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None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 716 |
| Forks | 205 |
| Language | Python |
| Category | AI Tool |
| Quality Score | 58/100 |
| Open Issues | 1 |
| Last Updated | 2026-04-25 |
| Created | 2026-02-01 |
| Platforms | python |
| Est. Tokens | ~15k |
本地知识库检索 Skill 演示项目 ⚠️ 项目已归档 本仓库已停止维护，不再更新。作者后续所有的开源 Skills 将统一发布至 garden-skills 仓库，欢迎 Star 关注，获取最新动态 ✨ 一个专为本地知识库智能检索设计的 AI Skill 演示仓库，展示如何通过分层索引和渐进式检索实现高效的多格式文件问答系统。 📖 项目简介 本项目是一个完整的本地知识库检索解决方案演示，包含： 核心 Skill： - 智能知识库检索助手 示例知识库： - 包含多领域、多格式的真实数据样本 最佳实践：遵循 Skill 编写规范，展示如何构建高效的 RAG（检索增强生成）系统 核心特性 ✅ 多格式支持 - Markdown、PDF、Excel 等多种文件格式 ✅ 分层索引 - 通过 实现智能目录导航 ✅ 渐进式检索 - 避免全文加载，按需局部读取，节省 token ✅ 强制学习机制 -...
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: