Agentic Awesome Skills vs wshobson/agents
Which should you use? A side-by-side look at what each one does, who it suits, what it costs, how hard it is to set up, and where each falls short.
Open source · MIT
A local catalog of 2,800+ reusable instruction files that helps coding agents pick and review skills.
Open source · MIT
A collection of plugins, agents, skills, and commands that run across several AI coding tools.
The short answer
Choose Agentic Awesome Skills if you need…
- Developers using Codex or Claude who want agent-chosen instructions for a project
- Teams that want to review an exact, saved list of skills before installing them
- People who want a local, inspectable workflow instead of a hosted service
- Users comfortable editing config files and running npm or CLI commands
Choose wshobson/agents if you need…
- Developers who already use one of the listed AI coding tools and want ready-made specialist agents
- Python or JavaScript/TypeScript developers looking for testing, packaging, or project setup guidance
- Teams wanting a shared set of review and security-scanning workflows across different tools
- People who want to install only individual skills without the full plugin set
Side-by-side
| Agentic Awesome Skills | wshobson/agents | |
|---|---|---|
| Type | Dev tool | Dev tool |
| Price | Free and open source | Free and open source |
| Licence | MIT | MIT |
| GitHub stars | 49k | 42.1k |
| Setup difficulty | Intermediate | Beginner |
| How you get it | Install with a package manager | Install with a package manager |
| Main language | Python | Python |
| Last code update | 4 days ago | 5 days ago |
What each one is
Agentic Awesome Skills
Agentic Awesome Skills is a library of installable SKILL.md playbooks, which are instruction files that AI coding agents such as Codex or Claude can read and follow. AAS Core is a local tool that lets the agent search the full catalog, record the skills it chooses, validate that selection, and preview a plan you can review before anything changes. According to the README, Core does not rank or recommend skills itself.
wshobson/agents
This project is a shared library of prompts-as-plugins for AI coding assistants. It contains 94 plugins with specialist agents, skills (reference guidance an agent loads when relevant), and commands (named workflows) covering areas like Python, JavaScript, code review, testing, infrastructure, and security. One Markdown source is adapted to Claude Code, OpenAI Codex CLI, Cursor, OpenCode, Antigravity CLI, GitHub Copilot, and Pi.
Best for
Agentic Awesome Skills
- Developers using Codex or Claude who want agent-chosen instructions for a project
- Teams that want to review an exact, saved list of skills before installing them
- People who want a local, inspectable workflow instead of a hosted service
- Users comfortable editing config files and running npm or CLI commands
wshobson/agents
- Developers who already use one of the listed AI coding tools and want ready-made specialist agents
- Python or JavaScript/TypeScript developers looking for testing, packaging, or project setup guidance
- Teams wanting a shared set of review and security-scanning workflows across different tools
- People who want to install only individual skills without the full plugin set
Strengths
Agentic Awesome Skills
- Covers the full catalog locally, so every listed skill can be searched and read
- Keeps a reviewable record of which skills were chosen and why, via manifests and plans
- Explicit dry-run and preview steps before changes are applied
wshobson/agents
- Covers seven coding tools from one shared source of components
- Large catalog: 94 plugins, 202 agents, 185 skills, and 105 commands according to the README
- Offers a skills-only install route that does not require the full plugin set
Not ideal for
Agentic Awesome Skills
- Non-technical users, since setup involves MCP configuration and terminal commands
- People who want the tool to recommend skills for them, because the README says Core does not rank or recommend
- Users who need apply or recovery features in production, since the README says these remain experimental and outside the supported preview
wshobson/agents
- People who do not use any supported AI coding tool, since the components only run inside those harnesses
- Anyone expecting the scores from the plugin-eval tool to prove a task will succeed, because the README says the LLM judge and Monte Carlo layers are experimental and not validated against human labels
- Users wanting a fully stable, versioned release, since the README lists no latest release
Trade-offs
Agentic Awesome Skills
- The README says apply and recovery are experimental, and it warns that validation does not certify semantic fit or safety to apply
- Setup depends on the Codex or Claude guides and on the README tracking main, so some features may need a later release than the one you install
- The skill count differs across the README and metadata (2,750+, 2,877+), so check the current catalog yourself
wshobson/agents
- The README notes that available components depend on the installation route and each harness's limits, so features differ by tool
- Some features (LLM judge, Monte Carlo evaluation) are experimental and may bill your Anthropic API account if ANTHROPIC_API_KEY is set
- Pi agents need a separate subagent extension, and the Codex native and generated routes behave differently
Getting started
Agentic Awesome Skills
Configure the local MCP for Codex (preview; returns an approval digest)
npm exec --yes --ignore-scripts --package=agentic-awesome-skills@20.2.0 -- aas mcp configure \
--host codex \
--scope user \
--config /absolute/path/to/codex/config.toml \
--cache-root /absolute/path/to/aas-cachePreview a direct install of selected skills
npm exec --yes --ignore-scripts --package=agentic-awesome-skills@20.2.0 -- \
agentic-awesome-skills --release 20.2.0 --path .agents/skills \
--skills brainstorming,systematic-debugging --dry-runwshobson/agents
Claude Code: register marketplace (run inside Claude Code)
/plugin marketplace add wshobson/agentsClaude Code: install Python plugin (run inside Claude Code)
/plugin install python-development@claude-code-workflowsFrequently asked questions
What is the difference between Agentic Awesome Skills and wshobson/agents?
Agentic Awesome Skills: A local catalog of 2,800+ reusable instruction files that helps coding agents pick and review skills. wshobson/agents: A collection of plugins, agents, skills, and commands that run across several AI coding tools. Agentic Awesome Skills suits developers using codex or claude who want agent-chosen instructions for a project, while wshobson/agents suits developers who already use one of the listed ai coding tools and want ready-made specialist agents.
Are Agentic Awesome Skills and wshobson/agents free?
Agentic Awesome Skills: Free and open source. wshobson/agents: Free and open source.
Which is easier to set up, Agentic Awesome Skills or wshobson/agents?
wshobson/agents is easier to get started with (rated beginner); Agentic Awesome Skills is rated intermediate and usually needs more setup.
Is Agentic Awesome Skills or wshobson/agents more popular?
Agentic Awesome Skills has more GitHub stars (49k) than wshobson/agents (42.1k). Popularity isn't the same as fit — check which one matches your use case above.
What are other alternatives to Agentic Awesome Skills and wshobson/agents?
Other options people compare them with include ECC, Trail-code, codebase-memory-mcp, opencodex, Our Free Model.
Keep comparing
Built from our catalogue entries for both products: open-source details come from each project's README (AI-assisted, refreshed weekly) and GitHub data; AI-tool details are editorial. Spotted something wrong? Let us know from either product's page.