by zilliztech · Codex Skill · ★ 158
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Featured in: Knowledge Base & RAG
npx skills add zilliztech/mfs --all -g
npx skills add zilliztech/mfs -a claude-code -a codex -gTaken from the project's README on GitHub.
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.
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 | 158 |
| Forks | 18 |
| Language | Python |
| Category | Codex Skill |
| License | Apache-2.0 |
| Quality Score | 62/100 |
| Open Issues | 4 |
| Last Updated | 2026-07-31 |
| Created | 2026-04-20 |
| Platforms | claude-code, codex, python |
| Est. Tokens | ~22k |
MFS — Multi-source File-like Search A context harness for AI agents — and for building them: one unified workspace over your code, memory, skills, docs, messages, and every data source. <img src="https://img.shields.io/badge/Discord-chat-72
These tools work well together with mfs for enhanced workflows:
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Explore other popular codex skill tools:
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: