by ai-zixun · Codex Skill · ★ 180
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npx skills add ai-zixun/humanizer-zh
npx skills add ai-zixun/humanizer-zh -gTaken 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 | 180 |
| Forks | 14 |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 58/100 |
| Last Updated | 2026-05-22 |
| Created | 2026-03-15 |
| Platforms | claude-code, codex |
| Est. Tokens | ~11k |
humanizer-zh 中文 | English 是一个兼容 Codex、Claude Code 和 OpenClaw 的中文去 AI 味技能。它用于重写、润色或审阅中文博客、评论、产品分析、newsletter、书稿章节等长文本，让文字更像中文母语者写出来的，而不是翻译腔、模型拼接稿或营销通稿。 这个仓库采用「单目录即技能包」结构：仓库根目录本身就是技能目录，通过 skills.sh 生态的 命令行一键安装到各类代理。 当前版本： 适用场景 中文博客、专栏、社论、评论稿的去 AI 味改写 中文产品分析、行业观察、长邮件、newsletter 的自然化润色 中译中修订，重点清理翻译腔、机械对照句、空泛大词和口号式收束 需要解释「这段中文为什么像 AI 写的」并给出修改前后示例 能力范围 识别并改写翻译腔、结构腔、排版腔和判断腔...
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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: