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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 | 113 |
| Forks | 14 |
| Language | Python |
| Category | AI Tool |
| License | CC0-1.0 |
| Quality Score | 72/100 |
| Last Updated | 2026-10-09 |
| Created | 2026-08-04 |
| Platforms | python |
| Est. Tokens | ~14k |
Torvalds Skill Distills Linus Torvalds' code-review methodology from his LKML emails into a reusable, language-agnostic Skill (and Soul) from various LLMs. Built from 38,293 real review moves extracted from 31,397 of his emails (2002–2026) on the Linux kernel mailing list, plus 67 interview transcripts. Validation: SmallChat Comparison The skill was validated on antirez/smallchat (706 LOC, C).
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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: