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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pickme-diagnostics
by galliganTroubleshoots pickme indexing issues including missing files, stale indexes, gitignore conflicts, and root coverage. Use when files are missing from pickme, index seems stale, or when debugging, troubleshooting, or investigating pickme behavior.
xmtp
by galliganUse the xmtp-signet to connect an agent to XMTP conversations through the v1 credential model. Covers the signet runtime, the owner/admin/operator/credential/seal hierarchy, the `xs` CLI surface for daily operation (status, chat, msg, inbox, search, lookup, consent, seal inspection, credential inspection, policy inspection), and how harnesses connect over WebSocket or MCP without direct XMTP access. Use this skill whenever someone asks what the signet is, how to run an agent on top of it, how to send or read messages through it, how to join or host Convos conversations, how to inspect seals or credentials, how reveals work, how trust is surfaced, or how a harness should stream and respond to XMTP traffic through the signet. For orchestrator-side setup — bootstrapping the daemon, creating operators, issuing credentials, managing keys and wallets — use the `xmtp-admin` skill.
xmtp-signet-use
by galliganUnderstand and use the xmtp-signet to connect agents to XMTP conversations through the current v1 credential model. Covers the signet runtime, the owner/admin/operator/credential/seal hierarchy, permission scopes, reveals, and how harnesses connect through WebSocket or MCP without direct XMTP access. Use this skill whenever someone asks what the signet is, how to scope an agent's permissions, how to connect an agent through the signet, what seals communicate, how trust and verification work, how to deploy a signet, or how an agent should participate in XMTP conversations through the signet.
xmtp-signet-dev
by galliganWork on the xmtp-signet codebase — add features, fix bugs, write handlers, extend transports, create schemas, and understand the current v1 architecture. Teaches the handler contract, package tiers, error taxonomy, Result types, and testing patterns. Use this skill whenever working on any packages/* code, adding a new feature to the signet, writing or modifying a handler, creating or updating Zod schemas, extending a transport adapter, debugging signet internals, understanding how the packages relate, or asking "where does this code go?"
xmtp-docs-blz
by galliganLook up current XMTP documentation using the blz CLI. Use when you need to check XMTP SDK methods, group permissions, identity model, content types, MLS details, or any XMTP protocol or API question. Prevents hallucinating outdated SDK patterns. Use when: (1) looking up XMTP SDK methods or patterns, (2) verifying API signatures before writing code, (3) understanding XMTP protocol concepts (groups, MLS, inboxes, attestations), (4) checking content type schemas, (5) any question about how XMTP works.
xmtp-admin
by galliganAdminister an xmtp-signet as an orchestrating agent or owner — bootstrap the daemon, initialize and rotate keys, create managed wallets, create and remove operators, define policies, issue and revoke credentials, create and link managed inboxes, verify seals and walk seal history, and drive the privileged `xs` command surface that sets agents up to operate against the signet. Use this skill whenever someone asks how to set up a signet for agents, how to issue or revoke a credential, how to provision an operator with a scoped policy, how to rotate or export operator keys, how to link an inbox to an operator, how to verify a seal chain, or how to run privileged admin flows. For day-to-day agent use (messaging, reading, inspecting credentials and seals, harness connection), use the `xmtp` skill.
skills-authoring
by galliganCreates or updates skills with proper YAML frontmatter, progressive disclosure, and best practices per the open Agent Skills specification. Supports simple, tool-restricted, multi-file, and script-based skills. Use when creating new skills, authoring skills, extending agent capabilities, or when `--create-skill` or `--new-skill` flag is mentioned.
mg-voice
by galliganWrites content in Matt Galligan's authentic voice—curious practitioner, builder's mindset, concrete specificity over abstraction. Use when drafting blog posts, articles, product announcements, personal reflections, or technical specs.
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.