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 Ezeafk · MCP Server · ★ 97
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is awesome-agent-skills safe to install? View the security audit →
Awesome Agent Skills A curated list of reusable skills, workflows, and tool-backed capabilities for AI agents. Languages: English Русский This list focuses on reusable capabilities that help AI agents complete real tasks. It is not a prompt dump. A listed project should have a clear use case, reusable structure, installation or usage instructions, and enough context to explain inputs, outputs, and safety boundaries. Last reviewed: 2026-06-28 What Counts As A Skill For this list, a skill is a reusable capability package for an AI agent. It may include instructions, workflows, scripts, references, templates, MCP servers, connectors, local app automation, validation steps, or examples. Legend Evaluation Method Skills are scored before inclusion. Stars are a weak signal only;
| Stars | 97 |
| Forks | 35 |
| Category | MCP Server |
| License | MIT |
| Quality Score | 56.9070146991511/100 |
| Open Issues | 35 |
| Last Updated | 2026-08-01 |
| Created | 2026-06-25 |
| Platforms | claude-code, codex, mcp |
| Est. Tokens | ~13k |
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awesome-agent-skills is Curated reusable skills, workflows, and tool-backed capabilities for AI agents.. It is categorized as a MCP Server with 97 GitHub stars.
You can find installation instructions and usage details in the awesome-agent-skills GitHub repository at github.com/Ezeafk/awesome-agent-skills. The project has 97 stars and 35 forks, indicating an active community.
awesome-agent-skills is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to awesome-agent-skills on Agent Skills Hub include awesome-ai-agent-skills, awesome-ai-coding-techniques, agents. 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: