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 Chat2AnyLLM · Claude Skill · ★ 149
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is awesome-claude-skills safe to install? View the security audit →
Awesome Claude Skills A curated list of awesome Claude Code skills to enhance your Claude Code experience. Total Skills: 9517 Last updated: 2026-04-26 15:33 UTC 📋 See full skill list - Convenient for searching through all skills without size limits. Contents Creating Skills Contributing Resources Join the Community License Skills by Domain: Backend Development [DevOps & Infrastructure](./
| Stars | 149 |
| Forks | 40 |
| Language | Python |
| Category | Claude Skill |
| Quality Score | 58.4803182240685/100 |
| Open Issues | 7 |
| Last Updated | 2026-09-23 |
| Created | 2025-12-23 |
| Platforms | claude-code, python |
| Est. Tokens | ~14k |
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awesome-claude-skills is A curated list of awesome claude skills. It is categorized as a Claude Skill with 149 GitHub stars.
awesome-claude-skills is primarily written in Python. It covers topics such as claude, claude-code, skills.
You can find installation instructions and usage details in the awesome-claude-skills GitHub repository at github.com/Chat2AnyLLM/awesome-claude-skills. The project has 149 stars and 40 forks, indicating an active community.
The top alternatives to awesome-claude-skills on Agent Skills Hub include mcpick, cclsp, claude-talk-to-figma-mcp. 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: