by decodingai-magazine · Agent Tool · ★ 3.1k
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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 | 3,113 |
| Forks | 526 |
| Language | Jupyter Notebook |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 60/100 |
| Open Issues | 6 |
| Last Updated | 2026-04-06 |
| Created | 2024-12-30 |
| Est. Tokens | ~19k |
Building Your Second Brain AI Assistant Using Agents, LLMs and RAG Learn how to access the collective wisdom of your own mind Open-source course by Decoding AI in collaboration with MongoDB, Comet, Opik, Unsloth and ZenML. 📖 About This Course This course is part of Decoding AI's open-source series, teaching you how to build production-ready GenAI systems using LLMs, RAG, agents and LLMOps.
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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: