by petergyang · Codex Skill · ★ 1.3k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
npx -y human-review setup --globalTaken from the project's README on GitHub. Check the security audit before running it.
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 | 1,267 |
| Forks | 102 |
| Language | JavaScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 70/100 |
| Open Issues | 29 |
| Last Updated | 2026-09-17 |
| Created | 2026-07-27 |
| Platforms | claude-code, cli, codex, node |
| Est. Tokens | ~13k |
Human Review Edit HTML and Markdown files directly, leave comments like a Google Doc, and send all your feedback to your AI agent at once. Read the full launch post https://github.com/user-attachments/assets/7cab09c9-eaa0-4e8b-984d-2925e810b5c2 Problem Giving AI feedback on files in chat is painful. Sometimes you want to change one sentence yourself.
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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: