by FerryCorleone · AI Tool · ★ 311
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
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 | 311 |
| Forks | 28 |
| Language | TypeScript |
| Category | AI Tool |
| License | MIT |
| Quality Score | 59/100 |
| Open Issues | 2 |
| Last Updated | 2026-10-17 |
| Created | 2026-09-20 |
| Platforms | node |
| Est. Tokens | ~11k |
Crush 好感监控器 一个用 Jev 分析你和 Crush 或对象聊天的小工具。帮你读懂一点对方的情绪和想法，也看看自己的回复哪里没表达好、可以怎么调整。 不过，AI 不知道你们现实中怎么相处，也不了解聊天之外的故事。分析结果就当图一乐、做个参考。怎么理解对方、怎么表达自己，最后还是得靠自己的感受和真诚。 特点 微信风格界面：还原聊天气泡，分析结果直接显示在消息下方。 情绪与意图：每句两行标签，从 12 类情绪、35 类意图中分别展示概率最高的三项。 好感度与回复评级：顶部显示好感信号评分，自己的回复按 SSS 到 D 分档，并给出下一步建议。 连续分析：继续粘贴新记录即可更新，支持识别重复片段。 本机运行，自带 Key：无需服务器，使用自己的 TypeSafe 账号和 API 额度。 为什么用 Jev Jev 是 TypeSafe...
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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: