by besoeasy · MCP Server · ★ 132
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/besoeasy/open-skills ~/open-skillsTaken 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 | 132 |
| Forks | 32 |
| Category | MCP Server |
| License | MIT |
| Quality Score | 66/100 |
| Open Issues | 4 |
| Last Updated | 2026-09-04 |
| Created | 2026-02-13 |
| Platforms | browser, claude-code, mcp |
| Est. Tokens | ~18k |
Open Skills Battle-tested execution playbooks that give any AI agent the exact commands, APIs, and patterns it needs — cutting token usage by 95–98% and making local models as capable as GPT-4. The Problem AI agents waste tokens discovering what you already know: Cloud models (GPT-4, Claude) — 10–30 trial-and-error calls per task → $0.15–$0.25/task Local models (Llama, Mistral, Qwen) — often fail...
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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: