by PipiHi0926 · Agent Tool · ★ 96
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
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 | 96 |
| Forks | 11 |
| Language | Jupyter Notebook |
| Category | Agent Tool |
| Quality Score | 48/100 |
| Last Updated | 2024-09-08 |
| Created | 2024-08-09 |
| Est. Tokens | ~4962k |
🤖 大型語言模型入門教學 中文分享整理 💻 ✍️ 作者: 鄭永誠 • ✉️ 信箱 • 🧑🤝🧑 合作夥伴: 紫式大數據決策 • 👫 我的朋朋: Morale AI 內容簡介: 🍻 LLM基礎改念: 本讀書會將整理一些LLM的基礎需求知識，但github上放的是實作資源為主不會講述太多，有興趣請再密我 🛠️ LLM相關工具: 以下內容全基於python實踐，同時會分享相關資源、套件、開源API...
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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: