Add mechanical stuck-loop guard for agent loops

README.md

@@ -13,6 +13,7 @@
 
 ## Table of Contents
 
+- [What's new (2026-06-20) — Stuck-Loop Guard (Agent Loop Progress Detection)](#whats-new-2026-06-20--stuck-loop-guard-agent-loop-progress-detection)
 - [What's new (2026-06-20) — Coordinate-Space Mapping (Model Grid ⇄ Physical Pixels)](#whats-new-2026-06-20--coordinate-space-mapping-model-grid--physical-pixels)
 - [What's new (2026-06-20) — Voice-Command Router](#whats-new-2026-06-20--voice-command-router)
 - [What's new (2026-06-20) — Locale-Aware Number, Currency & Date Parsing](#whats-new-2026-06-20--locale-aware-number-currency--date-parsing)
@@ -98,6 +99,12 @@
 
 ---
 
+## What's new (2026-06-20) — Stuck-Loop Guard (Agent Loop Progress Detection)
+
+Catch agents stuck in no-progress loops. Full reference: [`docs/source/Eng/doc/new_features/v46_features_doc.rst`](docs/source/Eng/doc/new_features/v46_features_doc.rst).
+
+- **`LoopGuard` / `digest_result`** (`AC_loop_guard_observe` / `AC_loop_guard_reset`, `ac_*`): the top computer-use failure mode is an agent repeating an action with no effect — and the model can't see its own loop. `LoopGuard` watches the `(tool, args, result)` stream and flags `repeat` (same call N times), `ping_pong` (A-B-A-B), and `no_op` (observation digest unchanged), escalating `ok`→`warn`→`critical` by run length. Complements the step/time budget and offline trajectory eval; pure-stdlib, deterministic.
+
 ## What's new (2026-06-20) — Coordinate-Space Mapping (Model Grid ⇄ Physical Pixels)
 
 Translate computer-use model clicks to real pixels. Full reference: [`docs/source/Eng/doc/new_features/v45_features_doc.rst`](docs/source/Eng/doc/new_features/v45_features_doc.rst).

README/README_zh-CN.md

@@ -12,6 +12,7 @@
 
 ## 目录
 
+- [本次更新 (2026-06-20) — 卡循环守卫(Agent Loop 进度检测)](#本次更新-2026-06-20--卡循环守卫agent-loop-进度检测)
 - [本次更新 (2026-06-20) — 坐标空间映射(模型网格 ⇄ 物理像素)](#本次更新-2026-06-20--坐标空间映射模型网格--物理像素)
 - [本次更新 (2026-06-20) — 语音指令路由器](#本次更新-2026-06-20--语音指令路由器)
 - [本次更新 (2026-06-20) — 区域设置感知的数字、货币与日期解析](#本次更新-2026-06-20--区域设置感知的数字货币与日期解析)
@@ -97,6 +98,12 @@
 
 ---
 
+## 本次更新 (2026-06-20) — 卡循环守卫(Agent Loop 进度检测)
+
+捕捉卡在无进展循环的 agent。完整参考:[`docs/source/Zh/doc/new_features/v46_features_doc.rst`](../docs/source/Zh/doc/new_features/v46_features_doc.rst)。
+
+- **`LoopGuard` / `digest_result`**(`AC_loop_guard_observe` / `AC_loop_guard_reset`、`ac_*`):电脑操作最主要的失败模式是 agent 重复一个无效果的动作 —— 而模型看不到自己的循环。`LoopGuard` 观察 `(tool, args, result)` 流并标记 `repeat`(相同调用 N 次)、`ping_pong`(A-B-A-B)与 `no_op`(观察摘要不变),依执行长度由 `ok`→`warn`→`critical` 升级。与步数/时间预算及离线轨迹评估互补;纯标准库、具确定性。
+
 ## 本次更新 (2026-06-20) — 坐标空间映射(模型网格 ⇄ 物理像素)
 
 将电脑操作模型的点击转成物理像素。完整参考:[`docs/source/Zh/doc/new_features/v45_features_doc.rst`](../docs/source/Zh/doc/new_features/v45_features_doc.rst)。

README/README_zh-TW.md

@@ -12,6 +12,7 @@
 
 ## 目錄
 
+- [本次更新 (2026-06-20) — 卡迴圈守衛(Agent Loop 進度偵測)](#本次更新-2026-06-20--卡迴圈守衛agent-loop-進度偵測)
 - [本次更新 (2026-06-20) — 座標空間對映(模型網格 ⇄ 實體像素)](#本次更新-2026-06-20--座標空間對映模型網格--實體像素)
 - [本次更新 (2026-06-20) — 語音指令路由器](#本次更新-2026-06-20--語音指令路由器)
 - [本次更新 (2026-06-20) — 區域設定感知的數字、貨幣與日期解析](#本次更新-2026-06-20--區域設定感知的數字貨幣與日期解析)
@@ -97,6 +98,12 @@
 
 ---
 
+## 本次更新 (2026-06-20) — 卡迴圈守衛(Agent Loop 進度偵測)
+
+捕捉卡在無進展迴圈的 agent。完整參考:[`docs/source/Zh/doc/new_features/v46_features_doc.rst`](../docs/source/Zh/doc/new_features/v46_features_doc.rst)。
+
+- **`LoopGuard` / `digest_result`**(`AC_loop_guard_observe` / `AC_loop_guard_reset`、`ac_*`):電腦操作最主要的失敗模式是 agent 重複一個無效果的動作 —— 而模型看不到自己的迴圈。`LoopGuard` 觀察 `(tool, args, result)` 串流並標記 `repeat`(相同呼叫 N 次)、`ping_pong`(A-B-A-B)與 `no_op`(觀察摘要不變),依執行長度由 `ok`→`warn`→`critical` 升級。與步數/時間預算及離線軌跡評估互補;純標準函式庫、具確定性。
+
 ## 本次更新 (2026-06-20) — 座標空間對映(模型網格 ⇄ 實體像素)
 
 將電腦操作模型的點擊轉成真實像素。完整參考:[`docs/source/Zh/doc/new_features/v45_features_doc.rst`](../docs/source/Zh/doc/new_features/v45_features_doc.rst)。

docs/source/Eng/doc/new_features/v46_features_doc.rst

@@ -0,0 +1,52 @@
+Stuck-Loop Guard (Agent Loop Progress Detection)
+================================================
+
+The dominant computer-use failure mode is an agent burning its budget repeating
+an action that has no effect — and the model usually can't see its own loop, so
+it must be caught **mechanically** from outside, by watching the stream of
+``(tool, args, result)`` triples. ``LoopGuard`` flags three patterns:
+
+- ``repeat`` — the same ``(tool, args)`` fired many times in a row;
+- ``ping_pong`` — two actions alternating A-B-A-B with no progress;
+- ``no_op`` — the observation (a screenshot/state digest) never changes.
+
+It complements a step/time budget (which can't tell a productive loop from a
+stuck one) and the offline trajectory evaluator. Pure standard library
+(``collections`` + ``hashlib``), deterministic; imports no ``PySide6``.
+
+Headless API
+------------
+
+.. code-block:: python
+
+    from je_auto_control import LoopGuard, digest_result
+
+    guard = LoopGuard(warn=8, critical=15)
+    for step in agent_steps:
+        verdict = guard.observe(step.tool, step.args,
+                                digest_result(step.screenshot))
+        if verdict.level == "critical":
+            break                       # abort: stuck loop
+        if verdict.level == "warn":
+            nudge_the_model(verdict.pattern)
+
+``observe`` returns ``{pattern, level, count}`` where ``level`` is ``ok`` /
+``warn`` / ``critical`` once the run length crosses the thresholds. ``count`` is
+the length of the detected run. ``digest_result`` makes a stable short hash of a
+screenshot/observation (bytes or any JSON-able value). ``reset`` clears history.
+
+Executor commands
+-----------------
+
+A module-level default guard backs the executor/MCP surfaces so a flow can track
+progress across steps:
+
+================================ ===================================================
+Command                          Effect
+================================ ===================================================
+``AC_loop_guard_observe``        Feed a step; returns ``{pattern, level, count}``.
+``AC_loop_guard_reset``          Clear the default guard's history.
+================================ ===================================================
+
+The same operations are exposed as MCP tools (``ac_loop_guard_observe`` /
+``ac_loop_guard_reset``) and as Script Builder commands under **Agent**.

docs/source/Eng/eng_index.rst

@@ -68,6 +68,7 @@ Comprehensive guides for all AutoControl features.
    doc/new_features/v43_features_doc
    doc/new_features/v44_features_doc
    doc/new_features/v45_features_doc
+   doc/new_features/v46_features_doc
    doc/ocr_backends/ocr_backends_doc
    doc/observability/observability_doc
    doc/operations_layer/operations_layer_doc

docs/source/Zh/doc/new_features/v46_features_doc.rst

@@ -0,0 +1,48 @@
+卡迴圈守衛(Agent Loop 進度偵測)
+================================
+
+電腦操作最主要的失敗模式,是 agent 不斷重複一個沒有效果的動作而耗盡預算 —— 而模型通常
+看不到自己的迴圈,因此必須從外部以**機械方式**偵測,藉由觀察 ``(tool, args, result)``
+三元組串流。``LoopGuard`` 會標記三種模式:
+
+- ``repeat`` —— 相同的 ``(tool, args)`` 連續觸發多次;
+- ``ping_pong`` —— 兩個動作以 A-B-A-B 交替而毫無進展;
+- ``no_op`` —— 觀察結果(截圖/狀態摘要)從未改變。
+
+它與步數/時間預算(無法分辨有進展的迴圈與卡住的迴圈)以及離線軌跡評估互補。純標準函式
+庫(``collections`` + ``hashlib``)、具確定性;不匯入 ``PySide6``。
+
+無頭 API
+--------
+
+.. code-block:: python
+
+    from je_auto_control import LoopGuard, digest_result
+
+    guard = LoopGuard(warn=8, critical=15)
+    for step in agent_steps:
+        verdict = guard.observe(step.tool, step.args,
+                                digest_result(step.screenshot))
+        if verdict.level == "critical":
+            break                       # 中止:卡住的迴圈
+        if verdict.level == "warn":
+            nudge_the_model(verdict.pattern)
+
+``observe`` 回傳 ``{pattern, level, count}``,其中 ``level`` 在執行長度跨過門檻後為
+``ok`` / ``warn`` / ``critical``。``count`` 為偵測到的執行長度。``digest_result`` 為截
+圖/觀察結果(位元組或任何可 JSON 化的值)產生穩定的短雜湊。``reset`` 清除歷史。
+
+執行器指令
+----------
+
+模組層級的預設守衛支撐 executor/MCP 介面,讓流程可跨步驟追蹤進度:
+
+================================ ===================================================
+指令                             效果
+================================ ===================================================
+``AC_loop_guard_observe``        餵入一步;回傳 ``{pattern, level, count}``。
+``AC_loop_guard_reset``          清除預設守衛的歷史。
+================================ ===================================================
+
+相同操作亦提供為 MCP 工具(``ac_loop_guard_observe`` / ``ac_loop_guard_reset``),以及
+Script Builder 中 **Agent** 分類下的指令。

docs/source/Zh/zh_index.rst

@@ -68,6 +68,7 @@ AutoControl 所有功能的完整使用指南。
    doc/new_features/v43_features_doc
    doc/new_features/v44_features_doc
    doc/new_features/v45_features_doc
+   doc/new_features/v46_features_doc
    doc/ocr_backends/ocr_backends_doc
    doc/observability/observability_doc
    doc/operations_layer/operations_layer_doc

je_auto_control/__init__.py

@@ -255,6 +255,10 @@
 from je_auto_control.utils.coordinate_space import (
     CoordinateSpace, downscale_png, normalized_space, xga_space,
 )
+# Mechanical stuck-loop detection for agent loops
+from je_auto_control.utils.loop_guard import (
+    LoopGuard, LoopVerdict, default_loop_guard, digest_result,
+)
 # Background popup/interrupt watchdog (unattended automation)
 from je_auto_control.utils.watchdog import (
     PopupWatchdog, WatchdogRule, default_popup_watchdog,
@@ -710,6 +714,7 @@ def start_autocontrol_gui(*args, **kwargs):
     "parse_number",
     "VoiceCommand", "VoiceRouter", "default_voice_router",
     "CoordinateSpace", "downscale_png", "normalized_space", "xga_space",
+    "LoopGuard", "LoopVerdict", "default_loop_guard", "digest_result",
     # MCP server
     "AuditLogger", "HttpMCPServer", "MCPContent", "MCPPrompt",
     "MCPPromptArgument", "MCPResource", "MCPServer", "MCPTool",

je_auto_control/gui/script_builder/command_schema.py

@@ -1041,6 +1041,21 @@ def _add_misc_specs(specs: List[CommandSpec]) -> None:
         ),
         description="Map a physical-pixel coordinate to a model grid.",
     ))
+    specs.append(CommandSpec(
+        "AC_loop_guard_observe", "Agent", "Loop Guard: Observe Step",
+        fields=(
+            FieldSpec("tool", FieldType.STRING, placeholder="AC_click_mouse"),
+            FieldSpec("args", FieldType.STRING, optional=True,
+                      placeholder='{"x": 10, "y": 20}'),
+            FieldSpec("result_digest", FieldType.STRING, optional=True),
+        ),
+        description="Detect repeat/ping-pong/no-op stuck-loop patterns.",
+    ))
+    specs.append(CommandSpec(
+        "AC_loop_guard_reset", "Agent", "Loop Guard: Reset",
+        fields=(),
+        description="Clear the default loop guard's history.",
+    ))
     specs.append(CommandSpec(
         "AC_generate_sop", "Report", "Generate SOP Document",
         fields=(

je_auto_control/utils/executor/action_executor.py

@@ -3213,6 +3213,22 @@ def _to_model(x: int, y: int, physical_w: int, physical_h: int,
     return {"x": mx, "y": my}
 
 
+def _loop_guard_observe(tool: str, args: Any = None,
+                        result_digest: str = "") -> Dict[str, Any]:
+    """Adapter: feed a step to the default loop guard; report the verdict."""
+    from je_auto_control.utils.loop_guard import default_loop_guard
+    verdict = default_loop_guard.observe(tool, args, result_digest)
+    return {"pattern": verdict.pattern, "level": verdict.level,
+            "count": verdict.count}
+
+
+def _loop_guard_reset() -> Dict[str, Any]:
+    """Adapter: clear the default loop guard's history."""
+    from je_auto_control.utils.loop_guard import default_loop_guard
+    default_loop_guard.reset()
+    return {"reset": True}
+
+
 class Executor:
     """
     Executor
@@ -3485,6 +3501,8 @@ def __init__(self):
             "AC_voice_clear": _voice_clear,
             "AC_to_physical": _to_physical,
             "AC_to_model": _to_model,
+            "AC_loop_guard_observe": _loop_guard_observe,
+            "AC_loop_guard_reset": _loop_guard_reset,
             "AC_a11y_record_start": _a11y_record_start,
             "AC_a11y_record_stop": _a11y_record_stop,
             "AC_a11y_record_events": _a11y_record_events,

je_auto_control/utils/loop_guard/__init__.py

@@ -0,0 +1,8 @@
+"""Mechanical stuck-loop detection for agent loops."""
+from je_auto_control.utils.loop_guard.loop_guard import (
+    LoopGuard, LoopVerdict, default_loop_guard, digest_result,
+)
+
+__all__ = [
+    "LoopGuard", "LoopVerdict", "default_loop_guard", "digest_result",
+]

je_auto_control/utils/loop_guard/loop_guard.py

@@ -0,0 +1,132 @@
+"""Detect when an agent loop is stuck, from outside the model.
+
+The dominant computer-use failure mode is an agent burning budget repeating an
+action that has no effect — the model usually can't see its own loop, so it must
+be caught mechanically by watching the stream of ``(tool, args, result)`` triples.
+``LoopGuard`` flags three patterns:
+
+* ``repeat``    — the same ``(tool, args)`` fired many times in a row;
+* ``ping_pong`` — two actions alternating A-B-A-B with no progress;
+* ``no_op``     — the observation (a screenshot/state digest) never changes.
+
+It complements a step/time budget (which can't tell a productive loop from a
+stuck one) and the offline trajectory evaluator. Pure standard library
+(``collections`` + ``hashlib``); deterministic; imports no ``PySide6``.
+"""
+import hashlib
+import json
+from collections import deque
+from dataclasses import dataclass
+from typing import Any, Deque, Optional, Tuple
+
+LEVEL_OK = "ok"
+LEVEL_WARN = "warn"
+LEVEL_CRITICAL = "critical"
+
+
+@dataclass(frozen=True)
+class LoopVerdict:
+    """The result of observing one step."""
+
+    pattern: Optional[str]   # None | "repeat" | "ping_pong" | "no_op"
+    level: str               # "ok" | "warn" | "critical"
+    count: int               # length of the detected run
+
+
+def _args_key(args: Any) -> str:
+    try:
+        return json.dumps(args, sort_keys=True, default=str)
+    except (TypeError, ValueError):
+        return repr(args)
+
+
+def digest_result(obj: Any) -> str:
+    """Return a stable short digest of a result/observation (e.g. a frame)."""
+    if isinstance(obj, (bytes, bytearray)):
+        data = bytes(obj)
+    else:
+        data = _args_key(obj).encode("utf-8")
+    return hashlib.sha256(data).hexdigest()[:16]
+
+
+class LoopGuard:
+    """Watches a stream of action triples and flags stuck-loop patterns."""
+
+    def __init__(self, *, warn: int = 8, critical: int = 15,
+                 window: int = 20) -> None:
+        """``warn``/``critical`` are run-length thresholds; ``window`` caps memory."""
+        self._warn = warn
+        self._critical = critical
+        self._events: Deque[Tuple[str, str]] = deque(maxlen=window)
+
+    def reset(self) -> None:
+        """Forget all observed steps."""
+        self._events.clear()
+
+    def observe(self, tool: str, args: Any = None,
+                result_digest: str = "") -> LoopVerdict:
+        """Record a step and return the strongest stuck-loop verdict."""
+        self._events.append((f"{tool}:{_args_key(args)}", result_digest))
+        pattern, count = self._classify()
+        return LoopVerdict(pattern, self._level(pattern, count), count)
+
+    def _classify(self) -> Tuple[Optional[str], int]:
+        repeat = self._trailing_repeat()
+        if repeat >= 2:
+            return "repeat", repeat
+        ping = self._trailing_ping_pong()
+        if ping >= 4:
+            return "ping_pong", ping
+        no_op = self._trailing_no_op()
+        if no_op >= 2:
+            return "no_op", no_op
+        return None, 0
+
+    def _trailing_repeat(self) -> int:
+        keys = [event[0] for event in self._events]
+        if not keys:
+            return 0
+        last = keys[-1]
+        count = 0
+        for key in reversed(keys):
+            if key != last:
+                break
+            count += 1
+        return count
+
+    def _trailing_ping_pong(self) -> int:
+        keys = [event[0] for event in self._events]
+        if len(keys) < 4 or keys[-1] == keys[-2]:
+            return 0
+        first, second = keys[-2], keys[-1]
+        count = 0
+        for index, key in enumerate(reversed(keys)):
+            expected = second if index % 2 == 0 else first
+            if key != expected:
+                break
+            count += 1
+        return count
+
+    def _trailing_no_op(self) -> int:
+        digests = [event[1] for event in self._events]
+        if not digests or not digests[-1]:
+            return 0
+        last = digests[-1]
+        count = 0
+        for digest in reversed(digests):
+            if digest != last:
+                break
+            count += 1
+        return count
+
+    def _level(self, pattern: Optional[str], count: int) -> str:
+        if pattern is None:
+            return LEVEL_OK
+        if count >= self._critical:
+            return LEVEL_CRITICAL
+        if count >= self._warn:
+            return LEVEL_WARN
+        return LEVEL_OK
+
+
+default_loop_guard = LoopGuard()