by nizos · Claude Skill · ★ 233
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Featured in: Agent Governance
npm install -D @nizos/probityTaken 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 | 233 |
| Forks | 30 |
| Language | TypeScript |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 67/100 |
| Open Issues | 32 |
| Last Updated | 2026-10-12 |
| Created | 2026-04-18 |
| Platforms | claude-code, cli, codex, node |
| Est. Tokens | ~15k |
Probity Probity blocks AI coding agents from breaking your rules — adding production code without a failing test, disabling lint rules instead of fixing the issue, reaching for when something more targeted would do. It works through your agent's existing hook system.
These tools work well together with probity for enhanced workflows:
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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: