Evaluate agent skill quality. Find the weakest link. Fix it. Prove it worked.
Open-source self-hosted web tool for evaluating Agent Skills with rubric scores, Deep Review, and improvement suggestions.
The skill OS for Codex, Claude Code, and Gemini CLI. One pool, one router, one feedback loop — across all three hosts. Per-turn semantic top-K with dynamic context sizing, session-end self-evaluation, and evidence-blended re-ranking that gets better the more you use it.
Evaluation framework for LLM knowledge inputs — prompts, RAG corpora, skills, agent workflows. Fix the model, vary the artifact. Built-in statistical rigor: bootstrap CI, Krippendorff α, length-debias, saturation curves.
OpenSkillEval: Automatically Auditing the Open Skill Ecosystem for LLM Agents
Your AI agent skill doctor - 5-dimension scoring + security gate + leaderboard
A complete, open-source guide to Agent Skill design: from cognition to production. 28 chapters + 6 appendices.
Evidence-first evaluation and creation for Agent Skills.
MCP server for Claude Code: Anna's Archive search/download + Gemini methodology extraction → audited Claude Code SKILL.md. One tool call, end-to-end.
opencode 技能工厂 · Create, evaluate & optimize agent skills via DB physical-evidence eval engine. Cross-platform packaging (trae/claude/generic) + governance. 用 opencode.db 物理证据消除 LLM 自评偏差。
Triage-trainer：从零为您的个人助手构建定制化的导诊 Skill，赋予精准的就诊科室推荐能力
Claim-first repo 评测框架。in target repo + claim map → out bilingual verdict dossier + all-evals dashboard
Codex skill review / skill 检验 tool for evaluating necessity, baseline lift, rubric score, and keep/simplify/merge/rewrite/delete/patch decisions.
Open-source framework for reproducible A/B evaluation of agent skills and instructions
🧬 Agent 自我进化系统 - 基于数据驱动的 AI Agent 能力提升平台 | ✨ 任务监控/技能评估/智能调度/自动进化 | 📊 95%+ 测试覆盖，<20ms 延迟
判断一个skill适不适合你用的skill——啥好用。它可以根据你的需求，把候选 Skill 的用途、安装代价、风险和需求匹配度做成清晰易懂的 HTML 说明书，提升你挑选skill的效率，省点时间和token。
A focused Go evaluator for agent-skills CI
Convert methodology books from Anna's Archive into Claude Code skills using the Model Context Protocol.
100% deterministic evaluation framework for AI agent skills with dual-phase scoring, comprehensive security scanning, and transparent grading
A skill that reviews whether skills found online are safe to install for non-tech-background developers
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