Free AI Skills Directory
Discover public SKILL.md files for Claude Code, Codex, and agent workflows. Browse by category, compare GitHub signals, and open detailed skill pages with source links and previews.
Indexed skills
144
Curated from GitHub code search with repo-level stats and category inference.
Visible results
144
Category hubs
11
Platform hubs
5
Frontend Skills
Discover SKILL.md files for UI work, design systems, React workflows, CSS, and browser-facing product tasks.
Backend Skills
Find SKILL.md files for APIs, data pipelines, servers, database work, and production backend implementation.
Testing Skills
Browse SKILL.md files for test planning, unit tests, integration tests, browser tests, and QA-oriented workflows.
Debugging Skills
Explore SKILL.md files that help agents debug errors, isolate regressions, reproduce issues, and review failing systems.
DevOps Skills
Find SKILL.md files for CI, deployment, infrastructure, automation, logs, containers, and operational workflows.
Security Skills
Browse SKILL.md files for secure coding, audit routines, secrets handling, access review, and safety-minded implementation.
Documentation Skills
Find SKILL.md files for writing docs, README maintenance, changelogs, onboarding content, and reference materials.
Productivity Skills
Explore SKILL.md files that help agents automate repeated workflows, planning, summarization, and day-to-day developer operations.
Integration Skills
Find SKILL.md files for external APIs, SaaS products, messaging tools, and connected platform workflows.
AI Development Skills
Discover SKILL.md files for model APIs, prompt workflows, embeddings, transcription, generation, and agent building.
Utility Skills
Browse practical SKILL.md files for command-line helpers, file operations, device control, search, and general-purpose automation.
Claude Code Skills
Browse SKILL.md files written for Claude Code workflows, conventions, triggers, and installation paths.
OpenClaw Skills
Explore SKILL.md files connected to the OpenClaw ecosystem and repos that mirror or extend Claude-style skills.
Cursor Skills
Browse skill-style instruction files and workflows relevant to Cursor and Cursor-adjacent agent usage.
Gemini CLI Skills
Discover SKILL.md files and workflow instructions tied to Gemini CLI or Gemini-adjacent agent tooling.
Generic Skills
Browse cross-platform SKILL.md files that appear portable across multiple agent ecosystems.
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Showing 1-24 of 144 skills
Page 1 of 6
architecture
nativewind/nativewind
The utility-first workflow you love from Tailwind CSS in your React Native applications.
pr
TypedDevs/bashunit
A simple yet powerfull testing library for bash scripts.
pr
alamenai/terrae
Composable and animated components that replace imperative layers with simple props. The perfect companion for shadcn/ui.
skill
blacktop/mcp-tts
MCP Server for Text to Speech
uiux
dlupiak/claude-session-dashboard
Claude Code Session Dashboard — local observability for ~/.claude sessions
pr
corv89/shannot
Human-in-the-loop execution for LLM agents
wdk
tetherto/wdk-docs
Official WDK docs found at docs.wallet.tether.io.
skills
drexed/cmdx
Framework for building maintainable business processes
skills
erikvullings/mithril-ui-form
Convert a (JSON) object to a dynamic (materialize-css) form.
pironman5-skill
sunfounder/pironman5
Code for Raspberry Pi 5 case (Pironman5)
skills
w3c/web-performance
W3C Web Performance Working Group repo
superbuild
asteroid-belt/skulto
Offline and security-first tool for syncing and managing agent skills
skill
ecto/vcad
BRep CAD kernel in Rust (and WASM)
skill
maquina-app/maquina_components
Modern UI components for Ruby on Rails, powered by TailwindCSS and Stimulus
skill
tmonk/mcp-stata
A lightweight Model Context Protocol (MCP) server for Stata. Execute commands, inspect data, retrieve stored results (r()/e()), and view graphs in your chat interface. Built for economists who want to integrate LLM assistance into their Stata workflow.
pd
majiayu000/claude-skill-registry
The most comprehensive Claude Code skills registry | Web Search: https://skills-registry-web.vercel.app
skill
redf0x1/camofox-mcp
Anti-detection browser MCP server for AI agents — navigate, interact, and automate the web without getting blocked
textum
snakeying/Textum
Structured workflow that stops AI from forgetting your requirements. 4 phases with validation gates. Not smarter AI, just controllable process. Weave ideas into code that actually works.
