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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 | 336 |
| Forks | 84 |
| Language | Python |
| Category | AI Tool |
| Quality Score | 53/100 |
| Open Issues | 5 |
| Last Updated | 2026-02-10 |
| Created | 2026-02-09 |
| Platforms | claude-code, python |
| Est. Tokens | ~2k |
Claude Code Stop Hook — 任务完成自动回调 当 Claude Code（含 Agent Teams）完成任务后，自动： 将结果写入 JSON 文件 发送 聊天软件 通知到指定群组 写入 pending-wake 文件供 AGI 主会话读取 架构 文件说明 使用方法 基础任务 Agent Teams 任务 参数 聊天软件 群组 ID（结果自动发送）
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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: