awesome-llm-skills: A curated list of awesome LLM and AI Agent Skills, resources and tools for customising AI Agent workflows

by Prat011 · Claude Skill · ★ 1.7k

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 65/100

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.

anthropicawesome-listawesome-listsclaude-codeclaude-skillsclaude-skills-creatorcodexcodex-cligeminigemini-cli

Quick Facts

Stars1,749
Forks303
LanguagePython
CategoryClaude Skill
Quality Score65/100
Open Issues163
Last Updated2026-07-14
Created2025-10-22
Platformsclaude-code, cli, codex, gemini, python
Est. Tokens~19k

About awesome-llm-skills

Awesome LLM Skills A curated list of awesome LLM Skills, resources, and tools for customizing AI workflows on tools like Claude Code, Codex, Gemini CLI, Qwen Code, OpenCode etc. Contents What Are LLM Skills? Quick Start Skills Platforms Claude Code (Anthropic) Claude Desktop (Anthropic) Codex CLI (OpenAI) Gemini CLI (Google) OpenCode (Open-source CLI) Qwen Code (Alibaba) Contributing Quick...

Compatible Skills

These tools work well together with awesome-llm-skills for enhanced workflows:

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How this security grade is produced

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:

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