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...
theme-starfleet
by linkerlin星际探索，未知领域，开拓前沿
incident-response-incident-response
by krishnakanthb13Use when working with incident response incident response
incident-brief
by dwani-aiIncident-style handoff brief from structured per-chunk scene, events, security, and logistics JSON.
mindfulness
by pjt222Cultivate defensive situational awareness, threat assessment, and mental clarity under pressure. Covers the Cooper color code awareness system, body language reading and intent detection, verbal de-escalation, moving mindfulness in public spaces, combat focus and the OODA loop, rapid grounding techniques for acute stress, context-specific integration, and ongoing review and refinement of awareness skills. Use when entering unfamiliar or potentially hostile environments, needing to assess a situation for safety, de-escalating a verbal confrontation, or integrating awareness practice into daily movement.
design-police-themed-nature-walk-challenge
by gabrielmoreiraDesign gamified nature walk challenges for police officers that include specific missions and use police terminology for personalization.
law-enforcement-wellness-generator
by gabrielmoreiraGenerates comprehensive wellness content—including books, meditations, progressive muscle relaxation (PMR), and activities—using a dual persona of officer and psychologist. Features specialized guided imagery, tactical relaxation techniques, and specific validation/affirmation meditations to help law enforcement professionals thrive amidst high-stress environments.
write-epic-encouraging-speeches-for-police-officers
by gabrielmoreiraGenerates motivational speeches for police officers facing specific struggles (e.g., substance use, burnout), using police-related terminology and an epic, encouraging tone.
police-wellness-meditation-generator
by gabrielmoreiraGenerates immersive guided imagery, structured relaxation, and mindfulness meditations for law enforcement officers. Utilizes tactical metaphors, validation, and affirmation to foster resilience, manage specific stressful scenarios, and support the transition between work and home life.
write-epic-encouraging-speeches-for-police-officers
by gabrielmoreiraGenerate epic, motivational speeches for police officers facing professional or personal struggles (e.g., substance use, burnout), utilizing police terminology to foster encouragement and resilience.
pilot-disaster-response-setup
by TeoSlayerDeploy a disaster response coordination system with 4 agents. Use this skill when: 1. User wants to set up coordinated disaster monitoring, response coordination, resource allocation, and communications agents 2. User is configuring an emergency management, incident response, or public safety workflow 3. User asks about disaster alert pipelines, resource deployment optimization, or emergency broadcast systems Do NOT use this skill when: - User wants a single alert notification (use pilot-alert instead) - User wants to broadcast a one-off announcement (use pilot-announce instead) - User only needs sensor data streaming without the response pipeline (use pilot-stream-data instead)
traffic-enforcement-summary
by lev-osGenerates structured summaries of traffic law enforcement data covering DUI metrics, violation trends, enforcement outcomes, and resource allocation. Use when analyzing citation records, arrest statistics, violation reports, or preparing public safety strategic planning documents for law enforcement leadership.
incident-command-decisions
by curiositechDecision-making patterns in incident command and emergency management leadership contexts
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.