by harshaneel · Claude Skill · ★ 491
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git clone https://github.com/harshaneel/humanize.git
Taken 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 3/5 · Changed wording, not structure · removed 1 AI-leaning structure feature · kept every fact · 0.9 min
| Stars | 491 |
| Forks | 49 |
| Language | HTML |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 72/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-22 |
| Created | 2026-05-26 |
| Platforms | claude-code, cli, codex |
| Est. Tokens | ~25k |
humanize LLM-agnostic skills for static AI text humanization and detection. Grounded in 50+ peer-reviewed sources through April 2026. Works in any LLM agent: Claude Code, Codex CLI, ChatGPT, Gemini, Cursor, Aider, OpenCode, Continue, Copilot. The install paths differ; the skill content is identical.
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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: