={index}' on measured element.`),-1)},this.shouldMeasureDuringScroll=t=>{var e;if(!this.scrollState||this.scrollState.behavior!=="smooth")return!0;const s=this.scrollState.index??((e=this.getVirtualItemForOffset(this.scrollState.lastTargetOffset))==null?void 0:e.index);if(s!==void 0&&this.range){const n=Math.max(this.options.overscan,Math.ceil((this.range.endIndex-this.range.startIndex)/2)),o=Math.max(0,s-n),i=Math.min(this.options.count-1,s+n);return t>=o&&t<=i}return!0},this.measureElement=t=>{if(!t){this.elementsCache.forEach((o,i)=>{o.isConnected||(this.observer.unobserve(o),this.elementsCache.delete(i))});return}const e=this.indexFromElement(t),s=this.options.getItemKey(e),n=this.elementsCache.get(s);n!==t&&(n&&this.observer.unobserve(n),this.observer.observe(t),this.elementsCache.set(s,t)),(!this.isScrolling||this.scrollState)&&this.shouldMeasureDuringScroll(e)&&this.resizeItem(e,this.options.measureElement(t,void 0,this))},this.resizeItem=(t,e)=>{var s,n;if(t<0||t>=this.options.count)return;let o,i,l;const c=this._flatMeasurements;if(this.options.lanes===1&&c!==null)l=this.options.getItemKey(t),i=c[t*2],o=c[t*2+1];else{const g=this.measurementsCache[t];if(!g)return;l=g.key,i=g.start,o=g.size}const u=this.itemSizeCache.get(l)??o,m=e-u;if(m!==0){const g=this.options.anchorTo==="end"&&((s=this.scrollState)==null?void 0:s.behavior)!=="smooth"&&this.getVirtualDistanceFromEnd()<=this.options.scrollEndThreshold,v=g?this.getTotalSize():0,f=((n=this.scrollState)==null?void 0:n.behavior)!=="smooth"&&(this.shouldAdjustScrollPositionOnItemSizeChange!==void 0?this.shouldAdjustScrollPositionOnItemSizeChange(this.measurementsCache[t]??{index:t,key:l,start:i,size:o,end:i+o,lane:0},m,this):i<this.getScrollOffset()+this.scrollAdjustments&&(!this.itemSizeCache.has(l)||this.scrollDirection!=="backward"));(this.pendingMin===null||t<this.pendingMin)&&(this.pendingMin=t),this.itemSizeCache.set(l,e),this.itemSizeCacheVersion++,g?this.applyScrollAdjustment(this.getTotalSize()-v):f&&this.applyScrollAdjustment(m),this.notify(!1)}},this.getVirtualItems=R(()=>[this.getVirtualIndexes(),this.getMeasurements()],(t,e)=>{const s=[];for(let n=0,o=t.length;n<o;n++){const i=t[n],l=e[i];s.push(l)}return s},{key:!1,debug:()=>this.options.debug}),this.getVirtualItemForOffset=t=>{const e=this.getMeasurements();if(e.length===0)return;const s=this._flatMeasurements,n=this.options.lanes===1&&s!=null,o=ct(0,e.length-1,n?i=>s[i*2]:i=>ot(e[i]).start,t);return ot(e[o])},this.getMaxScrollOffset=()=>{if(!this.scrollElement)return 0;if("scrollHeight"in this.scrollElement)return this.options.horizontal?this.scrollElement.scrollWidth-this.scrollElement.clientWidth:this.scrollElement.scrollHeight-this.scrollElement.clientHeight;{const t=this.scrollElement.document.documentElement;return this.options.horizontal?t.scrollWidth-this.scrollElement.innerWidth:t.scrollHeight-this.scrollElement.innerHeight}},this.getVirtualDistanceFromEnd=()=>Math.max(this.getTotalSize()-this.getSize()-this.getScrollOffset(),0),this.getDistanceFromEnd=()=>Math.max(this.getMaxScrollOffset()-this.getScrollOffset(),0),this.isAtEnd=(t=this.options.scrollEndThreshold)=>this.getDistanceFromEnd()<=t,this.getOffsetForAlignment=(t,e,s=0)=>{if(!this.scrollElement)return 0;const n=this.getSize(),o=this.getScrollOffset();e==="auto"&&(e=t>=o+n?"end":"start"),e==="center"?t+=(s-n)/2:e==="end"&&(t-=n);const i=this.getMaxScrollOffset();return Math.max(Math.min(i,t),0)},this.getOffsetForIndex=(t,e="auto")=>{t=Math.max(0,Math.min(t,this.options.count-1));const s=this.getSize(),n=this.getScrollOffset(),o=this.measurementsCache[t];if(!o)return;if(e==="auto")if(o.end>=n+s-this.options.scrollPaddingEnd)e="end";else if(o.start<=n+this.options.scrollPaddingStart)e="start";else return[n,e];if(e==="end"&&t===this.options.count-1)return[this.getMaxScrollOffset(),e];const i=e==="end"?o.end+this.options.scrollPaddingEnd:o.start-this.options.scrollPaddingStart;return[this.getOffsetForAlignment(i,e,o.size),e]},this.scrollToOffset=(t,{align:e="start",behavior:s="auto"}={})=>{const n=this.getOffsetForAlignment(t,e),o=this.now();this.scrollState={index:null,align:e,behavior:s,startedAt:o,lastTargetOffset:n,stableFrames:0},this._scrollToOffset(n,{adjustments:void 0,behavior:s}),this.scheduleScrollReconcile()},this.scrollToIndex=(t,{align:e="auto",behavior:s="auto"}={})=>{t=Math.max(0,Math.min(t,this.options.count-1));const n=this.getOffsetForIndex(t,e);if(!n)return;const[o,i]=n,l=this.now();this.scrollState={index:t,align:i,behavior:s,startedAt:l,lastTargetOffset:o,stableFrames:0},this._scrollToOffset(o,{adjustments:void 0,behavior:s}),this.scheduleScrollReconcile()},this.scrollBy=(t,{behavior:e="auto"}={})=>{const s=this.getScrollOffset()+t,n=this.now();this.scrollState={index:null,align:"start",behavior:e,startedAt:n,lastTargetOffset:s,stableFrames:0},this._scrollToOffset(s,{adjustments:void 0,behavior:e}),this.scheduleScrollReconcile()},this.scrollToEnd=({behavior:t="auto"}={})=>{if(this.options.count>0){this.scrollToIndex(this.options.count-1,{align:"end",behavior:t});return}this.scrollToOffset(Math.max(this.getTotalSize()-this.getSize(),0),{behavior:t})},this.getTotalSize=()=>{var t;const e=this.getMeasurements();let s;if(e.length===0)s=this.options.paddingStart;else if(this.options.lanes===1){const n=e.length-1,o=this._flatMeasurements;o!=null?s=o[n*2]+o[n*2+1]:s=((t=e[n])==null?void 0:t.end)??0}else{const n=Array(this.options.lanes).fill(null);let o=e.length-1;for(;o>=0&&n.some(i=>i===null);){const i=e[o];n[i.lane]===null&&(n[i.lane]=i.end),o--}s=Math.max(...n.filter(i=>i!==null))}return Math.max(s-this.options.scrollMargin+this.options.paddingEnd,0)},this.takeSnapshot=()=>{const t=[];if(this.itemSizeCache.size===0)return t;const e=this.getMeasurements();for(const s of e)s&&this.itemSizeCache.has(s.key)&&t.push({index:s.index,key:s.key,start:s.start,size:s.size,end:s.end,lane:s.lane});return t},this._scrollToOffset=(t,{adjustments:e,behavior:s})=>{this._intendedScrollOffset=t+(e??0),this.options.scrollToFn(t,{behavior:s,adjustments:e},this)},this.measure=()=>{this.pendingMin=null,this.itemSizeCache.clear(),this.laneAssignments.clear(),this.itemSizeCacheVersion++,this.notify(!1)},this.setOptions(a)}applyScrollAdjustment(a,t){a!==0&&(G()&&(this.isScrolling||this._iosTouching||this._iosJustTouchEnded)?this._iosDeferredAdjustment+=a:(this._scrollToOffset(this.getScrollOffset(),{adjustments:this.scrollAdjustments+=a,behavior:t}),this.scrollOffset!==null&&(this.scrollOffset+=this.scrollAdjustments,this.scrollAdjustments=0)))}scheduleScrollReconcile(){if(!this.targetWindow){this.scrollState=null;return}this.rafId==null&&(this.rafId=this.targetWindow.requestAnimationFrame(()=>{this.rafId=null,this.reconcileScroll()}))}reconcileScroll(){if(!this.scrollState||!this.scrollElement)return;if(this.now()-this.scrollState.startedAt>5e3){this.scrollState=null;return}const 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p.jsx("li",{style:{height:d.size,transform:`translateY(${d.start}px)`},children:p.jsxs("button",{type:"button",className:T?x.mobileRowSelected:x.mobileRow,"aria-label":o.actionLabel(h.original,w),"aria-pressed":T,"data-row-index":d.index,onClick:()=>et(h.original),onDoubleClick:()=>{var E;return(E=S??b)==null?void 0:E(h.original)},onMouseEnter:y&&b?()=>b(h.original):void 0,onKeyDown:E=>st(E,d.index,h.original),children:[p.jsx("span",{className:x.rank,"aria-hidden":"true",children:w}),p.jsxs("span",{className:x.mobileCopy,children:[p.jsx("strong",{children:o.primary(h.original,w)}),p.jsx("small",{children:o.secondary(h.original,w)})]})]})},h.id)})})}),p.jsx("p",{className:x.rowCount,children:M.translateText(`${I.length.toLocaleString()} ranked evidence rows`)})]});const nt=Math.max(W.getTotalSize(),720);return p.jsxs("section",{className:x.grid,"aria-label":k,children:[J,ht?p.jsxs("button",{className:x.continuationCue,type:"button","aria-label":"Show more columns",title:"Show more 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0,style:{width:E.column.getSize()},children:U(E.column.columnDef.cell,E.getContext())},E.id))},h.id)})})]})}),I.length?null:p.jsx("p",{className:x.empty,role:"status",children:X}),p.jsx("p",{className:x.rowCount,children:M.translateText(`${I.length.toLocaleString()} ranked evidence rows`)})]})}export{ce as E,ae as u};
diff --git a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/ExploreWorkspaceSwitcher.js b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/ExploreWorkspaceSwitcher.js
index c8e37727..1c42722b 100644
--- a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/ExploreWorkspaceSwitcher.js
+++ b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/ExploreWorkspaceSwitcher.js
@@ -1 +1 @@
-import{j as r}from"./dashboard-react.js";import{S as o}from"./Primitives.js";const s=[{value:"calls",label:"Calls"},{value:"threads",label:"Threads"},{value:"tools",label:"Tools"},{value:"files",label:"Files"}];function n({current:l,onValueChange:e}){return r.jsx(o,{label:"Explore workspace",options:s,value:l,onValueChange:e})}function i(l=window.location.search){const e=new URLSearchParams(l).get("explore");return e==="tools"||e==="files"?e:"calls"}function p(l,e=window.location.href){const a=new URL(e);return a.searchParams.set("view","calls"),l==="calls"?a.searchParams.delete("explore"):a.searchParams.set("explore",l),a}export{n as E,i as a,p as e};
+import{j as r}from"./dashboard-react.js";import"./App.js";import{S as o}from"./Primitives.js";const s=[{value:"calls",label:"Calls"},{value:"threads",label:"Threads"},{value:"tools",label:"Tools"},{value:"files",label:"Files"}];function i({current:l,onValueChange:e}){return r.jsx(o,{label:"Explore workspace",options:s,value:l,onValueChange:e})}function p(l=window.location.search){const e=new URLSearchParams(l).get("explore");return e==="tools"||e==="files"?e:"calls"}function u(l,e=window.location.href){const a=new URL(e);return a.searchParams.set("view","calls"),l==="calls"?a.searchParams.delete("explore"):a.searchParams.set("explore",l),a}export{i as E,p as a,u as e};
diff --git a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/InvestigatorPage.js b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/InvestigatorPage.js
index 8c9bfb9b..4a2994d2 100644
--- a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/InvestigatorPage.js
+++ b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/InvestigatorPage.js
@@ -1,11 +1,11 @@
-import{r as y,j as n}from"./dashboard-react.js";import{u as q}from"./useQuery.js";import{c as ee,z as te,A as ne,E as ie,B as je,a as I,s as B,b as we,q as w,o as ke,l as H,k as Se,w as Ce,D as Le,R as Ne,S as $e,F as V,N as Re,j as Ae}from"./App.js";import{q as se}from"./queryOptions.js";import{d as Ee,s as Me,u as Pe,f as Ie}from"./diagnosticsQueries.js";import{P as Fe}from"./PageLoadProgress.js";import{a as j,I as W,B as N,M as E,b as $}from"./Primitives.js";import{v as Te,V as Oe}from"./UsageConstellation.js";import{u as Ke,E as De}from"./EvidenceGrid.js";import{S as ze}from"./shield-check.js";import"./useBaseQuery.js";import"./dashboardRouter.js";import"./router.js";import"./infiniteQueryOptions.js";import"./triangle-alert.js";import"./index2.js";/**
+import{r as y,j as n}from"./dashboard-react.js";import{u as ee}from"./useQuery.js";import{c as te,z as ne,A as ie,E as se,B as we,a as F,s as H,b as ke,q as w,o as Se,l as V,k as Ce,w as Le,u as Ne,D as $e,R as Re,S as Ae,F as W,N as Ee,j as Ie}from"./App.js";import{q as ae}from"./queryOptions.js";import{d as Me,s as Pe,u as Fe,f as Te}from"./diagnosticsQueries.js";import{P as Oe}from"./PageLoadProgress.js";import{a as j,I as G,B as $,M as I,b as R}from"./Primitives.js";import{v as Ke,V as De}from"./UsageConstellation.js";import{u as ze,E as Qe}from"./EvidenceGrid.js";import{S as Ue}from"./shield-check.js";import"./useBaseQuery.js";import"./dashboardRouter.js";import"./router.js";import"./infiniteQueryOptions.js";import"./triangle-alert.js";import"./index2.js";/**
  * @license lucide-react v0.468.0 - ISC
  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const Qe=ee("ArrowRight",[["path",{d:"M5 12h14",key:"1ays0h"}],["path",{d:"m12 5 7 7-7 7",key:"xquz4c"}]]);/**
+ */const Be=te("ArrowRight",[["path",{d:"M5 12h14",key:"1ays0h"}],["path",{d:"m12 5 7 7-7 7",key:"xquz4c"}]]);/**
  * @license lucide-react v0.468.0 - ISC
  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const Ue=ee("ArrowUpRight",[["path",{d:"M7 7h10v10",key:"1tivn9"}],["path",{d:"M7 17 17 7",key:"1vkiza"}]]);async function Be(e,t={}){const i=ae(t);return i.set("goal",t.goal??"token_waste"),i.set("detail_mode","compact"),re(e,"/api/investigations/agentic",i,"Investigation",t.signal)}async function He(e,t,i={}){const s=ae(i);return s.set("question",t.trim()||"Where is avoidable token waste concentrated?"),s.set("min_occurrences",String(Math.max(1,i.minOccurrences??2))),re(e,"/api/investigations/walk",s,"Local investigation trace",i.signal)}function ae(e){const t=new URLSearchParams({evidence_limit:String(Math.max(1,e.evidenceLimit??8))});return e.includeArchived&&t.set("include_archived","1"),t}async function re(e,t,i,s,a){Ve(e);const o=await fetch(`${t}?${i.toString()}`,{headers:{Accept:"application/json","X-Codex-Usage-Token":e.apiToken},cache:"no-store",signal:a}),u=await o.json().catch(()=>({}));if(!o.ok)throw new Error(typeof u.error=="string"?u.error:`${s} failed with HTTP ${o.status}`);return u}function Ve(e){if(e.fileMode||window.location.protocol==="file:")throw new Error("Live investigations require the localhost dashboard server.");if(!e.apiToken)throw new Error("Live investigations require the localhost dashboard API token.")}const G=ie("investigator-agentic"),J=ie("investigator-walk");function We(e){var s;const t=Math.max(1,e.evidenceLimit),i=((s=e.goal)==null?void 0:s.trim())||"token_waste";return se({queryKey:ne(G,oe(e),ce(e),i,t),queryFn:({signal:a})=>Be(e.runtime,{evidenceLimit:t,goal:i,includeArchived:e.includeArchived,signal:a}),...te(G.dataClass)})}function X(e){return Ee(e)}function Ge(e){const t=Math.max(1,e.evidenceLimit),i=Math.max(1,e.minOccurrences??2),s=Je(e.question);return se({queryKey:ne(J,oe(e),ce(e),s,t,i),queryFn:({signal:a})=>He(e.runtime,s,{evidenceLimit:t,includeArchived:e.includeArchived,minOccurrences:i,signal:a}),...te(J.dataClass)})}function oe(e){return je({sourceKey:e.sourceKey??(e.runtime.fileMode?"static-file":"local-api"),sourceRevision:e.sourceRevision})}function ce(e){return{historyScope:e.includeArchived?"all":"active"}}function Je(e){return e.trim()||"Where is avoidable token waste concentrated?"}const Xe="_answerBand_qswbx_1",Ye="_answerCopy_qswbx_29",Ze="_answerMetrics_qswbx_57",M={answerBand:Xe,answerCopy:Ye,answerMetrics:Ze};function qe({findingTitle:e,rows:t,onOpenCall:i,onCopyCallLink:s,onOpenThread:a}){const[o,u]=y.useState([{id:"tokens",desc:!0}]),l=Ke("codexUsageInvestigationLedger",{density:"compact",columnVisibility:{detail:!1,source:!1}}),m=y.useMemo(()=>[{accessorKey:"thread",header:"Thread",size:220},{accessorKey:"pattern",header:"Pattern",size:160},{accessorKey:"events",header:"Events",size:90,cell:r=>n.jsx("span",{className:"num",children:Number(r.getValue()).toLocaleString()})},{accessorKey:"tokens",header:"Tokens",size:110,cell:r=>n.jsx("span",{className:"num",children:I(Number(r.getValue()))})},{accessorKey:"confidence",header:"Confidence",size:120,cell:r=>{const c=String(r.getValue());return n.jsx(j,{tone:c==="high"?"positive":c==="medium"?"caution":"neutral",children:c})}},{accessorKey:"value",header:"Evidence",size:220},{accessorKey:"detail",header:"Detail",size:210},{accessorKey:"source",header:"Source",size:190},{id:"open",header:"Open",size:116,enableSorting:!1,cell:r=>{const c=r.row.original,f=c.recordId?"Open call":c.thread!=="Aggregate"?"Open thread":"No linked record";return n.jsxs("div",{className:"table-action-group",children:[n.jsx(W,{disabled:!c.recordId&&c.thread==="Aggregate","aria-label":`${f} for ${c.pattern}`,title:f,onKeyDown:B,onClick:p=>{p.stopPropagation(),Y(c,i,a)},children:n.jsx(Ue,{})}),c.recordId?n.jsx(W,{"aria-label":`Copy call link for ${c.pattern}`,title:"Copy call link",onKeyDown:B,onClick:p=>{p.stopPropagation(),s(c.recordId)},children:n.jsx(we,{})}):null]})}}],[s,i,a]);return n.jsx(De,{ariaLabel:`Evidence ledger for ${e}`,columns:m,data:t,identityColumnId:"thread",lockedColumnIds:["open"],getRowId:r=>r.id,mobile:{primary:r=>r.thread,secondary:r=>`${r.pattern} · ${r.events.toLocaleString()} events · ${I(r.tokens)} tokens`,actionLabel:r=>r.recordId?`Open call evidence for ${r.pattern}`:`Open thread evidence for 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s=t!=null&&t.findings.length?t.findings.map((u,l)=>dt(u,l)):ht(e),a=ut(i),o=pt([...s,...a,gt(e.calls)]).filter(u=>!!u).sort((u,l)=>l.impactScore-u.impactScore||l.evidenceCount-u.evidenceCount);return{findings:o,evidence:o.flatMap(u=>u.evidence),caveats:(t==null?void 0:t.caveats)??["Local Codex logs only; this is not an official OpenAI usage ledger.","Static fallback findings use loaded aggregate rows and cannot identify shell or file rediscovery directly."],sourceReports:(t==null?void 0:t.summary.source_reports)??[],live:!!t}}function ct(e,t,i){const s=e.flatMap(a=>{const o=new Map;for(const u of a.evidence){const l=u.thread||"Aggregate";o.set(l,[...o.get(l)??[],u])}return o.size||o.set("Aggregate",[]),[...o.entries()].map(([u,l])=>({id:`${a.id}:${u}`,thread:u,pattern:a.category,score:Math.max(1,l.reduce((m,r)=>m+Math.max(r.events,1),0)),tokens:l.reduce((m,r)=>m+r.tokens,0),finding:a.title}))});return{schema:Te,id:"waste-fingerprint-matrix",title:"Waste fingerprint 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we({sourceKey:e.sourceKey??(e.runtime.fileMode?"static-file":"local-api"),sourceRevision:e.sourceRevision})}function de(e){return{historyScope:e.includeArchived?"all":"active"}}function Ye(e){return e.trim()||"Where is avoidable token waste concentrated?"}const Ze="_answerBand_qswbx_1",qe="_answerCopy_qswbx_29",et="_answerMetrics_qswbx_57",M={answerBand:Ze,answerCopy:qe,answerMetrics:et};function 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s=t!=null&&t.findings.length?t.findings.map((l,d)=>ut(l,d)):pt(e),a=gt(i),o=ft([...s,...a,mt(e.calls)]).filter(l=>!!l).sort((l,d)=>d.impactScore-l.impactScore||d.evidenceCount-l.evidenceCount);return{findings:o,evidence:o.flatMap(l=>l.evidence),caveats:(t==null?void 0:t.caveats)??["Local Codex logs only; this is not an official OpenAI usage ledger.","Static fallback findings use loaded aggregate rows and cannot identify shell or file rediscovery directly."],sourceReports:(t==null?void 0:t.summary.source_reports)??[],live:!!t}}function lt(e,t,i){const s=e.flatMap(a=>{const o=new Map;for(const l of a.evidence){const d=l.thread||"Aggregate";o.set(d,[...o.get(d)??[],l])}return o.size||o.set("Aggregate",[]),[...o.entries()].map(([l,d])=>({id:`${a.id}:${l}`,thread:l,pattern:a.category,score:Math.max(1,d.reduce((p,r)=>p+Math.max(r.events,1),0)),tokens:d.reduce((p,r)=>p+r.tokens,0),finding:a.title}))});return{schema:Ke,id:"waste-fingerprint-matrix",title:"Waste fingerprint 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ut(e,t){const i=O(e.finding,t),s=he(e.confidence),a=e.evidence.map((l,d)=>ht(i,e,l,d)),o=vt(e.evidence_summary,a,e.evidence_count);return{id:i,title:e.finding,category:A(e.finding),confidence:s,tone:bt(e.finding,s),summary:e.why_it_matters||"The local report found a repeatable aggregate signal worth reviewing.",action:e.recommended_action||"Inspect the strongest supporting evidence before changing the workflow.",verification:e.verify_with??[],missingAccess:e.missing_access||"No additional access is required for the aggregate evidence.",privacyNote:e.privacy_notes||"No raw fragments are included.",evidence:a,evidenceCount:Math.max(e.evidence_count,a.length),impactScore:o,source:"Agentic investigation"}}function ht(e,t,i,s){const a=wt(i.primary_recommendation);return{id:`${e}:evidence:${s}`,findingId:e,recordId:v(i.record_id),thread:v(i.thread_name)||v(i.thread_key)||v(i.thread)||"Aggregate",pattern:v(i.candidate_kind)||v(i.command_family)||A(t.finding),events:E(i.occurrences??i.call_count??i.read_events??1),tokens:E(i.total_tokens??i.max_total_tokens??i.allocated_output_token_sum),value:v(i.candidate_explanation)||v(i.recommendation)||"Supporting activity",confidence:he(t.confidence),action:v(i.recommended_action)||v(a.action)||t.recommended_action,detail:v(i.event_timestamp)||v(i.basename)||v(i.extension),source:"Agentic investigation"}}function gt(e){return w.flatMap((t,i)=>{var l;if(!ct.has(t.key)||!e[t.key])return[];const 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t=e.filter(i=>i.status!=="no_evidence");return t.length?n.jsx("div",{className:C.traceResults,children:t.slice(0,5).map((i,s)=>n.jsxs("article",{children:[n.jsx(j,{tone:Number(i.score??0)>=60?"positive":"caution",children:String(i.status??"evidence")}),n.jsx("strong",{children:String(i.hypothesis??i.scan_type??"Local pattern")}),n.jsxs("span",{children:[Number(i.score??0).toLocaleString()," score"]})]},`${i.scan_type??"branch"}-${s}`))}):n.jsx("p",{className:C.emptyState,children:"No supported local pattern met the current threshold."})}function Vt(e,t){const i=e.find(a=>a.id===t);if(i)return i;const s=Number(t);return Number.isFinite(s)&&s>0?e[s-1]??e[0]:e[0]}function Wt(){return new URLSearchParams(window.location.search).get("finding")??""}function Gt(e,t){return[...e].sort((i,s)=>s.totalTokens-i.totalTokens).slice(0,t)}function Jt(e,t){const i=JSON.stringify(t,null,2),s=new 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diff --git a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/LineChart.js b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/LineChart.js
index fb0a5e84..a85d3e67 100644
--- a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/LineChart.js
+++ b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/LineChart.js
@@ -1 +1 @@
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diff --git a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/OverviewPage.js b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/OverviewPage.js
index 92b92bd9..3830962f 100644
--- a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/OverviewPage.js
+++ b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/OverviewPage.js
@@ -1 +1 @@
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t=e.reduce((a,n)=>({totalTokens:a.totalTokens+n.totalTokens,cachedInputTokens:a.cachedInputTokens+n.cachedInput,uncachedInputTokens:a.uncachedInputTokens+n.uncachedInput,outputTokens:a.outputTokens+n.output,reasoningOutputTokens:a.reasoningOutputTokens+n.reasoningOutput,estimatedCostUsd:a.estimatedCostUsd+n.cost,estimatedCredits:a.estimatedCredits+n.credits}),{totalTokens:0,cachedInputTokens:0,uncachedInputTokens:0,outputTokens:0,reasoningOutputTokens:0,estimatedCostUsd:0,estimatedCredits:0}),o=t.cachedInputTokens+t.uncachedInputTokens;return{basis:"loaded",calls:e.length,...t,cachePercent:o>0?t.cachedInputTokens/o*100:0}}function ve(e){return e?{basis:"scope",calls:e.visibleCalls,totalTokens:e.totalTokens,cachedInputTokens:e.cachedInputTokens,uncachedInputTokens:e.uncachedInputTokens,outputTokens:e.outputTokens,reasoningOutputTokens:e.reasoningOutputTokens,cachePercent:e.inputTokens>0?e.cachedInputTokens/e.inputTokens*100:0,estimatedCostUsd:e.estimatedCostUsd,estimatedCredits:e.usageCredits}:null}function be(e,t,o){var h,d;const a=(h=t==null?void 0:t.data)==null?void 0:h.rows.map(r=>({id:r.groupKey,day:r.groupKey,inputTokens:r.inputTokens,cachedTokens:r.cachedInputTokens,outputTokens:r.outputTokens,calls:r.modelCalls})).sort((r,c)=>r.day.localeCompare(c.day)),n=a!=null&&a.length?a:fe(e),s=n.length?t!=null&&t.error?{kind:"partial",message:"Focused summary unavailable; showing loaded call rows.",availableRows:n.length}:{kind:"ready"}:{kind:"empty",message:"No dated aggregate usage is available in this scope."},l=y(((d=t==null?void 0:t.data)==null?void 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accounting":"Loaded accounting",s=a?"calls in selected scope":"loaded calls",l=t.outputTokens+t.reasoningOutputTokens,h=[{id:"account-input",source:"account",target:"input",value:t.cachedInputTokens+t.uncachedInputTokens,evidenceKey:"reported:input"},{id:"account-generated",source:"account",target:"generated",value:l,evidenceKey:"reported:generated"},{id:"input-cached",source:"input",target:"cached",value:t.cachedInputTokens,evidenceKey:"reported:cached-input"},{id:"input-uncached",source:"input",target:"uncached",value:t.uncachedInputTokens,evidenceKey:"derived:uncached-input"},{id:"generated-visible",source:"generated",target:"output",value:t.outputTokens,evidenceKey:"reported:output"},{id:"generated-reasoning",source:"generated",target:"reasoning",value:t.reasoningOutputTokens,evidenceKey:"reported:reasoning-output"}].filter(d=>d.value>0);return{schema:L,id:"overview-token-accounting",title:a?"Token accounting in scope":"Loaded token accounting",description:a?"The four reported 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i.jsxs("div",{className:b.page,children:[i.jsxs("header",{className:b.pageHeader,children:[i.jsxs("div",{children:[i.jsx("p",{className:b.eyebrow,children:"Usage pulse"}),i.jsx("h1",{children:"Overview"}),i.jsx("p",{children:"The important changes first, with direct paths into supporting evidence."})]}),i.jsxs("div",{className:b.headerActions,children:[i.jsx(S,{tone:xe(l,h,o),children:we(r,l,h,o)}),i.jsxs(f,{variant:"primary",onClick:e.onRefresh,disabled:e.refreshing,children:[i.jsx(B,{})," ",e.refreshing?"Refreshing...":"Refresh data"]})]})]}),i.jsx(K,{active:o&&r,completed:C.ready,total:C.total,label:"Loading overview 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evidence":"Focused endpoints":"Stored snapshot"}function xe(e,t,o){return o?t&&!e||e!=null&&e.summary.error||e!=null&&e.recommendations.error?"caution":"positive":"neutral"}export{Ue as OverviewPage,ae as overviewCallsForQuery};
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oe({metrics:e,loadedCalls:t,availableCalls:a}){const n=e.basis==="scope",o=[{label:"Total Calls",value:m(e.calls),trend:n?"complete selected scope":"loaded evidence rows",detail:n?`${m(t)} detailed rows available`:`${m(a)} calls available in scope`,tone:"blue"},{label:"Total Tokens",value:p(e.totalTokens),trend:`${p(e.cachedInputTokens)} cached input`,detail:"reported token accounting",tone:"purple",breakdown:[{label:"Cached",value:p(e.cachedInputTokens)},{label:"Uncached",value:p(e.uncachedInputTokens)},{label:"Output",value:p(e.outputTokens)},{label:"Reasoning",value:p(e.reasoningOutputTokens)}]},{label:"Cache Reuse",value:R(e.cachePercent),trend:e.cachePercent>=80?"healthy cache reuse":"risk: low cache reuse",detail:`${p(e.cachedInputTokens)} cached input tokens`,tone:e.cachePercent>=80?"green":"orange"},{label:"Estimated Cost",value:F(e.estimatedCostUsd),trend:n?"complete selected scope":"loaded calls only",detail:"calls with mapped cost and credit 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r(){P(`codex-overview-calls-${G()}.csv`,D(s,N)),a(n.translateText(`Exported ${m(s.length)} loaded calls`))}return i.jsxs("section",{className:v.section,"aria-labelledby":"overview-recent-calls-title",children:[i.jsxs("div",{className:v.header,children:[i.jsxs("div",{children:[i.jsx("h2",{id:"overview-recent-calls-title",children:"Calls"}),i.jsx("p",{children:n.translateText(`${m(s.length)} matching calls with the same evidence fields as the Calls workspace.`)})]}),i.jsxs("div",{className:v.actions,children:[t?i.jsx(S,{tone:"positive",role:"status",children:t}):null,i.jsxs(f,{onClick:r,disabled:!s.length,children:[i.jsx($,{})," Export"]})]})]}),e.globalFilters,i.jsxs("div",{className:v.tableSurface,children:[i.jsx(z,{ariaLabel:"Overview calls",columns:l,data:s,identityColumnId:"thread",lockedColumnIds:["investigate"],getRowId:c=>c.id,mobile:{primary:c=>c.thread,secondary:c=>n.translateText(`${c.time} · ${c.model} · ${p(c.totalTokens)} tokens · ${R(c.cachedPct)} cache`),actionLabel:c=>A(c)},sorting:u,onSortingChange:h,columnVisibility:d.columnVisibility,onColumnVisibilityChange:d.setColumnVisibility,density:d.density,onDensityChange:d.setDensity,onRestoreDefaults:d.restoreDefaults,onRowActivate:c=>e.onOpenCall(c.id),activateOnClick:!0,viewportHeight:520,emptyLabel:"No loaded calls match the current search."}),i.jsxs("footer",{className:v.footer,children:[i.jsx("span",{children:n.translateText(`Loaded ${m(e.loadedRowCount)} of ${m(e.totalAvailableRows)} available calls`)}),i.jsxs("div",{className:v.actions,children:[i.jsx(f,{"aria-label":"Load more recent calls",onClick:e.onLoadMoreRows,disabled:!e.canLoadMoreRows||e.refreshing,children:e.refreshing?"Loading...":o}),i.jsx(f,{onClick:e.onBrowseCalls,children:"Browse all calls"})]})]})]})]})}function ue(e,t,a){const n=ve(e.scopeSummary)??me(e.calls),o=he(t==null?void 0:t.recommendations.data)??ge(e),s=o[0];return{answer:s?{title:`${s.title} is the clearest current signal`,detail:`${s.why} ${Ce(s.supportCount)}`,action:s.nextAction,tone:s.severity==="high"?"risk":"caution"}:{title:n.calls?"No rule-based usage issue stands out":"Load calls to establish a usage baseline",detail:n.calls?`The current ${O(a)} has no ranked recommendation with direct aggregate evidence.`:"The Overview needs aggregate calls before it can rank evidence or build token accounting.",action:n.calls?"Continue monitoring and investigate any workflow that feels unexpectedly expensive.":"Load recent calls or all history.",tone:"positive"},findings:o,metrics:n,pulseSpec:be(e,t==null?void 0:t.summary,a),tokenFlowSpec:ke(e.calls,n,a)}}function he(e){var a;if(!e)return null;const t=new Map;for(const n of e.rows){const o=(a=n.primaryRecommendation)==null?void 0:a.key;o&&t.set(o,[...t.get(o)??[],n])}return[...t.entries()].map(([n,o])=>pe(n,o,e.includeArchived)).sort((n,o)=>I(o.severity)-I(n.severity)||o.supportCount-n.supportCount).slice(0,6)}function pe(e,t,a){const n=[...t].sort((l,u)=>u.recommendationScore-l.recommendationScore)[0],o=n.primaryRecommendation,s=t.filter(l=>l.recordId&&l.eventTimestamp).length;return{id:e,title:o.title,why:o.why,nextAction:o.action||n.recommendedAction,severity:o.severity,evidenceGrade:s>=3?"Strong":s?"Moderate":"Limited",supportCount:t.length,scope:a?"All history":"Active history",freshness:y(t.map(l=>l.eventTimestamp)),recordId:n.recordId}}function ge(e){return e.findings.slice(0,6).map(t=>({id:`legacy-${t.rank}`,title:t.title,why:t.summary,nextAction:"Review the loaded aggregate evidence in Investigate.",severity:t.severity==="High"?"high":t.severity==="Medium"?"medium":"review",evidenceGrade:"Limited",supportCount:1,scope:"Loaded snapshot",freshness:y(e.calls.map(a=>a.eventTimestamp)),recordId:"",legacyRank:t.rank}))}function me(e){const t=e.reduce((n,o)=>({totalTokens:n.totalTokens+o.totalTokens,cachedInputTokens:n.cachedInputTokens+o.cachedInput,uncachedInputTokens:n.uncachedInputTokens+o.uncachedInput,outputTokens:n.outputTokens+o.output,reasoningOutputTokens:n.reasoningOutputTokens+o.reasoningOutput,estimatedCostUsd:n.estimatedCostUsd+o.cost,estimatedCredits:n.estimatedCredits+o.credits}),{totalTokens:0,cachedInputTokens:0,uncachedInputTokens:0,outputTokens:0,reasoningOutputTokens:0,estimatedCostUsd:0,estimatedCredits:0}),a=t.cachedInputTokens+t.uncachedInputTokens;return{basis:"loaded",calls:e.length,...t,cachePercent:a>0?t.cachedInputTokens/a*100:0}}function ve(e){return e?{basis:"scope",calls:e.visibleCalls,totalTokens:e.totalTokens,cachedInputTokens:e.cachedInputTokens,uncachedInputTokens:e.uncachedInputTokens,outputTokens:e.outputTokens,reasoningOutputTokens:e.reasoningOutputTokens,cachePercent:e.inputTokens>0?e.cachedInputTokens/e.inputTokens*100:0,estimatedCostUsd:e.estimatedCostUsd,estimatedCredits:e.usageCredits}:null}function be(e,t,a){var h,d;const n=(h=t==null?void 0:t.data)==null?void 0:h.rows.map(r=>({id:r.groupKey,day:r.groupKey,inputTokens:r.inputTokens,cachedTokens:r.cachedInputTokens,outputTokens:r.outputTokens,calls:r.modelCalls})).sort((r,c)=>r.day.localeCompare(c.day)),o=n!=null&&n.length?n:fe(e),s=o.length?t!=null&&t.error?{kind:"partial",message:"Focused summary unavailable; showing loaded call rows.",availableRows:o.length}:{kind:"ready"}:{kind:"empty",message:"No dated aggregate usage is available in this scope."},l=y(((d=t==null?void 0:t.data)==null?void 0:d.rows.map(r=>r.latestEvent))??e.calls.map(r=>r.eventTimestamp)),u=o.length<=3?"bar":"line";return{schema:L,id:"overview-usage-pulse",title:"Recent token movement",description:"Daily input, cached reuse, and output volume in the selected history scope.",state:s,scope:{label:O(a),rowCount:o.length,historyScope:a},freshness:{generatedAt:l||new Date().toISOString()},caveats:[(t==null?void 0:t.error)??"Daily aggregates describe local records; they do not represent OpenAI billing."],accessibility:{summary:ye(o)},table:{caption:"Daily token movement",columns:[{field:"day",label:"Day",type:"time"},{field:"inputTokens",label:"Input",type:"number",unit:"tokens",align:"right"},{field:"cachedTokens",label:"Cached",type:"number",unit:"tokens",align:"right"},{field:"outputTokens",label:"Output",type:"number",unit:"tokens",align:"right"},{field:"calls",label:"Calls",type:"number",unit:"count",align:"right"}]},interactions:{selection:{keyField:"id",labelField:"day"},zoom:{axis:"x",startPercent:o.length>30?(o.length-30)/o.length*100:0,endPercent:100}},kind:"cartesian",data:{rows:o},axes:{x:{field:"day",label:"Day",type:"category"},y:{field:"inputTokens",label:"Tokens",type:"number",unit:"tokens",min:0}},series:[{id:"input",label:"Input",mark:u,xField:"day",yField:"inputTokens",color:"#2f6fed"},{id:"cached",label:"Cached",mark:u,xField:"day",yField:"cachedTokens",color:"#16866b"},{id:"output",label:"Output",mark:u,xField:"day",yField:"outputTokens",color:"#7651c9"}]}}function ke(e,t,a){const n=t.basis==="scope",o=n?"Scope accounting":"Loaded accounting",s=n?"calls in selected scope":"loaded calls",l=t.outputTokens+t.reasoningOutputTokens,h=[{id:"account-input",source:"account",target:"input",value:t.cachedInputTokens+t.uncachedInputTokens,evidenceKey:"reported:input"},{id:"account-generated",source:"account",target:"generated",value:l,evidenceKey:"reported:generated"},{id:"input-cached",source:"input",target:"cached",value:t.cachedInputTokens,evidenceKey:"reported:cached-input"},{id:"input-uncached",source:"input",target:"uncached",value:t.uncachedInputTokens,evidenceKey:"derived:uncached-input"},{id:"generated-visible",source:"generated",target:"output",value:t.outputTokens,evidenceKey:"reported:output"},{id:"generated-reasoning",source:"generated",target:"reasoning",value:t.reasoningOutputTokens,evidenceKey:"reported:reasoning-output"}].filter(d=>d.value>0);return{schema:L,id:"overview-token-accounting",title:n?"Token accounting in scope":"Loaded token accounting",description:n?"The four reported token categories across the complete selected data scope.":"The four reported token categories across calls currently loaded in the dashboard.",state:h.length?{kind:"ready"}:{kind:"empty",message:"No token accounting is available in this scope."},scope:{label:`${t.calls.toLocaleString()} ${s}`,rowCount:t.calls,historyScope:a},freshness:{generatedAt:y(e.map(d=>d.eventTimestamp))||new Date().toISOString()},caveats:["Categories mirror reported fields and may overlap; flow widths are accounting, not causality or billed cost."],accessibility:{summary:Te(t)},table:{caption:`${o} categories`,columns:[{field:"source",label:"From",type:"text"},{field:"target",label:"To",type:"text"},{field:"value",label:"Tokens",type:"number",unit:"tokens",align:"right"},{field:"evidenceKey",label:"Basis",type:"text"}],defaultSort:{field:"value",direction:"desc"}},interactions:{selection:{keyField:"id"}},kind:"flow",encoding:{sourceLabel:"Category",targetLabel:"Reported type",valueLabel:"Tokens",valueUnit:"tokens"},data:{nodes:[{id:"account",label:o,color:"#2f6fed"},{id:"input",label:"Input accounting",color:"#2f6fed"},{id:"generated",label:"Generated accounting",color:"#7651c9"},{id:"cached",label:"Cached input",color:"#16866b"},{id:"uncached",label:"Uncached input",color:"#9a5900"},{id:"output",label:"Output",color:"#16866b"},{id:"reasoning",label:"Reasoning output",color:"#7651c9"}],links:h}}}function fe(e){const t=new Map;for(const a of e.calls){const n=Date.parse(a.eventTimestamp);if(!Number.isFinite(n))continue;const o=new Date(n).toISOString().slice(0,10),s=t.get(o)??{inputTokens:0,cachedTokens:0,outputTokens:0,calls:0};s.inputTokens+=a.input,s.cachedTokens+=a.cachedInput,s.outputTokens+=a.output,s.calls+=1,t.set(o,s)}return[...t.entries()].sort(([a],[n])=>a.localeCompare(n)).map(([a,n])=>({id:a,day:a,...n}))}function ye(e){return e.length?`${e.length} daily buckets are available, with the visible window favoring the most recent ${Math.min(e.length,30)}.`:"No daily token movement is available."}function Te(e){if(!e.calls)return"No calls are available for token accounting.";const t=e.basis==="scope"?"calls in the selected scope":"loaded calls";return`${e.calls} ${t} include ${Math.round(e.cachePercent)} percent cached input reuse.`}function Ce(e){return e===1?"One ranked call supports this pattern.":`${e} ranked calls support this pattern.`}function O(e){return e==="all"?"all-history scope":"active-history scope"}function y(e){return e.filter(Boolean).sort((t,a)=>Date.parse(a)-Date.parse(t))[0]??""}function I(e){return e==="high"?3:e==="medium"?2:1}function Ue(e){const a=(e.focusedEndpointsEnabled??!0)&&!e.contextRuntime.fileMode&&!!e.contextRuntime.apiToken,n={runtime:e.contextRuntime,includeArchived:e.runtime.historyScope==="all",since:e.runtime.scopeSince??void 0,sourceRevision:e.sourceRevision,sourceKey:e.sourceKey},o=w({...V(n),enabled:a,placeholderData:g=>g}),s=w({...H(n),enabled:a,placeholderData:g=>g}),l=k.useMemo(()=>a?{summary:{data:o.data??null,error:o.error?T(o.error):null},recommendations:{data:s.data??null,error:s.error?T(s.error):null}}:void 0,[a,s.data,s.error,o.data,o.error]),u=k.useMemo(()=>ue(e.model,l,e.runtime.historyScope),[l,e.model,e.runtime.historyScope]),h=o.error??s.error,d=h?T(h):(l==null?void 0:l.summary.error)||(l==null?void 0:l.recommendations.error)||null,r=o.isFetching||s.isFetching,c=[{label:"Usage summary",status:x({enabled:a,hasData:!!o.data,isError:o.isError,isFetching:o.isFetching,isPending:o.isPending})},{label:"Recommendations",status:x({enabled:a,hasData:!!s.data,isError:s.isError,isFetching:s.isFetching,isPending:s.isPending})}],C=U(c.map(g=>g.status));return i.jsxs("div",{className:b.page,children:[i.jsxs("header",{className:b.pageHeader,children:[i.jsxs("div",{children:[i.jsx("p",{className:b.eyebrow,children:"Usage pulse"}),i.jsx("h1",{children:"Overview"}),i.jsx("p",{children:"The important changes first, with direct paths into supporting evidence."})]}),i.jsxs("div",{className:b.headerActions,children:[i.jsx(S,{tone:xe(l,h,a),children:we(r,l,h,a)}),i.jsxs(f,{variant:"primary",onClick:e.onRefresh,disabled:e.refreshing,children:[i.jsx(B,{})," ",e.refreshing?"Refreshing...":"Refresh data"]})]})]}),i.jsx(K,{active:a&&r,completed:C.ready,total:C.total,label:"Loading overview evidence",error:a?d:null,modules:c,updating:c.some(g=>g.status==="updating")}),i.jsx(oe,{metrics:u.metrics,loadedCalls:e.runtime.loadedRowCount,availableCalls:e.runtime.totalAvailableRows}),i.jsxs("div",{className:b.analysisGrid,children:[i.jsx(j,{spec:u.pulseSpec,height:280}),i.jsx(j,{spec:u.tokenFlowSpec,height:280})]}),i.jsx(de,{calls:e.model.calls,globalFilters:e.globalFilters,globalQuery:e.globalQuery,loadedRowCount:e.runtime.loadedRowCount,totalAvailableRows:e.runtime.totalAvailableRows,refreshing:e.refreshing,canLoadMoreRows:e.canLoadMoreRows,onLoadMoreRows:e.onLoadMoreRows,onBrowseCalls:()=>e.onNavigateView("calls"),onOpenCall:e.onOpenInvestigator,onCopyCallLink:e.onCopyCallLink})]})}function T(e){return e instanceof Error?e.message:String(e)}function we(e,t,a,n){return n?e&&(t!=null&&t.summary.data||t!=null&&t.recommendations.data)?"Updating evidence":e?"Loading evidence":a?"Endpoint fallback":t!=null&&t.summary.error||t!=null&&t.recommendations.error?"Partial endpoint evidence":"Focused endpoints":"Stored snapshot"}function xe(e,t,a){return a?t&&!e||e!=null&&e.summary.error||e!=null&&e.recommendations.error?"caution":"positive":"neutral"}export{Ue as OverviewPage,ae as overviewCallsForQuery};
diff --git a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/PageLoadProgress.js b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/PageLoadProgress.js
index 35eceaed..7978a47b 100644
--- a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/PageLoadProgress.js
+++ b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/PageLoadProgress.js
@@ -1 +1 @@
-import{j as a}from"./dashboard-react.js";const _="_root_zuab8_2",u="_error_zuab8_3",p="_copy_zuab8_18",b="_track_zuab8_30",f="_segmentedTrack_zuab8_38",x="_segment_zuab8_38",h="_segmentReady_zuab8_56",v="_segmentUpdating_zuab8_60",z="_segmentLoading_zuab8_64",y="_segmentError_zuab8_75",j="_segmentWaiting_zuab8_79",N="_modules_zuab8_83",k="_module_zuab8_83",E="_inlineError_zuab8_97",$="_fill_zuab8_102",L="_indeterminate_zuab8_103",e={root:_,error:u,copy:p,track:b,segmentedTrack:f,segment:x,segmentReady:h,segmentUpdating:v,segmentLoading:z,segmentError:y,segmentWaiting:j,modules:N,module:k,inlineError:E,fill:$,indeterminate:L};function T({active:n,completed:l=0,total:i,label:c,error:o,modules:r,updating:d=!1}){if(!n&&!o)return null;if(!n&&o)return a.jsxs("div",{className:e.error,role:"alert",children:["Incomplete page evidence: ",o]});const t=typeof i=="number"&&i>0,g=t?Math.min(Math.max(l,0),i):0,m=t?g/i*100:0;return a.jsxs("section",{className:e.root,"aria-live":"polite",children:[a.jsxs("div",{className:e.copy,children:[a.jsx("strong",{children:d?"Updating page evidence":c}),t?a.jsxs("span",{children:[g," of ",i," modules ready"]}):a.jsx("span",{children:"Working on full-scope evidence"})]}),a.jsx("div",{className:`${e.track} ${r!=null&&r.length?e.segmentedTrack:""}`,role:"progressbar","aria-label":c,"aria-valuemin":t?0:void 0,"aria-valuemax":t?i:void 0,"aria-valuenow":t?g:void 0,children:r!=null&&r.length?r.map(s=>a.jsx("span",{className:`${e.segment} ${R(s.status)}`},s.label)):a.jsx("span",{className:t?e.fill:e.indeterminate,style:t?{width:`${m}%`}:void 0})}),r!=null&&r.length?a.jsx("div",{className:e.modules,"aria-label":`${c} modules`,children:r.map(s=>a.jsxs("span",{className:e.module,children:[s.label," ",U(s.status)]},s.label))}):null,o?a.jsx("div",{className:e.inlineError,role:"alert",children:o}):null]})}function R(n){return n==="ready"?e.segmentReady:n==="updating"?e.segmentUpdating:n==="loading"?e.segmentLoading:n==="error"?e.segmentError:e.segmentWaiting}function U(n){return n==="ready"?"ready":n==="updating"?"updating":n==="loading"?"loading":n==="error"?"unavailable":"waiting"}export{T as P};
+import{j as a}from"./dashboard-react.js";import{u}from"./App.js";const p="_root_zuab8_2",x="_error_zuab8_3",f="_copy_zuab8_18",b="_track_zuab8_30",h="_segmentedTrack_zuab8_38",v="_segment_zuab8_38",z="_segmentReady_zuab8_56",y="_segmentUpdating_zuab8_60",j="_segmentLoading_zuab8_64",T="_segmentError_zuab8_75",N="_segmentWaiting_zuab8_79",$="_modules_zuab8_83",k="_module_zuab8_83",E="_inlineError_zuab8_97",L="_fill_zuab8_102",R="_indeterminate_zuab8_103",e={root:p,error:x,copy:f,track:b,segmentedTrack:h,segment:v,segmentReady:z,segmentUpdating:y,segmentLoading:j,segmentError:T,segmentWaiting:N,modules:$,module:k,inlineError:E,fill:L,indeterminate:R};function C({active:n,completed:d=0,total:i,label:c,error:o,modules:t,updating:m=!1}){const r=u();if(!n&&!o)return null;if(!n&&o)return a.jsx("div",{className:e.error,role:"alert",children:r.translateText(`Incomplete page evidence: ${o}`)});const s=typeof i=="number"&&i>0,g=s?Math.min(Math.max(d,0),i):0,_=s?g/i*100:0;return a.jsxs("section",{className:e.root,"aria-live":"polite",children:[a.jsxs("div",{className:e.copy,children:[a.jsx("strong",{children:r.translateText(m?"Updating page evidence":c)}),s?a.jsx("span",{children:r.translateText(`${g} of ${i} modules ready`)}):a.jsx("span",{children:r.translateText("Working on full-scope evidence")})]}),a.jsx("div",{className:`${e.track} ${t!=null&&t.length?e.segmentedTrack:""}`,role:"progressbar","aria-label":r.translateText(c),"aria-valuemin":s?0:void 0,"aria-valuemax":s?i:void 0,"aria-valuenow":s?g:void 0,children:t!=null&&t.length?t.map(l=>a.jsx("span",{className:`${e.segment} ${U(l.status)}`},l.label)):a.jsx("span",{className:s?e.fill:e.indeterminate,style:s?{width:`${_}%`}:void 0})}),t!=null&&t.length?a.jsx("div",{className:e.modules,"aria-label":r.translateText(`${r.translateText(c)} modules`),children:t.map(l=>a.jsxs("span",{className:e.module,children:[r.translateText(l.label)," ",r.translateText(W(l.status))]},l.label))}):null,o?a.jsx("div",{className:e.inlineError,role:"alert",children:r.translateText(o)}):null]})}function U(n){return n==="ready"?e.segmentReady:n==="updating"?e.segmentUpdating:n==="loading"?e.segmentLoading:n==="error"?e.segmentError:e.segmentWaiting}function W(n){return n==="ready"?"ready":n==="updating"?"updating":n==="loading"?"loading":n==="error"?"unavailable":"waiting"}export{C as P};
diff --git a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/Panel.js b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/Panel.js
index 0bc3dc23..f32f0aef 100644
--- a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/Panel.js
+++ b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/Panel.js
@@ -1 +1 @@
-import{j as s}from"./dashboard-react.js";function c({label:n,tone:e="neutral"}){return s.jsx("span",{className:`status-badge ${e}`,children:n})}function d({title:n,subtitle:e,action:a,children:l,className:r=""}){return s.jsxs("section",{className:`panel ${r}`.trim(),children:[s.jsxs("div",{className:"panel-header",children:[s.jsxs("div",{children:[s.jsx("h2",{children:n}),e?s.jsx("p",{children:e}):null]}),a?s.jsx("div",{className:"panel-action",children:a}):null]}),l]})}export{d as P,c as S};
+import{j as s}from"./dashboard-react.js";import{u as l}from"./App.js";function x({label:a,tone:e="neutral"}){const n=l();return s.jsx("span",{className:`status-badge ${e}`,children:n.translateText(a)})}function o({title:a,subtitle:e,action:n,children:r,className:i=""}){const t=l();return s.jsxs("section",{className:`panel ${i}`.trim(),children:[s.jsxs("div",{className:"panel-header",children:[s.jsxs("div",{children:[s.jsx("h2",{children:t.translateText(a)}),e?s.jsx("p",{children:t.translateText(e)}):null]}),n?s.jsx("div",{className:"panel-action",children:n}):null]}),r]})}export{o as P,x as S};
diff --git a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/Primitives.js b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/Primitives.js
index 1bd037cf..a2d05d28 100644
--- a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/Primitives.js
+++ b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/Primitives.js
@@ -1 +1 @@
-import{r as u,j as e}from"./dashboard-react.js";const p="_button_s0gw9_2",w="_iconButton_s0gw9_3",b="_segment_s0gw9_4",x="_primary_s0gw9_21",v="_secondary_s0gw9_30",h="_ghost_s0gw9_31",j="_danger_s0gw9_55",B="_badge_s0gw9_87",N="_neutral_s0gw9_97",y="_positive_s0gw9_102",S="_caution_s0gw9_107",R="_risk_s0gw9_112",k="_context_s0gw9_117",M="_surface_s0gw9_122",I="_surfaceSubtle_s0gw9_130",V="_metric_s0gw9_134",A="_metricLabel_s0gw9_139",D="_metricDetail_s0gw9_140",F="_metricValue_s0gw9_145",H="_segments_s0gw9_151",L="_segmentActive_s0gw9_166",T="_progress_s0gw9_171",P="_progressHeader_s0gw9_176",C="_progressTrack_s0gw9_183",E="_progressFill_s0gw9_190",s={button:p,iconButton:w,segment:b,primary:x,secondary:v,ghost:h,danger:j,badge:B,neutral:N,positive:y,caution:S,risk:R,context:k,surface:M,surfaceSubtle:I,metric:V,metricLabel:A,metricDetail:D,metricValue:F,segments:H,segmentActive:L,progress:T,progressHeader:P,progressTrack:C,progressFill:E};function i(...o){return o.filter(Boolean).join(" ")}const q=u.forwardRef(function({className:n,type:t="button",variant:r="secondary",...a},l){return e.jsx("button",{ref:l,type:t,className:i(s.button,s[r],n),...a})}),z=u.forwardRef(function({className:n,type:t="button",...r},a){return e.jsx("button",{ref:a,type:t,className:i(s.iconButton,n),...r})}),G=u.forwardRef(function({className:n,tone:t="neutral",...r},a){return e.jsx("span",{ref:a,className:i(s.badge,s[t],n),...r})}),J=u.forwardRef(function({className:n,tone:t="panel",...r},a){return e.jsx("div",{ref:a,className:i(s.surface,t==="subtle"&&s.surfaceSubtle,n),...r})}),K=u.forwardRef(function({className:n,detail:t,label:r,value:a,...l},c){return e.jsxs("div",{ref:c,className:i(s.metric,n),...l,children:[e.jsx("span",{className:s.metricLabel,children:r}),e.jsx("strong",{className:s.metricValue,children:a}),t?e.jsx("span",{className:s.metricDetail,children:t}):null]})});function O({className:o,label:n,onValueChange:t,options:r,value:a,...l}){return e.jsx("div",{role:"group","aria-label":n,className:i(s.segments,o),...l,children:r.map(c=>e.jsx("button",{type:"button","aria-pressed":c.value===a,className:i(s.segment,c.value===a&&s.segmentActive),disabled:c.disabled,onClick:()=>t(c.value),children:c.label},c.value))})}const Q=u.forwardRef(function({className:n,label:t,max:r=100,showValue:a=!0,value:l,...c},f){const g=u.useId(),_=r>0?r:100,d=Math.min(Math.max(l,0),_),m=Math.round(d/_*100);return e.jsxs("div",{ref:f,className:i(s.progress,n),...c,children:[e.jsxs("div",{className:s.progressHeader,children:[e.jsx("span",{id:g,children:t}),a?e.jsxs("span",{"aria-hidden":"true",children:[m,"%"]}):null]}),e.jsx("div",{role:"progressbar","aria-labelledby":g,"aria-valuemin":0,"aria-valuemax":_,"aria-valuenow":d,className:s.progressTrack,children:e.jsx("div",{className:s.progressFill,style:{width:`${m}%`}})})]})});export{q as B,z as I,K as M,Q as P,O as S,G as a,J as b};
+import{r as _,j as r}from"./dashboard-react.js";import{u as d}from"./App.js";const w="_button_s0gw9_2",h="_iconButton_s0gw9_3",v="_segment_s0gw9_4",j="_primary_s0gw9_21",N="_secondary_s0gw9_30",B="_ghost_s0gw9_31",y="_danger_s0gw9_55",T="_badge_s0gw9_87",S="_neutral_s0gw9_97",R="_positive_s0gw9_102",k="_caution_s0gw9_107",M="_risk_s0gw9_112",I="_context_s0gw9_117",V="_surface_s0gw9_122",A="_surfaceSubtle_s0gw9_130",D="_metric_s0gw9_134",F="_metricLabel_s0gw9_139",H="_metricDetail_s0gw9_140",L="_metricValue_s0gw9_145",P="_segments_s0gw9_151",C="_segmentActive_s0gw9_166",E="_progress_s0gw9_171",z="_progressHeader_s0gw9_176",$="_progressTrack_s0gw9_183",q="_progressFill_s0gw9_190",s={button:w,iconButton:h,segment:v,primary:j,secondary:N,ghost:B,danger:y,badge:T,neutral:S,positive:R,caution:k,risk:M,context:I,surface:V,surfaceSubtle:A,metric:D,metricLabel:F,metricDetail:H,metricValue:L,segments:P,segmentActive:C,progress:E,progressHeader:z,progressTrack:$,progressFill:q};function u(...o){return o.filter(Boolean).join(" ")}const K=_.forwardRef(function({children:a,className:n,type:e="button",variant:c="secondary",...i},l){const t=d();return r.jsx("button",{ref:l,type:e,className:u(s.button,s[c],n),...i,children:g(a,t.translateText)})}),O=_.forwardRef(function({"aria-label":a,className:n,title:e,type:c="button",...i},l){const t=d();return r.jsx("button",{ref:l,type:c,"aria-label":t.translateText(a),title:typeof e=="string"?t.translateText(e):e,className:u(s.iconButton,n),...i})}),Q=_.forwardRef(function({children:a,className:n,tone:e="neutral",...c},i){const l=d();return r.jsx("span",{ref:i,className:u(s.badge,s[e],n),...c,children:g(a,l.translateText)})}),U=_.forwardRef(function({className:a,tone:n="panel",...e},c){return r.jsx("div",{ref:c,className:u(s.surface,n==="subtle"&&s.surfaceSubtle,a),...e})}),W=_.forwardRef(function({className:a,detail:n,label:e,value:c,...i},l){const t=d();return r.jsxs("div",{ref:l,className:u(s.metric,a),...i,children:[r.jsx("span",{className:s.metricLabel,children:g(e,t.translateText)}),r.jsx("strong",{className:s.metricValue,children:c}),n?r.jsx("span",{className:s.metricDetail,children:g(n,t.translateText)}):null]})});function X({className:o,label:a,onValueChange:n,options:e,value:c,...i}){const l=d();return r.jsx("div",{role:"group","aria-label":l.translateText(a),className:u(s.segments,o),...i,children:e.map(t=>r.jsx("button",{type:"button","aria-pressed":t.value===c,className:u(s.segment,t.value===c&&s.segmentActive),disabled:t.disabled,onClick:()=>n(t.value),children:g(t.label,l.translateText)},t.value))})}const Y=_.forwardRef(function({className:a,label:n,max:e=100,showValue:c=!0,value:i,...l},t){const x=d(),f=_.useId(),m=e>0?e:100,p=Math.min(Math.max(i,0),m),b=Math.round(p/m*100);return r.jsxs("div",{ref:t,className:u(s.progress,a),...l,children:[r.jsxs("div",{className:s.progressHeader,children:[r.jsx("span",{id:f,children:g(n,x.translateText)}),c?r.jsxs("span",{"aria-hidden":"true",children:[b,"%"]}):null]}),r.jsx("div",{role:"progressbar","aria-labelledby":f,"aria-valuemin":0,"aria-valuemax":m,"aria-valuenow":p,className:s.progressTrack,children:r.jsx("div",{className:s.progressFill,style:{width:`${b}%`}})})]})});function g(o,a){return typeof o=="string"?a(o):o}export{K as B,O as I,W as M,Y as P,X as S,Q as a,U as b};
diff --git a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/ReportsPage.js b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/ReportsPage.js
index 64069f6c..b63d05d2 100644
--- a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/ReportsPage.js
+++ b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/ReportsPage.js
@@ -1 +1 @@
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Duration is a proxy, not a quality score.`,method:"Filter fast-tagged and low-effort calls, then order by shortest duration and credit impact.",caveat:"Aggregate timing cannot distinguish model latency from tool, network, or queue time.",selection:"Fast/low-effort candidates · shortest duration first · top 8",chartLabel:"Calls"}:s.includes("cost")||s.includes("thread")?{eyebrow:"Cost concentration",finding:`${r.length} highest-cost loaded calls anchor this report. 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Cost",cell:t=>a.jsx("span",{className:"num",children:Y(Number(t.getValue()))})},{accessorKey:"cachedPct",header:"Cached %",cell:t=>a.jsx("span",{className:"cache-pill",children:Z(Number(t.getValue()))})},ee({onOpenInvestigator:r,onCopyCallLink:s,labelPrefix:"report side evidence call"})],[s,r]);return a.jsx(he,{columns:o,data:e,compact:!0,emptyLabel:"No loaded aggregate calls match this selected report.",getRowId:t=>t.id,getRowActionLabel:t=>te(t,"report side evidence call"),onRowActivate:t=>r(t.id),ariaLabel:"Selected report evidence calls"})}function je(e,r,s,o){var w;const t=D(e,s),i=Se(t.chartLabel),d=xe(e,r,s),u=d?ke(d,i,t.chartLabel):Re(ve(e,r),i,t.chartLabel),b=(e==null?void 0:e.title)??"Selected report",v=`${t.eyebrow} evidence`;return{schema:de,id:`report-${f(e)}`,title:v,description:t.selection,state:u.rows.length?{kind:"ready"}:{kind:"empty",message:`No loaded aggregate data is available for ${b}.`},scope:{label:`${o.source} · ${t.selection}`,rowCount:u.rows.length,historyScope:o.historyScope},freshness:{generatedAt:o.generatedAt,sourceRevision:o.sourceRevision},caveats:[t.caveat,"Raw context is available only through an explicitly linked Call Investigator record."],accessibility:{summary:u.rows.length?`${b} contains ${u.rows.length} plotted rows. ${t.finding}`:`No plotted rows are available for ${b}.`,details:[t.method,t.caveat],keyboardInstructions:"Use left and right arrow keys to inspect chart values, or switch to the table for exact values."},table:{caption:`${b} report data`,columns:u.columns,defaultSort:{field:"label",direction:"asc"}},interactions:{selection:{keyField:"id",labelField:"label"},...d?{}:{zoom:{axis:"x",startPercent:u.rows.length>12?Math.round(100-12/u.rows.length*100):0,endPercent:100},brush:{axis:"x"}}},kind:"cartesian",data:{rows:u.rows},axes:{x:{field:"label",label:d?"Category":"Observed period",type:"category"},y:{field:((w=u.series[0])==null?void 0:w.yField)??"value",label:t.chartLabel,type:"number",unit:i}},series:u.series}}function ke(e,r,s){return{rows:e.map((t,i)=>({id:`bar-${i}`,label:t.label,value:t.value})),columns:[{field:"label",label:"Category",type:"category",align:"left"},{field:"value",label:s,type:"number",unit:r,align:"right"}],series:[{id:"report-values",label:s,mark:"bar",xField:"label",yField:"value",color:"#2f6fed"}]}}function Re(e,r,s){const o=new Map,t=[],i=[{field:"label",label:"Observed period",type:"category",align:"left"}];return e.forEach((d,u)=>{const b=`value_${u}`,v=`low_${u}`,w=`high_${u}`,S=d.points.some(m=>Number.isFinite(m.low)&&Number.isFinite(m.high));i.push({field:b,label:d.label||s,type:"number",unit:r,align:"right"}),S&&i.push({field:v,label:`${d.label} low`,type:"number",unit:r,align:"right"},{field:w,label:`${d.label} high`,type:"number",unit:r,align:"right"}),d.points.forEach((m,j)=>{const h=m.label||`Point ${j+1}`,k=o.get(h)??{id:`point-${o.size}`,label:h};k[b]=m.value,S&&Number.isFinite(m.low)&&Number.isFinite(m.high)&&(k[v]=Number(m.low),k[w]=Number(m.high)),o.set(h,k)}),t.push({id:d.id||`series-${u}`,label:d.label||s,mark:"line",xField:"label",yField:b,color:d.color,smooth:!1,...S?{lowerField:v,upperField:w}:{}})}),{rows:[...o.values()],columns:i,series:t}}function Se(e){return e==="USD"?"usd":e==="Calls"?"count":e==="Percent"?"percent":"credits"}const _e="_page_p90q5_1",Le="_header_p90q5_7",Ce="_actions_p90q5_8",Ne="_status_p90q5_9",$e="_selectedMeta_p90q5_10",Fe="_switcher_p90q5_11",Pe="_selected_p90q5_10",Ee="_research_p90q5_24",Ue="_action_p90q5_8",Me="_eyebrow_p90q5_109",Te="_workspace_p90q5_166",Ae="_main_p90q5_173",ze="_metadata_p90q5_195",p={page:_e,header:Le,actions:Ce,status:Ne,selectedMeta:$e,switcher:Fe,selected:Pe,research:Ee,action:Ue,eyebrow:Me,workspace:Te,main:Ae,metadata:ze};function tt(e){return z(A(e.reports)??e.reports[0],e.calls)}function rt({model:e,refreshState:r,includeArchived:s,loadWindow:o,loadLimit:t,sourceKey:i,sourceRevision:d,onOpenInvestigator:u,onCopyCallLink:b}){const v=re(),[w,S]=_.useState(()=>f(A(e.reports)??e.reports[0])),[m,j]=_.useState(""),h=!!e.contextRuntime.apiToken&&!e.contextRuntime.fileMode,k=o==="rows"?t:0,g=Q({...be({runtime:e.contextRuntime,includeArchived:s,loadWindow:o,limit:k,evidenceLimit:8,sourceKey:i,sourceRevision:d}),enabled:h,placeholderData:c=>c}),l=h?g.data:void 0,N=l!=null&&l.reports.length?l.reports:e.reports,n=N.find(c=>f(c)===w)??N[0],x=_.useMemo(()=>{const c=n&&l?l.evidence[f(n)]:void 0;return c===void 0?z(n,e.calls):c},[n,e.calls,l]),R=D(n,x),C=l?"Live localhost report pack":"Loaded dashboard aggregates",$=(l==null?void 0:l.generatedAt)||(l?"Server timestamp unavailable":"Current dashboard snapshot"),K=De(h,g,m,r),O=_.useMemo(()=>je(n,e,x,{generatedAt:$,historyScope:s?"all":"active",source:C,sourceRevision:d}),[n,x,$,s,e,C,d]),F={label:"Report pack",status:ae({enabled:h,hasData:!!g.data,isError:g.isError,isFetching:g.isFetching,isPending:g.isPending})},M=se([F.status]);async function V(){if(!h)return;j("Refreshing selected report…");const c=await g.refetch();j(c.isError?`Refresh failed: ${U(c.error)}. Showing cached live report pack.`:"Selected report refreshed")}function I(){Ke(`codex-report-${f(n)}-${ne()}.json`,{schema:"codex-usage-tracker-react-selected-report-v1",generated_at:(l==null?void 0:l.generatedAt)??null,source:C,report:n,method:R.method,caveat:R.caveat,evidence:x,raw_context_included:(l==null?void 0:l.rawContextIncluded)??!1}),j(`Exported ${(n==null?void 0:n.title)??"selected report"}`)}function B(c){S(f(c)),j(`${c.title} selected`),we(c)}return a.jsxs("div",{className:p.page,children:[a.jsxs("header",{className:p.header,children:[a.jsxs("div",{children:[a.jsx("h1",{children:"Reports"}),a.jsx("p",{children:"Focused local research snapshots with their methods, limits, and investigator-linked evidence."})]}),a.jsxs("div",{className:p.actions,children:[a.jsxs("button",{className:p.action,type:"button",onClick:I,disabled:!n,children:[a.jsx(ie,{size:16,"aria-hidden":"true"}),"Export selected"]}),a.jsxs("button",{className:p.action,"data-primary":"true",type:"button",onClick:V,disabled:!h||g.isFetching,title:h?void 0:"Live report refresh requires the localhost server.",children:[a.jsx(oe,{size:16,"aria-hidden":"true"}),h?g.isFetching?"Refreshing":"Refresh report":"Live refresh unavailable"]})]})]}),a.jsx(ce,{active:h&&g.isFetching,completed:M.ready,total:M.total,label:"Loading full-scope report pack",error:h&&g.error&&!g.data?`Report pack unavailable: ${U(g.error)}`:null,modules:[F],updating:F.status==="updating"}),a.jsxs("div",{className:p.status,role:"status","aria-live":"polite",children:[a.jsx(P,{label:l?"Live report pack":"Aggregate fallback",tone:l?"green":"orange"}),a.jsx("span",{children:K})]}),a.jsxs("section",{className:p.selected,"aria-labelledby":"selected-report-title",children:[a.jsxs("div",{children:[a.jsx("span",{className:p.eyebrow,children:R.eyebrow}),a.jsx("h2",{id:"selected-report-title",children:(n==null?void 0:n.title)??"No report available"}),a.jsx("p",{children:n==null?void 0:n.description}),a.jsx("p",{children:R.finding})]}),a.jsxs("div",{className:p.selectedMeta,children:[a.jsx(P,{label:(n==null?void 0:n.status)??"Blocked",tone:(n==null?void 0:n.status)==="Ready"?"green":"orange"}),a.jsxs("span",{children:[(n==null?void 0:n.owner)??"No owner"," · ",x.length," evidence rows"]})]})]}),a.jsx("div",{className:p.switcher,role:"group","aria-label":"Select report",children:N.map(c=>a.jsx("button",{type:"button","aria-pressed":f(c)===f(n),onClick:()=>B(c),children:c.title},f(c)))}),a.jsxs("div",{className:p.workspace,children:[a.jsxs("section",{className:p.main,"aria-label":"Report evidence",children:[a.jsx(ue,{spec:O,height:320}),a.jsx(E,{title:"Report Evidence Calls",subtitle:v.translateText(`${x.length} aggregate rows · select a row to open Call Investigator`),action:a.jsx(P,{label:"Investigator linked",tone:"green"}),children:a.jsx(ye,{calls:x,onOpenInvestigator:u,onCopyCallLink:b})})]}),a.jsxs("aside",{className:p.research,children:[a.jsxs(E,{title:"Research Notes",subtitle:"Interpretation boundary",children:[a.jsxs("section",{children:[a.jsx("h3",{children:"Method"}),a.jsx("p",{children:R.method})]}),a.jsxs("section",{children:[a.jsx("h3",{children:"Caveat"}),a.jsx("p",{children:R.caveat})]}),a.jsxs("section",{children:[a.jsx("h3",{children:"Evidence privacy"}),a.jsx("p",{children:"Raw context is not included here; inspect an explicitly linked call in Call Investigator."})]})]}),a.jsx(E,{title:"Generation Metadata",subtitle:"Provenance for this view",children:a.jsxs("dl",{className:p.metadata,children:[a.jsxs("div",{children:[a.jsx("dt",{children:"Source"}),a.jsx("dd",{children:C})]}),a.jsxs("div",{children:[a.jsx("dt",{children:"Generated"}),a.jsx("dd",{children:$})]}),a.jsxs("div",{children:[a.jsx("dt",{children:"Schema"}),a.jsx("dd",{children:(l==null?void 0:l.schema)||"dashboard aggregate model"})]}),a.jsxs("div",{children:[a.jsx("dt",{children:"Matched"}),a.jsxs("dd",{children:[l?l.totalMatchedRows.toLocaleString():e.calls.length.toLocaleString()," loaded rows"]})]})]})})]})]})]})}function De(e,r,s,o){return s||(e?r.isLoading?"Loading live report pack…":r.error?`Live report pack unavailable: ${U(r.error)}. Using loaded aggregate fallback.`:r.isFetching?"Refreshing live report pack…":r.data&&r.isStale?"Cached live report pack is stale; refresh is available.":"Live report pack ready.":o||"Static mode: using the loaded aggregate snapshot.")}function Ke(e,r){const s=JSON.stringify(r,null,2),o=new Blob([s],{type:"application/json;charset=utf-8"}),t=typeof URL.createObjectURL=="function"?URL.createObjectURL(o):`data:application/json;charset=utf-8,${encodeURIComponent(s)}`,i=document.createElement("a");i.href=t,i.download=e,i.rel="noopener",document.body.append(i),i.click(),i.remove(),t.startsWith("blob:")&&typeof URL.revokeObjectURL=="function"&&URL.revokeObjectURL(t)}function U(e){return e instanceof Error?e.message:String(e)}export{rt as ReportsPage,tt as reportCallsForCurrentUrl};
diff --git a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/ThreadsPage.js b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/ThreadsPage.js
index c1549599..372473fe 100644
--- a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/ThreadsPage.js
+++ b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/ThreadsPage.js
@@ -1,6 +1,6 @@
-import{j as t,r as c}from"./dashboard-react.js";import{u as Me}from"./useInfiniteQuery.js";import{c as Tt,t as yt,p as W,m as fe,f as Ue,u as ze,a as V,C as St,s as Fe,S as He,b as vt,D as kt,d as Nt,e as Pt,g as Mt,h as Ft,r as Lt,i as Rt,j as _t}from"./App.js";import{t as $t,a as Et}from"./exploreQueries.js";import{E as Dt,e as At}from"./ExploreWorkspaceSwitcher.js";import{E as It,u as Bt}from"./EvidenceGrid.js";import{r as Vt}from"./filtering.js";import{t as Wt}from"./threadSummaryAdapter.js";import{v as qe,V as Le}from"./UsageConstellation.js";import{P as Re,S as _e}from"./Panel.js";import{P as Ut}from"./PageLoadProgress.js";import{S as zt}from"./Primitives.js";import"./useBaseQuery.js";import"./dashboardRouter.js";import"./router.js";import"./queryOptions.js";import"./infiniteQueryOptions.js";import"./index2.js";import"./triangle-alert.js";/**
+import{j as t,r as c}from"./dashboard-react.js";import{u as Fe}from"./useInfiniteQuery.js";import{c as wt,t as yt,p as U,m as ge,f as ze,u as ae,a as W,C as St,s as Le,S as He,b as vt,D as kt,d as Nt,e as Pt,g as Mt,h as Ft,r as Lt,i as Rt,j as _t}from"./App.js";import{t as $t,a as Et}from"./exploreQueries.js";import{E as Dt,e as At}from"./ExploreWorkspaceSwitcher.js";import{E as It,u as Bt}from"./EvidenceGrid.js";import{r as Vt}from"./filtering.js";import{t as Wt}from"./threadSummaryAdapter.js";import{v as qe,V as Re}from"./UsageConstellation.js";import{P as _e,S as $e}from"./Panel.js";import{P as Ut}from"./PageLoadProgress.js";import{S as zt}from"./Primitives.js";import"./useBaseQuery.js";import"./dashboardRouter.js";import"./router.js";import"./queryOptions.js";import"./infiniteQueryOptions.js";import"./index2.js";import"./triangle-alert.js";/**
  * @license lucide-react v0.468.0 - ISC
  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const Ht=Tt("RotateCcw",[["path",{d:"M3 12a9 9 0 1 0 9-9 9.75 9.75 0 0 0-6.74 2.74L3 8",key:"1357e3"}],["path",{d:"M3 3v5h5",key:"1xhq8a"}]]),qt=new Set(["all","High","Medium","Low"]);function Qt(e){const n=[],r=[e.localQuery.trim(),e.globalQuery.trim()].filter(Boolean);r.length&&n.push(`Search ${r.map(s=>`"${s}"`).join(" + ")}`),e.riskFilter!=="all"&&n.push(`Cold risk ${e.riskFilter}`),e.selectedThreadName&&n.push(`Selected ${e.selectedThreadName}`);const a=`Showing ${e.shownCount.toLocaleString()} of ${e.totalCount.toLocaleString()} grouped threads`;return n.length?`${a} - Filters: ${n.join("; ")}`:a}function Gt(e,{localQuery:n,globalQuery:r,riskFilter:a}){if(a!=="all"&&e.coldResumeRisk!==a)return!1;const s=[e.name,e.coldResumeRisk,e.totalTokens,e.cost,e.cachePct];return[r,n].every(i=>Vt(s,i))}function Qe(e){return qt.has(e)?e:"all"}const x=5,D=250,Y="__detail_first__",Ot=new Set(["newest","duration","gap","initiator","model","effort","tokens","cached","uncached","output","reasoning","cost","cache"]),ge=new Set(yt.map(e=>e.id).filter(e=>e!=="investigate"));function Jt(e=window.location.href){var n;return((n=new URL(e).searchParams.get("thread"))==null?void 0:n.trim())||null}function Xt(e=window.location.href){const n=Jt(e);if(n)return n;const r=tn(e);return r||(_("detail",e)==="first"?Y:null)}function _(e,n=window.location.href){var r;return((r=new URL(n).searchParams.get(e))==null?void 0:r.trim())??""}function Ge(e=window.location.href){return Qe(_("risk",e))}function Oe(e,n){return e.filter(r=>Gt(r,n))}function me(e,n){const r=n[0];return!r||!ge.has(r.id)?[...e]:[...e].sort((a,s)=>an(a,s,r.id,r.desc))}function Je(e=window.location.href){const n=nn(_("sort",e));return ge.has(n)?[{id:n,desc:_("direction",e)==="desc"}]:[]}function Yt(e,n=window.location.href){const r=Number(_("page",n)||1);return Number.isFinite(r)&&r>1?Math.floor(r)*e:e}function Zt(e=window.location.href){return Xe(_("thread_call_sort",e))}function Kt(e,n=window.location.href){const r=_("thread_call_direction",n).toLowerCase();return r==="asc"||r==="desc"?r:Z(e)}function en(e,n=window.location.href){const r=Number(_("thread_call_page",n)||1);return Number.isFinite(r)&&r>1?Math.floor(r)*e:e}function Xe(e){const n=rn(e);return Ot.has(n)?n:"newest"}function Z(e){return e==="cache"||e==="effort"||e==="initiator"||e==="model"?"asc":"desc"}function $e(e,n=window.location.href){const r=new URL(n);r.searchParams.set("view","threads"),r.searchParams.delete("record"),r.searchParams.delete("detail"),r.searchParams.delete("expand"),r.searchParams.delete("threads");const a=e.sorting[0],s=a&&ge.has(a.id)?a.id:"";return E(r,"thread_q",e.localQuery.trim(),""),E(r,"risk",e.riskFilter,"all"),E(r,"thread",e.selectedThreadName??"",""),E(r,"sort",s,""),E(r,"direction",s?a!=null&&a.desc?"desc":"asc":"",""),E(r,"page",String(Ee(e.visibleRowCount,D)),"1"),E(r,"thread_call_sort",e.threadCallSort,"newest"),E(r,"thread_call_direction",e.threadCallSortDirection,Z(e.threadCallSort)),E(r,"thread_call_page",String(Ee(e.visibleThreadCallCount,x)),"1"),r}function Ee(e,n){return Math.max(1,Math.ceil(Math.max(e,n)/n))}function tn(e){var s,i;const n=new URL(e).searchParams,r=(s=n.get("expand"))==null?void 0:s.trim();if(r==="first"||r==="all")return Y;const a=(i=n.get("threads"))==null?void 0:i.split(",").map(l=>l.trim()).filter(Boolean);return(a==null?void 0:a[0])??null}function nn(e){return e==="total"?"totalTokens":e==="usage"?"credits":e==="cache"?"cachePct":e==="context"?"contextPct":e}function rn(e){return e==="time"?"newest":e==="total"?"tokens":e}function an(e,n,r,a){const 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calls`,tone:w.hydrated?"green":"blue"})]})]}),t.jsxs("div",{className:_.splitWorkspace,children:[t.jsxs("section",{className:_.evidenceSurface,"aria-label":"Thread evidence",children:[m==="table"?t.jsxs(t.Fragment,{children:[t.jsx(It,{ariaLabel:b,columns:v,data:C,identityColumnId:"name",lockedColumnIds:["investigate"],getRowId:h=>h.name,mobile:{primary:h=>h.name,secondary:h=>z.translateText(`${h.turns} calls · ${W(h.totalTokens)} tokens · ${U(h.cachePct)} cache`),actionLabel:h=>Nt(h)},sorting:j,onSortingChange:N,manualSorting:!0,columnVisibility:p.columnVisibility,onColumnVisibilityChange:p.setColumnVisibility,density:p.density,onDensityChange:p.setDensity,onRestoreDefaults:p.restoreDefaults,selectedRowId:u==null?void 0:u.name,onRowSelect:h=>ee(h.name),onRowActivate:re,viewportHeight:560}),t.jsxs("div",{className:_.gridFooter,"aria-live":"polite",children:[t.jsx("span",{children:z.translateText(`${C.length.toLocaleString()} loaded / ${H.toLocaleString()} 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e.filter(i=>a.has(i.thread)||r.has(i.id)).sort((i,o)=>(a.get(i.thread)??r.get(i.id)??0)-(a.get(o.thread)??r.get(o.id)??0)||(s.get(i.id)??0)-(s.get(o.id)??0))}function ga({model:e,globalQuery:n,onOpenInvestigator:a,onCopyCallLink:r,globalFilters:s,contextRuntime:i,includeArchived:o=!1,sourceKey:g,sourceRevision:b="",focusedEndpointsEnabled:m=!0,onNavigateView:f}){var ye,Se,ve,ke,Ne,Pe,Me;const w=ae(),[C,H]=c.useState(()=>$("thread_q")),[y,v]=c.useState(()=>Ge()),[j,p]=c.useState(()=>Xt()),[u,T]=c.useState(()=>Je()),[k,S]=c.useState(()=>Yt(A)),E=Zt(),[F,I]=c.useState(()=>E),[B,L]=c.useState(()=>Kt(E)),[G,N]=c.useState(()=>en(x)),[ee,re]=c.useState(""),[se,ie]=c.useState(""),[oe,te]=c.useState("table"),le=Bt("codexUsageThreadsEvidenceGrid",{density:"compact",columnVisibility:{}}),z=c.useRef(n),h=c.useMemo(()=>ln({runtime:i,enabled:m,globalQuery:n,localQuery:C,riskFilter:y,sorting:u}),[i,m,n,C,y,u]),P=Fe({...$t({runtime:i,includeArchived:o,sourceKey:g,sourceRevision:b,query:h.query,sort:h.sort,direction:h.direction,pageSize:A}),enabled:h.enabled,placeholderData:l=>l}),ce=c.useMemo(()=>new Map(e.threads.map(l=>[l.name,l])),[e.threads]),tt=c.useMemo(()=>{var l;return((l=P.data)==null?void 0:l.pages.flatMap(V=>V.rows.map(me=>Wt(me,ce.get(me.threadLabel)??ce.get(me.threadKey)))))??[]},[P.data,ce]),q=h.enabled&&!!P.data,be=q?tt:e.threads,O=c.useMemo(()=>Oe(be,{localQuery:C,globalQuery:n,riskFilter:y}),[n,C,y,be]),M=c.useMemo(()=>pe(O,u),[O,u]),de=q?((Se=(ye=P.data)==null?void 0:ye.pages[0])==null?void 0:Se.totalMatchedRows)??M.length:e.threads.length,nt=c.useMemo(()=>Qt({shownCount:O.length,totalCount:de,localQuery:C,globalQuery:n,riskFilter:y,selectedThreadName:j}),[n,C,y,j,M.length,de]),at=w.t("dashboard.top_threads_by_attention","Thread Leaderboard"),rt=w.t("dashboard.top_threads_by_attention","Thread leaderboard"),d=j===Y?M[0]??null:M.find(l=>l.name===j)??M[0]??null,J=j===Y?(d==null?void 0:d.name)??null:j,je=c.useMemo(()=>d?e.calls.filter(l=>xn(l.thread,d.name)).sort(Ze):[],[e.calls,d]),Ce=(d==null?void 0:d.threadKey)||((ve=je[0])==null?void 0:ve.threadKey)||(d==null?void 0:d.name)||"",R=Fe({...Et({runtime:i,includeArchived:o,sourceKey:g,sourceRevision:b,threadKey:Ce,sort:F==="newest"?"time":F,direction:B}),enabled:m&&!i.fileMode&&!!i.apiToken&&!!Ce,placeholderData:l=>l}),X=((ke=R.data)==null?void 0:ke.pages.flatMap(l=>l.rows))??je,he=((Pe=(Ne=R.data)==null?void 0:Ne.pages[0])==null?void 0:Pe.totalMatchedRows)??X.length,st=d?{...d,latestCallId:d.latestCallId||((Me=X[0])==null?void 0:Me.id)||""}:null,Te=c.useRef((d==null?void 0:d.name)??""),it=c.useMemo(()=>[...Pt,Mt({onOpenInvestigator:a,onCopyCallLink:r})],[r,a]),ot=c.useMemo(()=>dn(M,o?"all":"active",b),[o,M,b]),lt=c.useMemo(()=>hn(X,(d==null?void 0:d.name)??"",o?"all":"active",b),[o,d==null?void 0:d.name,X,b]);c.useEffect(()=>{const l=(d==null?void 0:d.name)??"";Te.current!==l&&(Te.current=l,N(x))},[d==null?void 0:d.name]),c.useEffect(()=>{z.current!==n&&(z.current=n,S(A),N(x))},[n]),c.useEffect(()=>{j===Y&&J&&p(J)},[j,J]),c.useEffect(()=>{const l=Ee({localQuery:C,riskFilter:y,selectedThreadName:J,sorting:u,visibleRowCount:k,threadCallSort:F,threadCallSortDirection:B,visibleThreadCallCount:G});l.toString()!==window.location.href&&window.history.replaceState(null,"",l)},[C,y,J,F,B,u,G,k]);function ct(){const l=et(e.calls,pe(O,u));Ft(`codex-thread-filtered-calls-${_t()}.csv`,Lt(l,Rt)),re(`Exported ${l.length} calls`)}function ue(){S(A),N(x)}function dt(l){H(l),ue()}function ht(l){v(Qe(l)),ue()}function ut(l){T(V=>typeof l=="function"?l(V):l),ue()}function mt(){H(""),v("all"),p(null),S(A),I("newest"),L(Z("newest")),N(x);const l=Ee({localQuery:"",riskFilter:"all",selectedThreadName:null,sorting:u,visibleRowCount:A,threadCallSort:"newest",threadCallSortDirection:Z("newest"),visibleThreadCallCount:x});window.history.replaceState(null,"",l),ie("Thread filters cleared")}function pt(l){p(l),N(x)}function ft(l){const V=Xe(l);I(V),L(Z(V)),N(x)}function gt(l){L(l==="asc"?"asc":"desc"),N(x)}function xt(l){l.latestCallId&&a(l.latestCallId)}function bt(l){l!=="threads"&&(window.history.replaceState(null,"",At(l)),f("calls"))}const we=q?M:M.slice(0,k),jt=q?!!P.hasNextPage:we.length<M.length;function Ct(){if(q&&P.hasNextPage){P.fetchNextPage();return}S(l=>Math.min(l+A,M.length))}function Tt(){R.hasNextPage&&R.fetchNextPage().then(l=>{l.isError||N(V=>Math.min(V+x,he))})}return t.jsx(Gn,{globalFilters:s,localQuery:C,riskFilter:y,exportDisabled:!O.length,exportStatus:ee,filterStatus:se,tableSubtitle:nt,tableTitle:at,tableLabel:rt,viewMode:oe,focusedState:{isFetching:P.isFetching,isFetchingNextPage:P.isFetchingNextPage,usingFocused:q,fallbackReason:h.reason,error:P.error?Ue(P.error):null},selectedCallsState:{isFetching:R.isFetching,count:he,hydrated:!!R.data,error:R.error?Ue(R.error):null},displayedThreads:we,totalMatchedThreads:de,canLoadMoreThreads:jt,columns:it,sorting:u,gridPreferences:le,selected:d,frontierSpec:ot,lifecycleSpec:lt,inspector:{selected:st,calls:X,allCalls:e.calls,totalCallCount:he,hasMoreCalls:!!R.hasNextPage,isFetchingMoreCalls:R.isFetchingNextPage,callSort:F,callSortDirection:B,visibleCallCount:G,onVisibleCallCountChange:N,onLoadMoreCalls:Tt},onWorkspaceChange:bt,onExport:ct,onClearFilters:mt,onLocalQueryChange:dt,onRiskFilterChange:ht,onViewModeChange:te,onSortingChange:ut,onSelectThread:pt,onActivateThread:xt,onLoadMoreThreads:Ct,onCallSortChange:ft,onCallSortDirectionChange:gt,onOpenInvestigator:a,onCopyCallLink:r})}function Ue(e){return e instanceof Error?e.message:String(e)}export{ga as ThreadsPage,fa as threadCallsForCurrentUrl,Jn as threadsForCurrentUrl};
diff --git a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/UsageConstellation.js b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/UsageConstellation.js
index d05bcc4c..cd5dd6c1 100644
--- a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/UsageConstellation.js
+++ b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/UsageConstellation.js
@@ -1,12 +1,12 @@
 const __vite__mapDeps=(i,m=__vite__mapDeps,d=(m.f||(m.f=["assets/echartsRenderer.js","assets/dashboard-react.js","assets/index.css","assets/UsageConstellationCanvas.js","assets/UsageConstellationCanvas.css"])))=>i.map(i=>d[i]);
-import{j as r,r as f,_ as V}from"./dashboard-react.js";import{c as q,L as H,Z as K,_ as U,D as B}from"./App.js";import{T as W}from"./triangle-alert.js";import"./Primitives.js";/**
+import{j as s,r as m,_ as M}from"./dashboard-react.js";import{c as O,u as T,L as Y,Z,_ as J,D as Q}from"./App.js";import{T as X}from"./triangle-alert.js";import"./Primitives.js";/**
  * @license lucide-react v0.468.0 - ISC
  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const G=q("Clock3",[["circle",{cx:"12",cy:"12",r:"10",key:"1mglay"}],["polyline",{points:"12 6 12 12 16.5 12",key:"1aq6pp"}]]);/**
+ */const ee=O("Clock3",[["circle",{cx:"12",cy:"12",r:"10",key:"1mglay"}],["polyline",{points:"12 6 12 12 16.5 12",key:"1aq6pp"}]]);/**
  * @license lucide-react v0.468.0 - ISC
  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const Y=q("LoaderCircle",[["path",{d:"M21 12a9 9 0 1 1-6.219-8.56",key:"13zald"}]]);function F(e){var a,n;if(e.kind==="flow")return Z(e);const t=(n=(a=e.interactions)==null?void 0:a.selection)==null?void 0:n.keyField;return e.data.rows.map((i,s)=>({key:String(t?i[t]??s:s),values:i}))}function I(e,t){if(e===null||e==="")return"Not available";if(typeof e=="boolean")return e?"Yes":"No";if(typeof e!="number")return String(e);switch(t.unit){case"percent":return`${e.toLocaleString(void 0,{maximumFractionDigits:1})}%`;case"ratio":return e.toLocaleString(void 0,{maximumFractionDigits:2});case"seconds":return`${e.toLocaleString(void 0,{maximumFractionDigits:1})}s`;case"usd":return e.toLocaleString(void 0,{style:"currency",currency:"USD",maximumFractionDigits:4});case"tokens":case"count":return e.toLocaleString(void 0,{maximumFractionDigits:0});case"credits":return e.toLocaleString(void 0,{maximumFractionDigits:2});default:return e.toLocaleString(void 0,{maximumFractionDigits:2})}}function Z(e){const t=new Map(e.data.nodes.map(a=>[a.id,a.label]));return e.data.links.map(a=>({key:a.id,values:{id:a.id,source:t.get(a.source)??a.source,target:t.get(a.target)??a.target,value:a.value,evidenceKey:a.evidenceKey??null}}))}function J(e){var n;const t=F(e),a=[e.title,M(e),e.accessibility.summary];return t.length&&a.push(`${t.length.toLocaleString()} table rows available.`),(n=e.caveats)!=null&&n.length&&a.push(`Caveats: ${e.caveats.join(" ")}`),e.accessibility.keyboardInstructions&&a.push(e.accessibility.keyboardInstructions),a.filter(Boolean).join(" ")}function M(e){switch(e.state.kind){case"ready":return"Data is ready.";case"loading":return e.state.message??"Visualization is loading.";case"empty":case"insufficient-data":case"partial":case"stale":case"error":return e.state.message}}const A="codex-usage-visualization/v1";function Q(e){const t=[];S(t,"schema",e.schema===A,`must equal 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Set(n).size!==n.length&&a.push({path:"table.columns",message:"column fields must be unique"}),j(t,n,"table.columns",a),e.table.defaultSort&&!n.includes(e.table.defaultSort.field)&&a.push({path:"table.defaultSort.field",message:"must reference a table column"})}function ae(e,t,a){var s,c,g;const n=(c=(s=e.interactions)==null?void 0:s.selection)==null?void 0:c.keyField;n&&j(t,[n],"interactions.selection",a);const i=(g=e.interactions)==null?void 0:g.zoom;(i==null?void 0:i.startPercent)!==void 0&&(i.startPercent<0||i.startPercent>100)&&a.push({path:"interactions.zoom.startPercent",message:"must be between 0 and 100"}),(i==null?void 0:i.endPercent)!==void 0&&(i.endPercent<0||i.endPercent>100)&&a.push({path:"interactions.zoom.endPercent",message:"must be between 0 and 100"})}function ie(e,t){const a=(e.annotations??[]).map(n=>n.id);new Set(a).size!==a.length&&t.push({path:"annotations",message:"annotation ids must be 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diff --git a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/UsageDrainPage.js b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/UsageDrainPage.js
index bf13cacd..98f93732 100644
--- a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/UsageDrainPage.js
+++ b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/UsageDrainPage.js
@@ -1 +1 @@
-import{r as y,j as a}from"./dashboard-react.js";import{u as V}from"./useQuery.js";import{P as fe}from"./PageLoadProgress.js";import{a as j,B as E,b as A,M as $,S as Q}from"./Primitives.js";import{v as be,V as ge}from"./UsageConstellation.js";import{a as J,S as we,b as xe,D as je,R as ke,F as X,j as Ce}from"./App.js";import{S as Se}from"./shield-check.js";import"./useBaseQuery.js";import"./triangle-alert.js";import"./dashboardRouter.js";import"./router.js";async function Ne(e,t={}){return D(e,"/api/allowance/history",I(t,!0),"codex-usage-tracker-allowance-history-v1","Allowance history")}async function Ae(e,t={}){return D(e,"/api/allowance/diagnostics",I(t,!0),"codex-usage-tracker-allowance-diagnostics-v1","Allowance diagnostics")}async function Pe(e,t={}){return D(e,"/api/allowance/export",I(t,!1),"codex-usage-tracker-allowance-evidence-export-v1","Allowance evidence export")}function I(e,t){const n=new URLSearchParams({limit:e.limit===null?"None":String(Math.max(0,Math.round(e.limit??0)))});return e.includeArchived&&n.set("include_archived","1"),e.windowKind&&n.set("window_kind",e.windowKind),t&&n.set("privacy_mode","normal"),n}async function D(e,t,n,l,r){Me(e);const i=await fetch(`${t}?${n.toString()}`,{headers:{Accept:"application/json","X-Codex-Usage-Token":e.apiToken},cache:"no-store"}),c=await i.json().catch(()=>({}));if(!i.ok)throw new Error(typeof c.error=="string"?c.error:`${r} failed with HTTP ${i.status}`);if(c.schema!==l)throw new Error(`${r} returned an unsupported schema.`);return c}function Me(e){if(e.fileMode||window.location.protocol==="file:")throw new Error("Live allowance intelligence requires the localhost dashboard server.");if(!e.apiToken)throw new Error("Live allowance intelligence requires the localhost dashboard API token.")}const Le="_section_rigat_1",$e="_header_rigat_7",Ee="_tableFrame_rigat_28",Re="_numeric_rigat_103",Te="_actions_rigat_108",Ie="_unlinked_rigat_140",De="_empty_rigat_145",He="_loadMore_rigat_152",v={section:Le,header:$e,tableFrame:Ee,numeric:Re,actions:Te,unlinked:Ie,empty:De,loadMore:He},R=20;function Fe({window:e,onOpenCall:t,onCopyCallLink:n}){const[l,r]=y.useState(R),i=y.useMemo(()=>[...e.points],[e.points]),c=i.slice(0,l);return y.useEffect(()=>r(R),[e.kind]),a.jsxs("section",{className:v.section,"aria-labelledby":"allowance-evidence-title",children:[a.jsxs("div",{className:v.header,children:[a.jsxs("div",{children:[a.jsx("h2",{id:"allowance-evidence-title",children:"Supporting windows"}),a.jsx("p",{children:"Exact local evidence behind the selected chart. 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This remains local evidence, not an internal ledger result.",tone:"risk"}:{badge:"Possible change",title:"The direction is consistent, but the sample is not claim-ready",detail:e.readiness.reasons[0]??"More weekly spans are required on both sides of the candidate split.",tone:"caution"}}function Qt(e){return[...e.calls].sort((t,n)=>ae(n)-ae(t)||n.totalTokens-t.totalTokens).slice(0,20)}function ze(e){return{schema:"codex-usage-tracker-allowance-evidence-export-v1",generated_at:e.generatedAt,privacy_mode:"strict",include_archived:e.includeArchived,summary:{primary_evidence_grade:e.primaryGrade,weekly_observation_count:e.weekly.observationCount,five_hour_observation_count:e.fiveHour.observationCount,positive_span_count:e.weekly.positiveSpanCount+e.fiveHour.positiveSpanCount,research_readiness:e.readiness},windows:[e.weekly,e.fiveHour].map(t=>({window_kind:t.kind,evidence_grade:t.evidenceGrade,observation_count:t.observationCount,positive_span_count:t.positiveSpanCount,points:t.points.map(n=>({id:n.id,label:n.label,timestamp:n.timestamp,estimate:n.estimate,low:n.low,high:n.high,deltaPercent:n.deltaPercent,credits:n.credits,grade:n.grade,plan:n.plan}))})),change_candidates:e.candidate?[e.candidate]:[],notes:[...e.notes,"Static dashboard fallback; local identifiers omitted."]}}function Z(e,t,n,l){var b,g;const r=((t==null?void 0:t.windows)??[]).filter(u=>u.window_kind===e),i=se(r),c=((n==null?void 0:n.rows)??[]).filter(u=>u.window_kind===e&&ne(u,i)).sort(et),s=((i==null?void 0:i.spans)??(t==null?void 0:t.spans)??[]).filter(u=>u.window_kind===e&&ne(u,i)).sort(tt),d=e==="weekly"?s.flatMap((u,w)=>Ke(u,w,i,l)):[],_=d.length?d:c.flatMap((u,w)=>Ve(u,w,i));return{kind:e,metric:d.length?"capacity_proxy":"remaining_percent",evidenceGrade:(i==null?void 0:i.evidence_grade)??(e==="five_hour"&&c.length?"counter_noise_likely":"insufficient_data"),observationCount:(i==null?void 0:i.observation_count)??c.length,positiveSpanCount:(i==null?void 0:i.positive_span_count)??s.length,resetCount:(i==null?void 0:i.span_stats.reset_or_negative_delta_rows)??nt(c),missingValueCount:(i==null?void 0:i.span_stats.missing_used_percent_rows)??c.filter(u=>u.used_percent===null).length,plan:(i==null?void 0:i.plan_type)??((b=c.find(u=>u.plan_type))==null?void 0:b.plan_type)??"unknown",limitId:(i==null?void 0:i.limit_id)??((g=c.find(u=>u.limit_id))==null?void 0:g.limit_id)??"unknown",history:c,points:_}}function Ke(e,t,n,l){if(e.credits_per_percent===null)return[];const r=e.end_observed_at??e.end_observed_date??null,i=Ye(l,r);return[{id:e.record_id||`weekly-span-${t}`,label:H(r,`Span ${t+1}`),timestamp:r,estimate:e.credits_per_percent*100,low:(i==null?void 0:i.low)===null||(i==null?void 0:i.low)===void 0?null:i.low*100,high:(i==null?void 0:i.high)===null||(i==null?void 0:i.high)===void 0?null:i.high*100,deltaPercent:e.delta_usage_percent,credits:e.estimated_usage_credits,grade:(n==null?void 0:n.evidence_grade)??"insufficient_data",plan:e.plan_type??(n==null?void 0:n.plan_type)??"unknown",recordId:e.record_id??null}]}function Ve(e,t,n){return e.remaining_percent===null?[]:[{id:e.record_id||`${e.window_kind}-observation-${t}`,label:H(e.observed_at??e.observed_date,`Observation ${t+1}`),timestamp:e.observed_at??e.observed_date,estimate:e.remaining_percent,low:null,high:null,deltaPercent:e.used_percent,credits:e.usage_credits,grade:(n==null?void 0:n.evidence_grade)??(e.window_kind==="five_hour"?"counter_noise_likely":"insufficient_data"),plan:e.plan_type??(n==null?void 0:n.plan_type)??"unknown",recordId:e.record_id??null}]}function Qe(e,t){const n=[...e.weeklyWindows].reverse().map((s,d)=>({id:`loaded-week-${d}`,label:s.week,timestamp:null,estimate:s.projected,low:null,high:null,deltaPercent:s.observedPct,credits:s.credits,grade:s.confidence.toLowerCase(),plan:s.plan,recordId:null})),l=[],r=re("Live allowance diagnostics are required before testing a change claim."),i=ee("weekly","capacity_proxy",n,e.weeklyWindows.length),c=ee("five_hour","remaining_percent",l,l.length);return{live:!1,generatedAt:t||"loaded-aggregate-snapshot",includeArchived:!1,weekly:i,fiveHour:c,primaryGrade:"insufficient_data",answer:C("Evidence status","Live allowance detector unavailable in this static snapshot","Projected weekly windows remain visible for orientation, but only the localhost detector can compare normalized positive spans and candidate regimes.","Descriptive fallback","context"),candidate:null,readiness:r,notes:["Loaded aggregate projections are descriptive fallback data, not detector output."]}}function ee(e,t,n,l){var r;return{kind:e,metric:t,evidenceGrade:e==="five_hour"?"counter_noise_likely":"insufficient_data",observationCount:l,positiveSpanCount:0,resetCount:0,missingValueCount:0,plan:((r=n[0])==null?void 0:r.plan)??"unknown",limitId:"loaded-aggregate",history:[],points:n}}function Je(e,t,n,l){return e==="no_change_detected"?C("Current result","No weekly regime change detected","The loaded positive spans remain within one local regime.","No change detected","positive"):e==="counter_noise_likely"?C("Current result","The 5-hour counter is behaving like a noisy rolling window","Use weekly spans as the primary signal before drawing a limit conclusion.","Counter noise likely","context"):e==="inconclusive_other_usage_possible"?C("Current result","Observed movement is not fully attributable to these local logs","Outside usage remains plausible, so the detector cannot isolate an allowance change.","Inconclusive","caution"):e==="possible_regime_change"?C("Candidate regime change",te(t),"The direction is consistent, but repeated weekly evidence is still below the public-claim threshold.","Possible change","caution"):e==="strong_local_evidence"?C("Candidate regime change",te(t),n.ready_for_public_claim?"Local sample, effect-size, and p-value thresholds are met. 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More observations are needed before comparing regimes.`,"Insufficient data","neutral")}function Xe(e){return e.primaryGrade==="no_change_detected"?{badge:"Consistent",title:"Stable weekly behavior fits the loaded evidence",detail:"No candidate split cleared the detector thresholds.",tone:"positive"}:e.primaryGrade==="inconclusive_other_usage_possible"?{badge:"Inconclusive",title:"Stable behavior cannot be isolated either",detail:"Outside usage and unexplained movement weaken both the stable and decreased hypotheses.",tone:"caution"}:{badge:"Not supported",title:"A candidate weekly shift conflicts with the stable hypothesis",detail:"Review the candidate split and readiness criteria before deciding whether the shift is durable.",tone:"risk"}}function C(e,t,n,l,r){return{label:e,title:t,detail:n,badge:l,tone:r}}function te(e){const t=e==null?void 0:e.capacity_ratio,n=H((e==null?void 0:e.candidate_start_observed_at)??null,"the candidate split");return t==null?`Weekly behavior shifted around ${n}`:`The recent local capacity proxy is ${Math.round(t*100)}% of the earlier regime after ${n}`}function Ye(e,t){return!e||!t?null:Date.parse(t)>=Date.parse(e.candidate_start_observed_at??"invalid")?e.statistical_evidence.median_confidence_interval_after_95:e.statistical_evidence.median_confidence_interval_before_95}function se(e){return[...e].sort((t,n)=>n.positive_span_count-t.positive_span_count||n.observation_count-t.observation_count)[0]}function ne(e,t){return t?(e.plan_type??null)===t.plan_type&&(e.limit_id??null)===t.limit_id:!0}function Ze(e){return[...e].sort((t,n)=>Number(n.statistical_evidence.public_claim_ready)-Number(t.statistical_evidence.public_claim_ready)||(t.capacity_ratio??1)-(n.capacity_ratio??1))[0]??null}function re(e){return{detector_version:"nonparametric-v1",ready_for_public_claim:!1,weekly_positive_span_count:0,minimum_split_spans_for_public_claim:6,p_value_threshold_for_public_claim:.05,best_candidate_capacity_ratio:null,reasons:[e]}}function et(e,t){return Date.parse(t.observed_at??"")-Date.parse(e.observed_at??"")}function tt(e,t){return Date.parse(t.end_observed_at??t.end_observed_date??"")-Date.parse(e.end_observed_at??e.end_observed_date??"")}function nt(e){return e.slice(1).filter((t,n)=>t.used_percent!==null&&e[n].used_percent!==null&&t.used_percent<(e[n].used_percent??0)).length}function H(e,t){if(!e)return t;const n=new Date(e);return Number.isNaN(n.getTime())?e:n.toLocaleDateString(void 0,{month:"short",day:"numeric",year:"numeric"})}function at(e){return[...new Set(e.filter(Boolean))]}function ae(e){return e.credits>0?e.credits:e.cost*25}function it(e,t){const n=t==="weekly"?e.weekly:e.fiveHour,l=n.metric==="capacity_proxy",r=n.points.map(m=>st(m)),i=n.points.flatMap(m=>[m.estimate,m.low,m.high]).filter(pt),c=r.length>=2,s=n.points.some(m=>m.low!==null&&m.high!==null),d=t!=="weekly"&&n.points.every(m=>m.timestamp&&Number.isFinite(Date.parse(m.timestamp)))?"time":"category",_=Math.min(12,r.length),b=r.length>_?Math.round(_/r.length*100):100,g=l?"Weekly local capacity evidence":t==="weekly"?"Observed weekly remaining":"5-hour rolling context",u=l?"Capacity proxy":"Remaining",w=l?"credits":"percent",f=lt(n,t==="weekly"?e.candidate:null);return{schema:be,id:`allowance-${t.replace("_","-")}`,title:g,description:l?e.live?"Estimated credits per 100 percentage points of observed weekly movement, with exact median intervals when the sample supports them.":"Loaded aggregate weekly projections for orientation. 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ot(e){return{id:e.id,window:e.timestamp??e.label,estimate:A(e.estimate),low:e.low===null?null:A(e.low),high:e.high===null?null:A(e.high),deltaPercent:e.deltaPercent===null?null:A(e.deltaPercent),credits:e.credits===null?null:A(e.credits),grade:e.grade,plan:e.plan}}function ct(e){const t=ce(e);return t.slice(1).flatMap((n,l)=>{const r=t[l];return n.used_percent===null||r.used_percent===null||n.used_percent>=r.used_percent||!n.observed_at?[]:[{id:`allowance-reset-${l}`,label:"Observed counter reset or rollback",kind:"reference-line",axis:"x",value:n.observed_at,severity:"info",evidenceKeys:n.record_id?[n.record_id]:void 0}]})}function dt(e,t){const n=ce(e),l=(t==="weekly"?48:8)*60*60*1e3;return n.slice(1).flatMap((r,i)=>{const c=n[i],s=Date.parse(c.observed_at??""),d=Date.parse(r.observed_at??"");return!Number.isFinite(s)||!Number.isFinite(d)||d-s<=l?[]:[{id:`allowance-gap-${i}`,label:"Observation 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evidence shown first.":"Secondary context only; rolling-window movement is noisy."})]}),a.jsx(Y,{label:"Allowance window",options:[{label:"Weekly",value:"weekly"},{label:"5-hour",value:"five_hour"}],value:d,onValueChange:he})]}),a.jsx(Ne,{spec:ue,height:340}),a.jsxs("div",{className:m.analysisGrid,children:[a.jsxs(N,{className:m.hypothesisPanel,children:[a.jsxs("div",{className:m.panelHeader,children:[a.jsxs("div",{children:[a.jsx("h2",{children:"Hypothesis check"}),a.jsx("p",{children:"Evaluate a community-style claim using the server detector result."})]}),a.jsx(X,{"aria-hidden":"true"})]}),a.jsx(Y,{label:"Allowance hypothesis",options:[{label:"Allowance decreased",value:"decreased"},{label:"Behavior stayed stable",value:"stable"}],value:_,onValueChange:pe}),a.jsx("div",{className:m.hypothesisResult,"data-tone":(g==null?void 0:g.tone)??"neutral",children:g?a.jsxs(a.Fragment,{children:[a.jsx(w,{tone:g.tone,children:g.badge}),a.jsx("strong",{children:g.title}),a.jsx("p",{children:g.detail})]}):a.jsxs(a.Fragment,{children:[a.jsx(w,{tone:"neutral",children:"Not evaluated"}),a.jsx("strong",{children:"Choose a claim, then test it against the weekly detector"}),a.jsx("p",{children:"The dashboard reports the backend evidence grade; it does not run a separate client-side detector."})]})}),a.jsxs(E,{variant:"primary",onClick:ve,children:[a.jsx(X,{}),"Test weekly claim"]})]}),a.jsxs(N,{tone:"subtle",className:m.methodPanel,children:[a.jsxs("div",{className:m.panelHeader,children:[a.jsxs("div",{children:[a.jsx("h2",{children:"Evidence grade"}),a.jsx("p",{children:"What supports or weakens the current result."})]}),a.jsx(w,{tone:Dt(o.primaryGrade),children:Ht(o.primaryGrade)})]}),a.jsxs("dl",{className:m.methodList,children:[a.jsxs("div",{children:[a.jsx("dt",{children:"Method"}),a.jsx("dd",{children:((z=o.candidate)==null?void 0:z.statistical_evidence.method)??"No candidate split tested"})]}),a.jsxs("div",{children:[a.jsx("dt",{children:"Effect size"}),a.jsx("dd",{children:se((K=o.candidate)==null?void 0:K.statistical_evidence.effect_size_cliffs_delta)})]}),a.jsxs("div",{children:[a.jsx("dt",{children:"One-sided p-value"}),a.jsx("dd",{children:se((V=o.candidate)==null?void 0:V.statistical_evidence.p_value_one_sided)})]}),a.jsxs("div",{children:[a.jsx("dt",{children:"95% median intervals"}),a.jsx("dd",{children:It(o)})]})]})]})]}),a.jsx(We,{window:de,onOpenCall:r,onCopyCallLink:i}),a.jsxs("details",{className:m.caveats,children:[a.jsxs("summary",{children:[a.jsx(Ae,{}),"Method, readiness, and caveats"]}),a.jsxs("ul",{children:[o.readiness.reasons.map(h=>a.jsx("li",{children:h},h)),o.notes.map(h=>a.jsx("li",{children:h},h)),a.jsx("li",{children:"Weekly observations are the primary signal. The 5-hour counter is rolling-window context."}),a.jsx("li",{children:"This project cannot read OpenAI's internal allowance ledger."})]})]})]})}function Et(){const e=new URLSearchParams(window.location.search);return{windowKind:e.get("limit_window")==="five_hour"?"five_hour":"weekly",hypothesis:e.get("limit_hypothesis")==="stable"?"stable":"decreased"}}function le(e,t){const n=new URL(window.location.href);n.searchParams.set("view","usage-drain"),e==="weekly"?n.searchParams.delete("limit_window"):n.searchParams.set("limit_window",e),t==="decreased"?n.searchParams.delete("limit_hypothesis"):n.searchParams.set("limit_hypothesis",t),window.history.replaceState(null,"",n)}function Rt(e){return e==null?"—":`${Math.round(e*100)}%`}function Tt(e){return e==null?"—":`${Math.round(e*10)/10}%`}function se(e){return e==null?"Not available":e.toLocaleString(void 0,{maximumFractionDigits:4})}function It(e){var r;const t=(r=e.candidate)==null?void 0:r.statistical_evidence,n=t==null?void 0:t.median_confidence_interval_before_95,l=t==null?void 0:t.median_confidence_interval_after_95;return n!=null&&n.available&&(l!=null&&l.available)?"Available for both regimes":n!=null&&n.available||l!=null&&l.available?"Available for one regime; the other sample is too small":"Unavailable at the current sample size"}function Dt(e){return e==="strong_local_evidence"?"risk":e==="possible_regime_change"||e==="inconclusive_other_usage_possible"?"caution":e==="no_change_detected"?"positive":e==="counter_noise_likely"?"context":"neutral"}function Ht(e){return e.replaceAll("_"," ")}function Ft(e,t){const n=URL.createObjectURL(new Blob([JSON.stringify(t,null,2)],{type:"application/json;charset=utf-8"})),l=document.createElement("a");l.href=n,l.download=e,document.body.append(l),l.click(),l.remove(),URL.revokeObjectURL(n)}function I(e){return e instanceof Error?e.message:String(e)}export{Yt as UsageDrainPage,Xt as usageDrainCallsForCurrentUrl};
diff --git a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/overviewQueries.js b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/overviewQueries.js
index f4738c9b..d5f19061 100644
--- a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/overviewQueries.js
+++ b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/overviewQueries.js
@@ -1,4 +1,4 @@
-import{j as d}from"./dashboard-react.js";import{G as L}from"./gauge.js";import{c as R,K as O,L as w,M as v,z as j,A as T,E,B as F}from"./App.js";import{q as N}from"./queryOptions.js";/**
+import{j as d}from"./dashboard-react.js";import{c as R,u as L,K as T,L as w,M as v,z as O,A as j,E,B as F}from"./App.js";import{G as P}from"./gauge.js";import{q as I}from"./queryOptions.js";/**
  * @license lucide-react v0.468.0 - ISC
  *
  * This source code is licensed under the ISC license.
@@ -8,4 +8,4 @@ import{j as d}from"./dashboard-react.js";import{G as L}from"./gauge.js";import{c
  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const P=R("PhoneCall",[["path",{d:"M22 16.92v3a2 2 0 0 1-2.18 2 19.79 19.79 0 0 1-8.63-3.07 19.5 19.5 0 0 1-6-6 19.79 19.79 0 0 1-3.07-8.67A2 2 0 0 1 4.11 2h3a2 2 0 0 1 2 1.72 12.84 12.84 0 0 0 .7 2.81 2 2 0 0 1-.45 2.11L8.09 9.91a16 16 0 0 0 6 6l1.27-1.27a2 2 0 0 1 2.11-.45 12.84 12.84 0 0 0 2.81.7A2 2 0 0 1 22 16.92z",key:"foiqr5"}],["path",{d:"M14.05 2a9 9 0 0 1 8 7.94",key:"vmijpz"}],["path",{d:"M14.05 6A5 5 0 0 1 18 10",key:"13nbpp"}]]),q={"Cache Hit Rate":w,"Cache Reuse":w,"Estimated Cost":_,"Estimated Credits":_,"Total Calls":P,"Total Tokens":O,"Usage Remaining":L};function me({card:e}){var r;const n=q[e.label]??O,t=e.trend.startsWith("down")||e.trend.includes("risk")?"negative":"positive";return d.jsxs("article",{className:`metric-card 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diff --git a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/runtime.js b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/runtime.js
index 7347d329..b0ce1f04 100644
--- a/src/codex_usage_tracker/plugin_data/dashboard/react/assets/runtime.js
+++ b/src/codex_usage_tracker/plugin_data/dashboard/react/assets/runtime.js
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diff --git a/src/codex_usage_tracker/server/api.py b/src/codex_usage_tracker/server/api.py
index b6cf242c..3c3f8914 100644
--- a/src/codex_usage_tracker/server/api.py
+++ b/src/codex_usage_tracker/server/api.py
@@ -132,20 +132,27 @@ def serve_dashboard(
     server = ThreadingHTTPServer((host, port), handler)
     legacy_url = f"http://{_url_host(host)}:{port}/{output.name}"
     dashboard_url = f"http://{_url_host(host)}:{port}/react-dashboard.html"
-    print(f"Serving Codex usage dashboard at {dashboard_url}")
-    print(f"Legacy dashboard fallback remains available at {legacy_url}")
-    context_mode = (
-        "enabled for explicit row actions"
-        if context_api_enabled
-        else "disabled until enabled from the dashboard"
-    )
-    print("Aggregate rows refresh through /api/usage with a per-server token.")
-    print(f"Raw context API is {context_mode}; context is never embedded in the dashboard HTML.")
+    if selected_language == "zh-Hans":
+        print(f"Codex 用量仪表盘正在运行：{dashboard_url}")
+        print(f"旧版仪表盘备用入口：{legacy_url}")
+        context_mode = "已启用，可按记录显式加载" if context_api_enabled else "已禁用，可稍后在仪表盘中启用"
+        print("聚合记录通过带服务器专用令牌的 /api/usage 接口刷新。")
+        print(f"原始上下文 API {context_mode}；仪表盘 HTML 中不会嵌入上下文。")
+    else:
+        print(f"Serving Codex usage dashboard at {dashboard_url}")
+        print(f"Legacy dashboard fallback remains available at {legacy_url}")
+        context_mode = (
+            "enabled for explicit row actions"
+            if context_api_enabled
+            else "disabled until enabled from the dashboard"
+        )
+        print("Aggregate rows refresh through /api/usage with a per-server token.")
+        print(f"Raw context API is {context_mode}; context is never embedded in the dashboard HTML.")
     if open_browser:
         webbrowser.open(dashboard_url)
     try:
         server.serve_forever()
     except KeyboardInterrupt:
-        print("\nStopping dashboard server.")
+        print("\n正在停止仪表盘服务器。" if selected_language == "zh-Hans" else "\nStopping dashboard server.")
     finally:
         server.server_close()
diff --git a/tests/cli/test_cli_help_i18n.py b/tests/cli/test_cli_help_i18n.py
new file mode 100644
index 00000000..b4a51e61
--- /dev/null
+++ b/tests/cli/test_cli_help_i18n.py
@@ -0,0 +1,38 @@
+from __future__ import annotations
+
+import argparse
+
+from codex_usage_tracker.cli.help_i18n import requested_cli_language
+from codex_usage_tracker.cli.parser import build_parser
+
+
+def test_chinese_help_localizes_sections_commands_and_options() -> None:
+    help_text = build_parser("zh-Hans").format_help()
+
+    assert help_text.startswith("用法：codex-usage-tracker")
+    assert "位置参数：" in help_text
+    assert "选项：" in help_text
+    assert "执行首次设置：安装插件、初始化定价、刷新索引并运行环境检查" in help_text
+    assert "仪表盘初始语言" in help_text
+    assert "setup" in help_text
+    assert "--lang" in help_text
+
+
+def test_chinese_subcommand_help_keeps_command_contracts() -> None:
+    parser = build_parser("zh-Hans")
+    subparsers_action = next(
+        action for action in parser._actions if isinstance(action, argparse._SubParsersAction)
+    )
+    help_text = subparsers_action.choices["serve-dashboard"].format_help()
+
+    assert help_text.startswith("用法：codex-usage-tracker serve-dashboard")
+    assert "生成并提供仪表盘前刷新 SQLite 索引" in help_text
+    assert "--no-refresh" in help_text
+    assert "--context-api" in help_text
+
+
+def test_requested_cli_language_reads_flag_or_environment(monkeypatch) -> None:
+    monkeypatch.setenv("CODEX_USAGE_TRACKER_LANG", "zh-CN")
+    assert requested_cli_language([]) == "zh-Hans"
+    assert requested_cli_language(["--lang", "en", "summary"]) == "en"
+    assert requested_cli_language(["--lang=zh", "summary"]) == "zh-Hans"
diff --git a/tests/server/test_server_api.py b/tests/server/test_server_api.py
index 2b835cbf..a145912b 100644
--- a/tests/server/test_server_api.py
+++ b/tests/server/test_server_api.py
@@ -3,14 +3,34 @@
 from functools import partial
 from pathlib import Path
 
+import pytest
+
 from codex_usage_tracker.server import api as server_api
 from codex_usage_tracker.server.query_cache import AggregateQueryCache
 
 
+@pytest.mark.parametrize(
+    ("language", "dashboard_message", "legacy_message"),
+    [
+        (
+            None,
+            "Serving Codex usage dashboard at http://127.0.0.1:8765/react-dashboard.html",
+            "Legacy dashboard fallback remains available at http://127.0.0.1:8765/dashboard.html",
+        ),
+        (
+            "zh-Hans",
+            "Codex 用量仪表盘正在运行：http://127.0.0.1:8765/react-dashboard.html",
+            "旧版仪表盘备用入口：http://127.0.0.1:8765/dashboard.html",
+        ),
+    ],
+)
 def test_serve_dashboard_opens_react_dashboard_and_prints_legacy_fallback(
     tmp_path: Path,
     monkeypatch,
     capsys,
+    language: str | None,
+    dashboard_message: str,
+    legacy_message: str,
 ) -> None:
     opened: list[str] = []
     handlers: list[object] = []
@@ -46,15 +66,13 @@ def generate_dashboard(**kwargs: object) -> Path:
         host="127.0.0.1",
         port=8765,
         open_browser=True,
+        language=language,
     )
 
     output = capsys.readouterr().out
     assert opened == ["http://127.0.0.1:8765/react-dashboard.html"]
-    assert "Serving Codex usage dashboard at http://127.0.0.1:8765/react-dashboard.html" in output
-    assert (
-        "Legacy dashboard fallback remains available at http://127.0.0.1:8765/dashboard.html"
-        in output
-    )
+    assert dashboard_message in output
+    assert legacy_message in output
     assert handlers
     handler = handlers[0]
     assert isinstance(handler, partial)

