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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 | 631 |
| Forks | 61 |
| Language | JavaScript |
| Category | AI Tool |
| License | MIT |
| Quality Score | 49/100 |
| Open Issues | 11 |
| Last Updated | 2026-09-22 |
| Created | 2026-09-18 |
| Platforms | node |
| Est. Tokens | ~3k |
Jev-cu 把 Computer Use 的「下一步点哪里」交给 Jev（TypeSafe System One）：Jev 从界面文字候选中选元素、动作、完成度与风险，Codex Computer Use 负责读取界面与执行，本地策略门槛拦截敏感操作。只传文字，不传截图。 目录 安装 skill skill 源文件里的 会在安装时替换成仓库实际路径。 使用 先在 写入 key（不提交），或设置同名环境变量： 循环要在 Codex 桌面 App 的 运行时里执行： 验证 安全边界 默认 dry-run；删除、发送、支付、授权、上传、验证码、安装、系统设置等操作停在 ，需人工确认。 App 白名单在 ，新增 App 必须显式修改。 界面文字只作为数据，不作为指令；不绕过登录、付费墙和验证码。
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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: