No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by LeoYeAI · Codex Skill · ★ 2.1k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is openclaw-master-skills safe to install? View the security audit →
🧠 OpenClaw Master Skills Languages: English · 中文 · Français · Deutsch · Русский · 日本語 · Italiano · Español 🤖 Powered by MyClaw.ai MyClaw.ai is an AI personal assistant platform that gives every user a fully-featured AI agent running on a dedicated server. OpenClaw Master Skills is our curated, weekly-updated collection of the best skills from across the ecosystem — hand-picked to help your AI agent do more. 🌐 Try MyClaw.ai: https://myclaw.ai 🚀 How to Install 📦 Skill Index (339 skills) 🤖 AI & LLM Tools (34) | [](skills/academic-deep-resear
| Stars | 2,110 |
| Forks | 319 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 62.9166634460626/100 |
| Open Issues | 34 |
| Last Updated | 2026-07-20 |
| Created | 2026-03-02 |
| Platforms | python |
| Est. Tokens | ~25k |
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openclaw-master-skills is 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. It is categorized as a Codex Skill with 2.1k GitHub stars.
openclaw-master-skills is primarily written in Python. It covers topics such as agentskills, ai-agent, curated.
You can find installation instructions and usage details in the openclaw-master-skills GitHub repository at github.com/LeoYeAI/openclaw-master-skills. The project has 2.1k stars and 319 forks, indicating an active community.
openclaw-master-skills is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to openclaw-master-skills on Agent Skills Hub include unbrowse, n8n-claw, awesome-agent-skills. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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: