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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open-data
by djimitHelpt bij het publiceren en gebruiken van open data conform Nederlandse en Europese standaarden, inclusief DCAT-AP-NL, data.overheid.nl, high-value datasets en de Wet hergebruik overheidsinformatie (Who). Gebruik deze skill wanneer de gebruiker vraagt over 'open data', 'DCAT', 'DCAT-AP', 'DCAT-AP-NL', 'data.overheid.nl', 'dataset publiceren', 'publish dataset', 'open data overheid', 'government open data', 'high-value dataset', 'HVD', 'Wet hergebruik overheidsinformatie', 'Who', 'Open Data Richtlijn', 'Open Data Directive', 'CKAN', 'dataportaal', 'data portal', 'catalogus', 'metadata dataset', 'linked data overheid', 'SPARQL overheid', 'API dataset', 'bulk download', 'machine-leesbaar', 'machine-readable', 'CSV overheid', 'JSON overheid', 'RDF overheid', 'open data licentie', 'CC0', 'public domain', 'hergebruik data', 'data reuse', 'FAIR data', 'dataregister', 'data inventory', of wanneer de gebruiker data wil publiceren of gebruiken via Nederlandse overheidsdata-platformen.
zgw-apis
by djimitHelpt bij het integreren met ZGW API-standaarden (Zaakgericht Werken) en Haal Centraal API's voor Nederlandse overheidsorganisaties. Biedt richtlijnen voor de Zaken API, Documenten API, Catalogi API, Besluiten API, Klantinteracties API, en Haal Centraal (BRP, BAG, BRK, WOZ). Gebruik deze skill wanneer de gebruiker vraagt over 'ZGW', 'zaakgericht werken', 'Zaken API', 'Documenten API', 'Catalogi API', 'Besluiten API', 'Autorisaties API', 'Contactmomenten API', 'Klantinteracties API', 'ZGW API', 'case management API', 'zaaktype', 'zaak aanmaken', 'document uploaden', 'informatieobject', 'statustype', 'resultaattype', 'Haal Centraal', 'BRP API', 'BAG API', 'BRK API', 'WOZ API', 'basisregistratie', 'base registry API', 'personen API', 'adressen API', 'kadaster API', 'VNG Realisatie', 'VNG standaarden', 'NL API Design Rules', 'API Design Rules overheid', 'REST API overheid', 'government REST API', 'Common Ground API', 'Open Zaak', 'zaaksysteem', 'case system', 'OpenAPI overheid', 'API-strategie overheid', 'Digikop
dpia-assessment
by djimitHelpt bij het uitvoeren van een DPIA (Data Protection Impact Assessment / Gegevensbeschermingseffectbeoordeling) conform de AVG en het model van de Rijksoverheid. Begeleidt door alle stappen van het assessment met vragen, risicobeoordeling, maatregelen en AP-criteria. Gebruik deze skill wanneer de gebruiker vraagt over 'DPIA', 'data protection impact assessment', 'gegevensbeschermingseffectbeoordeling', 'GEB', 'PIA', 'privacy impact assessment', 'DPIA uitvoeren', 'DPIA invullen', 'DPIA template', 'DPIA model', 'DPIA Rijksoverheid', 'DPIA verplicht', 'DPIA criteria', 'AP DPIA-lijst', 'risicobeoordeling privacy', 'privacy risk assessment', 'voorafgaande raadpleging AP', 'prior consultation', 'hoog risico verwerking', 'high risk processing', 'DPIA artikel 35', 'DPIA algoritme', 'DPIA AI', 'DPIA app', 'DPIA systeem', 'DPIA software', 'privacy risico', 'privacy risk', 'restrisico', of wanneer de gebruiker een gegevensbeschermingseffectbeoordeling wil uitvoeren voor een systeem, applicatie of gegevensverwerking.
tooi-metadata
by djimitHelpt bij het werken met TOOI (Thesauri en Ontologieen voor Overheidsinformatie), de Woo (Wet open overheid) en het publiceren van overheidsdocumenten volgens het KOOP-publicatieplatform. Biedt richtlijnen voor metadata-standaarden, waardelijsten, identificatie-URI's en Woo-categorisering. Gebruik deze skill wanneer de gebruiker vraagt over 'TOOI', 'Woo', 'Wet open overheid', 'WOB', 'openbaarheid', 'overheidsinformatie publiceren', 'KOOP', 'publicatieplatform overheid', 'officielebekendmakingen', 'wetten.overheid.nl', 'open.overheid.nl', 'overheid.nl metadata', 'BWB', 'JCDR', 'CVDR', 'waardelijst overheid', 'thesaurus overheid', 'informatiecategorie Woo', 'actieve openbaarmaking', 'TOP-lijst', 'register Woo', 'Woo-verzoek', 'Woo-besluit', 'publicatieplicht', 'Staatscourant', 'Gemeenteblad', 'Provinciaal blad', 'STOP standaard', 'TPOD', 'juriconnect', 'overheidsidentificatie', 'identifier overheid', 'URI-strategie overheid', of wanneer de gebruiker overheidsdocumenten wil publiceren of metadata wil structurere
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.