Explore AI Agent Skills & Claude Prompts
Discover open-source agent skills for Claude Code, Codex, ChatGPT, and any tool that uses SKILL.md.
Enter through keywords, occupations, creators, and GitHub sources to see what kinds of skills are emerging across domains.
Use the same catalog through the API
Connect 381,784 public skills to your own search, analytics, or agent workflow with the REST API.
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apprun-skills
by yysunEnd-to-end guidance for AppRun apps in TypeScript using MVU including component patterns, event handling, state management (including async generators), routing/navigation with params and guards, and testing with vitest. Use when designing or reviewing AppRun components, wiring routes, managing state flows, or writing AppRun tests.
git-wiki
by yysunBuild and maintain local code-project wikis under .wiki or language-specific wiki roots such as .wiki-cn and .wiki-fr. Use this skill whenever the user mentions "wiki", "ingest", "refresh wiki", "update wiki", "lint wiki", "check wiki", "document the codebase", "export wiki", "bundle wiki", "archive wiki", or asks a question that can be answered from wiki pages. Also use it when the user asks how something works in the project and a wiki page could capture the answer for future reference.
ai-workspace-skill
by yysunScaffold, review, audit, and validate skill-based AI workspaces for agent hosts. Use when the user wants an AI workspace built around SKILL.md plus event handlers, references, templates, scripts, data, and output instead of AGENTS.md; when they want knowledge distillation workflows packaged as a reusable skill; or when they want to convert an AGENTS.md workspace pattern into a skill-owned workspace.
music-to-svg
by yysunUse the converter script to render a MusicXML file to SVG markdown image output.
notebooklm
by yysunUse this skill for NotebookLM tasks to create notebooks, add sources, query content, and generate artifacts through the NotebookLM CLI.
react-app
by yysunUse when creating, modifying, refactoring, reviewing, or organizing a React web app that uses Tailwind or utility-first CSS. Trigger for requests involving React pages, routes, layouts, components, feature UI, styling systems, app shells, frontend folder structure, UI architecture, import boundaries, thin routes, component placement, or avoiding catch-all folders such as `components` and `lib`. Especially relevant when deciding whether code belongs in foundations, primitives, patterns, features, pages, shell, or shared utilities.
story-deck
by yysunUse when user needs to plan, storyboard, review, critique, or rewrite a presentation outline or slide deck, including SCR presentations, BBP/Beyond Bullet Points presentations, scene-based decks, headline development, bitmap visual generation, and handoffs to Markdown, Marp, or PPTX production.
workspace-design
by yysunDesign or review business operation pages, workbenches, and review or follow-up pages as task-centric workspaces. Use when working from requirement docs, business workflows, wireframes, screenshots, HTML, or frontend page proposals.
youtube-search
by yysunUse this skill when the user asks to search YouTube or find videos by keyword. Trigger on phrases like "search youtube", "find on youtube", "look up on youtube", or when the user provides search keywords and wants YouTube results. Always use this skill for YouTube searches.
ai-workspace
by yysunCreate, review, audit, and validate AI workspaces for agent hosts such as Codex, Copilot, Gemini, and similar desktop or CLI runtimes. Use when the user asks to design an agent-ready repo, scaffold AGENTS.md and event handlers, create an API-backed or domain knowledge workspace, audit AGENTS.md or SKILL.md quality, or improve how a repo exposes behavior to coding agents.
rpd
by yysunUse this skill for software development tasks that should follow the RPD workflow: requirements, architecture planning, implementation, debugging, tests, E2E checks, code review, commits, done docs, or worktrees. Trigger on natural-language requests for those workflow stages, or when any of these keywords appears with command-like intent: RPD, REQ, AP, AR, SS, DF, DD, ET, TT, CR, VR, GC, WT, !!. The keyword must be surrounded by message boundaries, punctuation, or whitespace. Match examples like `REQ`, `REQ:`, `REQ-`, `REQ,`, `REQ -`, and `'REQ'`. Match middle or end forms like `please REQ: add login` or `ship it SS`. Do not match when a letter, digit, or underscore touches the keyword. Ignore keywords inside fenced code blocks or inline code spans.
react-architect
by yysunEnforce three-layer UI architecture (Foundations → Primitives → Patterns) for React + Tailwind projects. Use this skill whenever the user creates, modifies, reviews, or refactors React components, UI styling, CSS variables, Tailwind tokens, or design system code. Also use when the user asks where a component belongs, how to organize UI code, whether something should be a primitive or pattern, or how to avoid duplication in their component library — even if they don't mention "design system" or "three layers" explicitly.
Browse Agent Skills by Occupation
23 major groups · 867 SOC occupations
Browse by Category
Explore agent skills organized by their primary use case
Explore the agent skills ecosystem by occupation and creator
SkillMD is not just a keyword search box. It is an open map that organizes public skills by occupation, creator, and repository, helping you see which workflows, judgment criteria, and domain habits people are writing for AI agents.
Then follow creators and GitHub repositories back to the source: compare the skills a team maintains, whether the repo is active, and how the README frames the work before you open, install, or reuse anything.
Use it three ways: learn an unfamiliar field by occupation, study how creators organize skills, then use source context to decide what is worth opening or reusing.
01 Map a field
Browse 23 occupation groups and 867 SOC roles to learn what skills exist in adjacent domains and how they break down real work.
02 Follow creators
Use creator and repository pages to inspect maintained skill collections, recent updates, and source context before trusting a result.
03 Search with sources
Search 1.7M+ collected skills, then use occupation tags, creators, and GitHub source context to decide what is worth opening.
Start with the occupation map, then follow creators and repositories back to real code. SkillMD helps explain why a skill is worth opening, not only what it is named.
Standardizing Agent Capabilities with SKILL.md and Model Context Protocol (MCP)
In the rapidly evolving landscape of artificial intelligence, LLM agents (Large Language Model agents) have transitioned from simple text predictors to autonomous problem solvers. To orchestrate complex, multi-step agentic workflows, developers require a standardized format to specify agent capabilities, prompt instructions, system rules, and database bindings. This is where SKILL.md and the Model Context Protocol (MCP) have emerged as standard developer paradigms. SkillMD serves as the central directory for indexing, exploring, and sharing these critical agent configurations.
Our open-source registry currently tracks over 1.7 million collected SKILL.md configurations and system prompts. By compiling agent configurations from active developers on GitHub, we bridge the gap between prompt engineering research and production execution. Whether you are building agents with Anthropic's Claude Code, OpenAI's GPT-4, Google's Gemini, or local models using Ollama and LlamaIndex, standardized skill definitions ensure your agents behave predictably across different runtime environments.
What is the Model Context Protocol (MCP)?
The Model Context Protocol (MCP) is an open-source standard designed to connect LLMs to data sources, developer tools, and external environments. MCP establishes a bidirectional communication channel between client applications (like Cursor, Claude Desktop, or custom agent systems) and servers hosting data or capabilities. Standardizing instructions via SKILL.md enables LLMs to query databases, read local files, execute terminal commands, and integrate third-party APIs. SkillMD allows you to find ready-to-run MCP servers and prompt instructions for various occupations and technical tasks.
The Structure of a Professional SKILL.md File
A valid SKILL.md configuration is designed to be easily read by humans and parsed by LLMs. It contains precise system instructions, trigger conditions, required parameters, and execution examples. Below is the typical architectural blueprint of a professional agent skill:
- Metadata & Core Scope: Declares the name of the skill, author details, target models, and a description of the capability.
- Triggers & Intent Detection: Details semantic triggers that help the agent decide when to invoke this skill.
- System Prompts: Explicit system-level instructions that direct the agent's behavior, personality, safety guardrails, and formatting preferences.
- Capabilities & Tools: Lists the files, databases, or APIs the agent must access to complete the tasks.
- Few-Shot Examples: Demonstrates real inputs and outputs, helping the model generalize behavior through in-context learning.
Optimizing Agent Workflows for Modern LLMs
Writing effective agent skills requires deep knowledge of prompt engineering. With the release of advanced reasoning models like Claude 3.5 Sonnet, ChatGPT o1, and DeepSeek-V3, prompt templates must focus on structured thinking. Developers are encouraged to use XML tags (e.g., <thought>, <context>, and <rules>) to isolate execution boundaries. Standardized prompts prevent agents from suffering from context drift, ensuring that long-running tasks remain aligned with the initial system parameters.
Exploring by SOC Occupations and Creator Profiles
What makes SkillMD unique is its taxonomy. Instead of simple text search, we parse and organize files according to the Standard Occupational Classification (SOC) system. This means you can discover skills written for Computer and Mathematical roles, Business and Financial operations, Legal, Design, and and Educational Instruction fields. By tracking creator profiles, developers can study how different teams organize their custom instructions, compare version updates, and fork public configs for specialized enterprise use cases.
SkillMD operates as a high-performance index running on a fast Go backend and a highly responsive Astro SSR frontend. All search queries execute in milliseconds, featuring smart debouncing to prevent multiple API requests while keeping user data secure. Join our community of developers to standardize your AI agent instructions and optimize your LLM prompting workflows today.
Frequently Asked Questions
A practical guide to agent skills: what they are, how to inspect them, and how SkillMD helps you explore the ecosystem.