by onllm-dev · Codex Skill · ★ 758
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
brew install onllm-dev/tap/onwatch
git clone https://github.com/onllm-dev/onwatch.git && cd onwatchTaken from the project's README on GitHub. Check the security audit before running it.
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 | 758 |
| Forks | 66 |
| Language | Go |
| Category | Codex Skill |
| License | GPL-3.0 |
| Quality Score | 69/100 |
| Open Issues | 7 |
| Last Updated | 2026-10-23 |
| Created | 2026-02-06 |
| Platforms | claude-code, codex, go |
| Est. Tokens | ~24k |
onWatch Free, open-source AI API quota monitoring for developers. Track usage across Synthetic, Z.ai, Anthropic, Codex, GitHub Copilot, MiniMax, Gemini CLI, Cursor, and Antigravity in one place. See history, get alerts, and open a local web dashboard before you hit throttling or run over budget.
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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: