by study8677 · Codex Skill · ★ 64
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 | 64 |
| Forks | 7 |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 56/100 |
| Open Issues | 1 |
| Last Updated | 2026-07-10 |
| Created | 2026-05-24 |
| Platforms | claude-code, codex |
| Est. Tokens | ~10k |
Architecture Copilot · 架构副驾 🧭 一个给 Claude Code / Cursor / OpenAI Codex 用的「架构共创」skill。 在你写第一行代码前,它用持续的深度提问陪你把系统架构想清楚——不是替你决定,而是帮你看清每个选择背后的取舍。 English · 简体中文 为什么需要它 AI 已经能替你写绝大部分代码。但有件事它不会主动替你做,而它恰恰是项目成败的关键: 在动手之前,先想清楚这个系统该长什么样。 大多数 AI 编程助手的默认行为是「你说要什么,我立刻开始写」。于是你常常在没想清楚边界、规模、一致性、取舍的情况下,就被它带着冲进了实现细节——等架构的坑暴露出来,已经是几个月后、推倒重来的时候了。 架构副驾反其道而行:它把 AI...
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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: