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ManzoliW/effect-harness-agent

An LLM-native cognitive harness for React + Effect TypeScript projects

Python MIT GitHub ↗
★ 0
stars
100
AI関連スコア
50
個人開発度
2
AIツール痕跡

SUMMARY AI要約 by gpt-5-mini

Effect Harness Agent is an agent-driven engineering framework for TypeScript/Effect projects — an LLM-native, machine-to-machine protocol (not a human-facing framework). It turns natural-language intent into structured, executable tasks for autonomous LLM agents while enforcing engineering discipline. Who uses it: teams or systems that integrate LLM agents to design, implement, test, and maintain TypeScript/Effect code with predictable governance and cost. Key features: - Intent Gateway routing and execution profiles (@patch/@standard/@learn) - 6‑phase Lifecycle State Machine with human-in-the-loop approval and validation gates - Knowledge Graph (LLM Wiki) and budgeted navigation to avoid context bloat - Contract-first OpenSpec and explore_report outputs before coding - Skills Matrix (specialized agent capabilities) and self-correcting guard hooks - Token-cost model and shortcuts to control cost and prevent runaway searches

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OpenAI Codex (AGENTS.md) AGENTS.md Claude Code CLAUDE.md

DETECTED 検出されたAIスタック

このRepoのdescription / GitHub topics / READMEのAI要約に出現したAI関連キーワードをカテゴリ別に表示。各バッジは該当カテゴリの詳細ランキングへリンクします。

🤖 LLMモデル (1)
Claude
🌐 Web/アプリフレームワーク (1)
React

GitHub Topics

#agent-framework #claude-code #effect-ts #llm-harness #typescript

使用言語(バイト数比)

Python
77.9%
TypeScript
22.1%

オーナー情報

アカウント
ManzoliW
タイプ
User
フォロワー
95

日付

GitHub作成日 2026-05-09
最終Push 2026-05-09
当サイト初検出 2026-05-09
最終取得 2026-05-09 18:12

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