by mrdainami · Codex Skill · ★ 255
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/mrdainami/nami.gitTaken 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 | 255 |
| Forks | 60 |
| Language | JavaScript |
| Category | Codex Skill |
| License | Apache-2.0 |
| Quality Score | 60/100 |
| Open Issues | 4 |
| Last Updated | 2026-09-22 |
| Created | 2026-08-09 |
| Platforms | claude-code, codex, gemini, node |
| Est. Tokens | ~14k |
Nami Put the world's best AI agents to work. One workspace for all of them. Say what you need in plain English and watch it get done. ↓ Download for Mac macOS 13 or later · free and open source On an older Intel Mac? Get the Intel build. Nami is free and open source under the Apache License 2.0. It is built by one person so that anyone — not just engineers — can put AI agents to work.
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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: