by dualface · Agent Tool · ★ 191
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npx skills add dualface/ste-zh -g
npx skills add dualface/ste-zhTaken 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 | 191 |
| Forks | 14 |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 58/100 |
| Last Updated | 2026-10-11 |
| Created | 2026-10-05 |
| Est. Tokens | ~3k |
ste-zh：简化技术中文规范 一个面向 AI Agent 的任务汇报规范 skill。借鉴航空与工业界严谨的 ASD-STE100（Simplified Technical English，简化技术英语）原则，约束 Agent 用清晰、严密且无歧义的中文汇报工作结果。 Agent 的日常汇报常常过程冗长、推测含糊，或者漏掉关键的验证证据。开启 后，Agent 将遵循受控中文规范进行汇报：结论先行、实证说话、状态固定、一目了然。 💡 本 skill 仅规范 Agent 向用户汇报与讨论时的表达方式，绝不影响项目代码、注释、Commit 信息及生成的文件内容。 为什么需要 ste-zh？ 同一个 Bug 修复任务，常见汇报与规范化汇报的差异如下： 常见 AI 汇报（冗长、推测、不报实证）： 「好的，我先看了一下登录相关的代码，发现问题应该是出在 token...
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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: