What are agent skills?

Agent skills are declarative bundles (written as SKILL.md files) that detail instructions, triggers, capabilities, and system prompts for autonomous AI agents like Claude Code, Cursor, or GitHub Copilot. They define what an agent does and when it should execute.

How do I install agent skills from SkillMD?

You can install any skill directly using the agent-reach CLI: run 'agent-reach install '. Most skills are also integrated by copying the SKILL.md file into your agent's workspace directory.

Are these skills safe to use?

All skills on SkillMD are indexed from public open-source repositories on GitHub. Since they contain system instructions and prompts, we recommend reviewing the repository source code and the creator's profile before utilizing them in untrusted environments.

Can I use multiple skills together?

Yes! Modern AI agents are designed to select the appropriate skill dynamically based on user triggers. You can register multiple SKILL.md instructions into your agent's command list.

Can I create and share my own skills?

Absolutely. Simply create a repository containing a valid SKILL.md file on GitHub and publish it. Our background scraper subprocess regularly scans GitHub to index new agent skills.

What is SKILL.md format?

SKILL.md is an open standard developed by Anthropic for defining AI agent capabilities. A skill is a folder containing a SKILL.md file with YAML frontmatter (name, description, metadata) and a Markdown body with instructions. It is supported by Claude Code, Cursor, GitHub Copilot, Codex CLI, Gemini CLI, Windsurf, VS Code, and many other AI tools.

How often are skills updated?

The index is continuously updated by our background scraper subprocess, which runs periodically to scan new stars, updates, and newly created SKILL.md files on GitHub.

Is this website affiliated with Anthropic or OpenAI?

No. SkillMD is an independent open-source community registry built for developers to search and discover agent components across any LLM platform.

381,784 Collected SKILL.md files

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.

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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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Total Skills Indexed

381,784

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Total Repo Stars

692,234,539

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Active Creators

by RightNow-AI

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Go programming expert for goroutines, channels, interfaces, modules, and concurrency patterns

navigation main article SKILL.md

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Browse Agent Skills by Occupation

23 major groups · 867 SOC occupations

Browse by Category

Explore agent skills organized by their primary use case

SKILLMD / CREATORS AND OCCUPATION CATEGORIES

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.

SEO KNOWLEDGE HUB & TECHNICAL OVERVIEW

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.

8 QUESTIONS

Frequently Asked Questions

A practical guide to agent skills: what they are, how to inspect them, and how SkillMD helps you explore the ecosystem.

Explore AI Agent Skills & Claude Prompts

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browser-automation

docker

data-pipeline

data-analyst

elasticsearch

email-writer

figma-expert

graphql-expert

gcp

git-expert

github

golang-expert

Browse Agent Skills by Occupation

Computer and Mathematical Occupations

Business and Financial Operations Occupations

Arts, Design, Entertainment, Sports, and Media Occupations

Office and Administrative Support Occupations

Legal Occupations

Educational Instruction and Library Occupations

Life, Physical, and Social Science Occupations

Management Occupations