skill
abra5umente/api-proxy
a small python container that lets you proxy requests from claude's cloud container through your home network
nanobanana
skorfmann/nanobanana
Lightweight CLI for AI image generation using Google Gemini API. Text-to-image, image editing, multi-image composition. Perfect for coding agents like Claude Code.
skill
Aryanpanwar10005/seo-geo-optimizer
Universal SEO & GEO skill for AI IDEs — Google, Bing, AI Overviews, Bing Copilot, ChatGPT, Perplexity. Works with Cursor, Windsurf, GitHub Copilot, Replit, Lovable, Bolt, and any AI assistant.
skill
AI-Coding-Shield/ai-coding-shield
Security auditing tool for AI development workflows, rules, skills, and MCPs.
skills
scherhak/uplinkr
CLI-first monitoring for Laravel. Monitor websites and APIs with file-based JSON storage, Artisan commands, and scheduler integration.
session-pack
ten-builder/ten-builder
AI로 10배 빠르게 빌드하는 방법, 직접 써보고 검증한 AI 실전 노하우
More Intel Tools
Why a SKILL.md directory matters
The fast growth of AI coding assistants has created a new problem: discovery. More developers now know that aSKILL.md file can shape how an agent works, but finding good ones is still awkward. Most existing indexes are either raw GitHub scrapers, inconsistent mirrors, or flat lists with very little context. That makes it hard to understand what a skill actually does, whether the source repo is maintained, and whether the workflow is specific enough to be useful.
This directory is designed to solve that discovery problem in a more practical way. Instead of pretending to be a perfect marketplace of every skill ever published, it focuses on a cleaner indexed subset backed by GitHub search and repo metadata. That means the star counts, update timestamps, repo ownership, and source links come from the place developers already trust. It also means every skill page can be enriched with category context, related skills, and a direct preview of the underlying file instead of just echoing a name and a link.
How to use the directory well
The best way to use a skills directory is not to install everything that looks interesting. Start by searching for the exact workflow you want to improve: frontend polish, debugging, SEO audits, testing, integrations, or prompt-driven AI development. Open the detail page, inspect the repo signals, and read the raw preview of the skill file. If the scope is too broad or the instructions are vague, skip it. The strongest skills are usually narrow, opinionated, and realistic about when they should be used.
What makes a good SKILL.md
A useful SKILL.md file usually answers four questions quickly: what task it helps with, which tools or libraries it expects, which mistakes to avoid, and what good output looks like. Great skills often encode lessons a team learned the hard way. That makes them valuable because they reduce prompt repetition and give the agent a more reliable path through a class of work that would otherwise be inconsistent.
Benefits of browsing skills by category
Category hubs matter for two reasons. First, they make the directory easier to use. If you know you want frontend, backend, testing, or AI-development workflows, it is much faster to browse a focused subset than to search a flat list and hope the descriptions are enough. Second, they create stronger information architecture for search engines. People rarely search for generic phrases like free skills directory alone. They search for frontend skills, debugging skills, Next.js skills, or Claude Code skills for SEO. Category pages let the directory compete for those more specific intents.
This is also why the skill pages themselves need more than a few metadata fields. To rank well and to be genuinely useful, they need context: what the skill is for, why someone would use it, how to evaluate it, what source repo it comes from, and which related skills might solve adjacent problems. That approach turns the directory into something closer to a curated knowledge base than a simple scraper output.
What to check before you install a skill
- Look at the source repo and make sure the skill comes from a project that appears maintained and intentional.
- Check the update date and stars, but do not treat popularity alone as proof of quality.
- Read the preview and confirm the skill is specific enough to guide behavior clearly.
- Prefer skills that name the tools, frameworks, or environments they are written for.
- Test the skill on a small task first so you can judge whether it improves output instead of adding noise.
Why this directory is GitHub-first
Some third-party skill indexes are useful for inspiration, but they can also become inconsistent quickly. Repo counts, popularity signals, or normalized metadata may drift away from the source of truth. A GitHub-first directory avoids a lot of that confusion. It lets us use the GitHub Search API for discovery, repo endpoints for real maintenance signals, and raw file URLs for direct previews of the actual SKILL.md content. That gives you cleaner data, more transparent sourcing, and a better foundation for SEO pages that stay anchored to real repositories instead of abstract entries.
The goal is not to be exhaustive at any cost. The goal is to make skills easier to understand, easier to compare, and easier to discover through search. If a user lands on a specific skill page from Google, that page should explain the skill in plain language, show why it is relevant, and help the user decide whether it is worth trying. That is the standard this directory is built around.