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.
Querying local SQLite index...
gaps-to-issues
by selfxyzCreate Linear issues from a PR audit doc — one issue per PR bucket with acceptance criteria and linked audit findings.
pr-summary
by selfxyzGenerate a GitHub PR title and summary from all branch changes, including Linear issue and Figma links when available. When targeting staging, generates a release changelog instead.
spec-from-audit
by selfxyzGenerate one spec per issue — repo file (canonical) + Linear document (mirror). Agent-executable implementation plans with file paths, validation commands, and acceptance criteria.
pr-audit
by selfxyzMulti-agent PR review — component, integration, and routing analysis merged into a structured audit doc with severity and PR buckets.
linear-initiative-update
by selfxyzDraft and post a status update for a Linear initiative you own. Pulls the last status update plus recent issue activity across the initiative's projects, drafts a brief informative update, and posts it after confirmation.
verify-agents
by selfxyzVerify Self Agent ID identities and add verification middleware to APIs. Covers one-off agent verification, SelfAgentVerifier builder pattern, reputation scoring, freshness validation, sybil detection, and the critical provider check. Use when the user asks to "verify an agent", "check agent identity", "add verification", "agent verification middleware", "is this agent verified", "reputation score", "check proof of human", or "validate agent freshness".
register-agent
by selfxyzStep-by-step guide for registering AI agents with proof-of-human identity on the Self Agent ID registry. Covers all 4 registration modes (verified-wallet, agent-identity, wallet-free, smart-wallet), 6 verification configs, MCP tools, and SDK usage. Use when the user asks to "register an agent", "create agent identity", "get verified", "self agent registration", "proof of human", "register with self", or "onboard agent".
self-agent-id-overview
by selfxyzConceptual overview of the Self Agent ID system — on-chain identity registry, ERC-8004 standard, ZK proof-of-human, provider system, trust model, and soulbound NFTs on Celo. Use when the user asks "what is self agent id", "explain self agent id", "how does agent identity work", "self protocol agents", "ERC-8004", or "proof of human for agents". Do NOT use for specific workflows like registration, signing, verification, or integration — use the dedicated skills for those.
sign-requests
by selfxyzHow to sign HTTP requests with Self Agent ID's 3-header authentication system. Covers ECDSA and Ed25519 signing, the signing algorithm, MCP tools (self_sign_request, self_authenticated_fetch), SDK usage in TypeScript/Python/Rust, and replay protection. Use when the user asks to "sign a request", "authenticate as agent", "agent auth headers", "self agent fetch", "signed HTTP request", "ed25519 signing", or "make authenticated call".
query-credentials
by selfxyzRead-only queries for Self Agent ID data — look up agents by address or ID, list agents for a human, check own identity, retrieve ZK-attested credentials, reputation scores, freshness status, and A2A agent cards. Use when the user asks to "lookup agent", "agent credentials", "check agent status", "find agents", "agent discovery", "agent card", "agent info", or "list agents for human". Do NOT use for verification middleware or adding verification to APIs — use verify-agents for that.
integrate-self-id
by selfxyzEnd-to-end integration guide for adding Self Agent ID to a project. Covers agent-side setup (SelfAgent class), service-side verification (SelfAgentVerifier), MCP server configuration, on-chain Solidity integration, and quick starts for TypeScript, Python, Rust, Express, FastAPI, Axum, and Hono. Use when the user asks to "add self agent id", "integrate self id", "setup self agent", "add agent verification to my project", "self agent id sdk", "install agent sdk", or "integrate proof of human".
self-xyz
by selfxyzIntegrate Self (self.xyz) — a privacy-first identity protocol using zero-knowledge proofs to verify passports and ID cards. Use when the user mentions Self protocol, Self identity, self.xyz, passport verification, zero-knowledge identity verification, SelfAppBuilder, SelfBackendVerifier, SelfVerificationRoot, or wants to add privacy-preserving KYC, age verification, nationality checks, OFAC screening, or Sybil resistance using real-world identity documents. Covers frontend QR code integration, backend proof verification, and on-chain smart contract verification on Celo.
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.