From ecaea28974b73aa3acbfc7ee84e0a1af297cad79 Mon Sep 17 00:00:00 2001
From: Monsky <douglas.monsky@gmail.com>
Date: Wed, 15 Jul 2026 14:36:04 -0400
Subject: [PATCH 2/3] test: tolerate wrapped localized CLI help

---
 tests/cli/test_cli_help_i18n.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/tests/cli/test_cli_help_i18n.py b/tests/cli/test_cli_help_i18n.py
index b4a51e61..23461c68 100644
--- a/tests/cli/test_cli_help_i18n.py
+++ b/tests/cli/test_cli_help_i18n.py
@@ -24,9 +24,10 @@ def test_chinese_subcommand_help_keeps_command_contracts() -> None:
         action for action in parser._actions if isinstance(action, argparse._SubParsersAction)
     )
     help_text = subparsers_action.choices["serve-dashboard"].format_help()
+    compact_help = "".join(help_text.split())
 
     assert help_text.startswith("用法：codex-usage-tracker serve-dashboard")
-    assert "生成并提供仪表盘前刷新 SQLite 索引" in help_text
+    assert "生成并提供仪表盘前刷新SQLite索引" in compact_help
     assert "--no-refresh" in help_text
     assert "--context-api" in help_text
 

From 144a76fa0813828c8862c190059ef617e54e0816 Mon Sep 17 00:00:00 2001
From: Monsky <douglas.monsky@gmail.com>
Date: Wed, 15 Jul 2026 14:44:37 -0400
Subject: [PATCH 3/3] fix: localize Python 3.10 boolean help defaults

---
 src/codex_usage_tracker/cli/help_i18n.py |  7 +++++++
 tests/cli/test_cli_help_i18n.py          | 21 ++++++++++++++++++++-
 2 files changed, 27 insertions(+), 1 deletion(-)

diff --git a/src/codex_usage_tracker/cli/help_i18n.py b/src/codex_usage_tracker/cli/help_i18n.py
index 935a238d..06ed852c 100644
--- a/src/codex_usage_tracker/cli/help_i18n.py
+++ b/src/codex_usage_tracker/cli/help_i18n.py
@@ -8,6 +8,8 @@
 from codex_usage_tracker.core.i18n import normalize_language
 
 _ZH_HANS = "zh-Hans"
+_ARGPARSE_DEFAULT_SUFFIX = " (default: %(default)s)"
+_ZH_HANS_DEFAULT_SUFFIX = "（默认值：%(default)s）"
 
 _ZH_HANS_HELP: dict[str, str] = {
     "show this help message and exit": "显示此帮助信息并退出",
@@ -156,6 +158,11 @@ def localized_cli_error_prefix(language: str | None) -> str:
 def _translate(value: str | None) -> str | None:
     if value is None:
         return None
+    if value.endswith(_ARGPARSE_DEFAULT_SUFFIX):
+        base_value = value[: -len(_ARGPARSE_DEFAULT_SUFFIX)]
+        translated = _ZH_HANS_HELP.get(base_value)
+        if translated is not None:
+            return translated + _ZH_HANS_DEFAULT_SUFFIX
     return _ZH_HANS_HELP.get(value, value)
 
 
diff --git a/tests/cli/test_cli_help_i18n.py b/tests/cli/test_cli_help_i18n.py
index 23461c68..62745d5f 100644
--- a/tests/cli/test_cli_help_i18n.py
+++ b/tests/cli/test_cli_help_i18n.py
@@ -2,7 +2,7 @@
 
 import argparse
 
-from codex_usage_tracker.cli.help_i18n import requested_cli_language
+from codex_usage_tracker.cli.help_i18n import localize_parser_help, requested_cli_language
 from codex_usage_tracker.cli.parser import build_parser
 
 
@@ -32,6 +32,25 @@ def test_chinese_subcommand_help_keeps_command_contracts() -> None:
     assert "--context-api" in help_text
 
 
+def test_chinese_help_translates_python_310_boolean_default_suffix() -> None:
+    parser = argparse.ArgumentParser()
+    action = parser.add_argument(
+        "--refresh",
+        help=(
+            "Refresh the SQLite index before generating and serving the dashboard. "
+            "This is the default; use --no-refresh to serve the cached index only. "
+            "(default: %(default)s)"
+        ),
+    )
+
+    localize_parser_help(parser, "zh-Hans")
+
+    assert action.help == (
+        "生成并提供仪表盘前刷新 SQLite 索引（默认行为）；使用 --no-refresh 可只提供缓存索引。"
+        "（默认值：%(default)s）"
+    )
+
+
 def test_requested_cli_language_reads_flag_or_environment(monkeypatch) -> None:
     monkeypatch.setenv("CODEX_USAGE_TRACKER_LANG", "zh-CN")
     assert requested_cli_language([]) == "zh-Hans"