by devswha · Codex Skill · ★ 385
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
Featured in: Humanizer & Anti-Slop Skills
npx patina-cli doctor
npx patina-cli --lang en input.txtTaken from the project's README on GitHub.
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.
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.
One of 23 tools we ran end to end on the same task for our Humanizer & Anti-Slop Skills page (2026-10-07).
Result: Reads human 2/5 · Changed wording, not structure · kept every fact · 8.2 min
| Stars | 385 |
| Forks | 37 |
| Language | JavaScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 69/100 |
| Open Issues | 4 |
| Last Updated | 2026-09-29 |
| Created | 2026-02-24 |
| Platforms | claude-code, cli, codex, node |
| Est. Tokens | ~15k |
patina Strip the AI packaging. Keep the meaning. 한국어 · 中文 · 日本語 · English Try the browser audit — no install patina is a deterministic, pattern-based humanizer for Korean, English, Chinese, and Japanese. It finds AI-sounding phrasing and rewrites it without changing the claim, numbers, polarity
These tools work well together with patina for enhanced workflows:
Looking for a patina alternative? If you're comparing patina with other codex skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
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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: