awesome-claude-code vs awesome-agent-skills

Directories for Claude Code and AI agent resources compared

awesome-claude-code and awesome-agent-skills are curated directories that point developers to tools and resources for coding agents. awesome-claude-code focuses on Claude Code and related additions, while awesome-agent-skills spans multiple agent platforms and ecosystems.

awesome-claude-codeawesome-agent-skills
Languagenot specified.TypeScript
LicenseCC0-1.0.CC0-1.0
Stars523.20
Forks620.61
Last analyzedOct 3, 2026Oct 3, 2026

Key differences

  • awesome-claude-code organizes resources around Claude Code, including plugins, skills, IDE integrations, SDKs, and alternatives; awesome-agent-skills groups resources across ecosystems such as MCP, Cursor, Windsurf, Gemini CLI, and Copilot.
  • awesome-claude-code includes official Anthropic resources and community projects; awesome-agent-skills also includes directories, marketplaces, and individual projects.
  • awesome-agent-skills describes automated data sources and sync methods, with update frequency varying by source; awesome-claude-code records star counts as snapshots from when entries were added.
  • awesome-agent-skills lists TypeScript as its language; no language is specified for awesome-claude-code.
  • The provided snapshots report 523 stars and 620 forks for awesome-claude-code, compared with 20 stars and 61 forks for awesome-agent-skills.
  • Both repositories use the CC0-1.0 license and are not archived; the snapshots report 589 open issues for awesome-claude-code and 69 for awesome-agent-skills.

Choose awesome-claude-code if you…

  • need Claude Code-specific skills, plugins, integrations, or utilities in one directory.
  • want to explore Claude Code learning resources, SDKs, or alternatives.
  • are comparing Claude Code workflow additions, including options that may also work with other coding agents.
Read the awesome-claude-code analysis →

Choose awesome-agent-skills if you…

  • want to compare skills and tools across multiple AI coding-agent ecosystems.
  • need to browse MCP resources, platform-specific rules, or tools for frameworks such as LangChain, CrewAI, or n8n.
  • want a directory that describes its data sources and sync methods.
Read the awesome-agent-skills analysis →

Compare the numbers side by side, or add more projects

This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.