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A lightweight, modular Java application framework for web and CLI development, designed for AI integration and plugin-based architecture. Enabling developers to create robust solutions with ease for building efficient and scalable applications.
Open-source alternative to TypeSafe's Jev: a System One style model layer that gives typed, calibrated decisions from any open-weights LLM in one forward pass (HF + vLLM), with honest benchmarks
Route every coding task to the best AI agent on your machine — Claude Code, Codex, Cursor, Gemini CLI, Aider, OpenCode. Installs as a Claude Code plugin, Gemini extension, or Agent Skill.
Does a TypeSafe Jev rerank beat embedding search? Graded relevance eval (9,831 pairs, 164 zh/en queries) over the Agent Skills Hub catalog, with the judge-circularity bias measured.
Cross-domain check on MIND news: a zero-shot Jev headline prior is worth ~500 labelled articles, adds +0.069 ρ as features, and lifts a Thompson-sampling cold start by 25%.
Screens an AI agent's tool calls before they run and tool results before the agent reads them. An MCP proxy plus a hooks adapter for a client's built-in tools.
Can a TypeSafe Jev prior read from a README on day one predict which new agent-skill repos gain stars? Zero-shot Jev ≈ a text model trained on ~150 labels; best used as a feature. Prospective test running.
Can a Jev-labelled GitHub issue stream catch a broken release before the fix? No at daily cadence (null, n=7). Per issue, Jev matches triage labels far better than keywords or sentiment.
Does a Jev-labelled support-tweet stream spike before a brand admits an outage? At equal false alarms it catches 17 vs 10 incidents (volume), ~4h ahead; a good keyword list is almost as good.