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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csv-documentation-generator
by LeoYeAIUse when generating computer system validation (CSV) documentation for pharmaceutical and medical device industries, including validation plans, URS, FS, IQ/OQ/PQ documents, and traceability matrices.
capa-officer
by ricardonevesbragaGestão do sistema CAPA para QMS de dispositivos médicos. Cobre análise de causa raiz, planejamento de ações corretivas, verificação de eficácia e métricas de CAPA. Use para investigações CAPA, análise dos 5 Porquês, diagramas de Ishikawa, determinação de causa raiz, rastreamento de ações corretivas, verificação de eficácia ou otimização do programa de CAPA.
fda-consultant-specialist
by ricardonevesbragaConsultor regulatório FDA para empresas de dispositivos médicos. Fornece orientação sobre vias 510(k)/PMA/De Novo, conformidade QSR (21 CFR 820), avaliações HIPAA e cibersegurança de dispositivos. Use quando o usuário mencionar submissão FDA, 510(k), PMA, De Novo, QSR, pré-mercado, dispositivo predicado, equivalência substancial, HIPAA para dispositivos médicos ou cibersegurança FDA.
qms-audit-expert
by ricardonevesbragaEspecialista em auditoria interna ISO 13485 para QMS de dispositivos médicos. Cobre planejamento de auditoria, execução, classificação de não conformidades e verificação de CAPA. Use para planejamento de auditoria interna, execução de auditoria, classificação de achados, preparação para auditoria externa ou gestão do programa de auditoria.
quality-documentation-manager
by ricardonevesbragaGestão do sistema de controle de documentos para QMS de dispositivos médicos. Cobre numeração de documentos, controle de versão, gestão de mudanças e conformidade com 21 CFR Part 11. Use para procedimentos de controle de documentos, fluxo de trabalho de controle de mudanças, numeração de documentos, gestão de versões, conformidade de assinatura eletrônica ou revisão de documentação regulatória.
neuroskill-data-reference
by NeuroSkill-comNeuroSkill EEG data reference — all metric fields including band powers, EEG ratios and indices, core scores, complexity measures, PPG/HRV fields, motion and artifact markers, sleep stage codes, headache/migraine correlate indices, and consciousness metrics. Use when looking up what a specific metric means or its value range.
capa-officer
by tools-onlyCAPA system management for medical device QMS. Covers root cause analysis, corrective action planning, effectiveness verification, and CAPA metrics. Use for CAPA investigations, 5-Why analysis, fishbone diagrams, root cause determination, corrective action tracking, effectiveness verification, or CAPA program optimization.
qms-audit-expert
by tools-onlyISO 13485 internal audit expertise for medical device QMS. Covers audit planning, execution, nonconformity classification, and CAPA verification. Use for internal audit planning, audit execution, finding classification, external audit preparation, or audit program management.
mdr-745-specialist
by thiagofernandes1987-createManage — EU MDR 2017/745 compliance specialist for medical device classification, technical documentation, clinical evidence, and post-market surveillance. Covers Annex VIII classification
healthcare-products
by gauravhubUsage guidance, safety information, and troubleshooting for healthcare and wellness devices
neurokit2
by jswortzComprehensive biosignal processing toolkit for analyzing physiological data including ECG, EEG, EDA, RSP, PPG, EMG, and EOG signals. Use this skill when processing cardiovascular signals, brain activity, electrodermal responses, respiratory patterns, muscle activity, or eye movements. Applicable for heart rate variability analysis, event-related potentials, complexity measures, autonomic nervous system assessment, psychophysiology research, and multi-modal physiological signal integration.
clawhub-lovable
by LJT-520Helps OpenClaw Clinical Hackathon participants get started quickly building clinical and healthcare apps with Lovable. Use when the user is building a clinical app in Lovable, mentions the hackathon or Lovable, or asks for quick-start guidance for clinical projects (patient intake, dashboards, assessments, PHI-safe patterns).
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.