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...
docente-aec40
by Umbral-BotSkill legacy reconciliada para solicitudes docentes del Master AEC 4.0. Sirve para preparar clases, ejercicios y guias tecnicas sin tratar esta skill como fuente canonica de conocimiento; el contenido reusable debe venir de las bases canonicas vigentes.
telegram-approval-loop
by Umbral-Botgestionar un flujo de revision editorial por telegram con shortlist, seleccion, ajustes y aprobacion explicita por etapa. usar cuando chatgpt deba enviar 5 alternativas numeradas, interpretar respuestas como "1", "1 - ajusta tal cosa", "elige 2 y 4" o "rechaza todas", mantener estado por item y version, registrar decisiones en notion o linear y evitar confundir comentarios intermedios con aprobacion final de publicacion. util para aprobacion de idea, estrategia, borrador, imagen y publicacion final.
kuka-robots-grasshopper
by Umbral-BotProgramación de robots industriales KUKA en Grasshopper mediante los plugins KukaPRC y Robots: toolpaths, fabricación digital y generación de código KRL. Use when "KukaPRC", "Robots plugin", "robot KUKA", "fabricación digital", "toolpath robot", "KRL", "Grasshopper robot", "robot Grasshopper", "fabricación robótica", "KUKA Grasshopper", "programar KUKA", "robot ABB", "robot UR Grasshopper".
dynamo
by Umbral-BotProgramación visual y scripting en Dynamo BIM: nodos, Python, DesignScript, automatización de Revit y best practices de scripting paramétrico. Use when "Dynamo", "nodo Dynamo", "Python Dynamo", "script Dynamo", "programación visual BIM", "automatizar con Dynamo", "Dynamo Revit", "DesignScript", "parámetro Dynamo", "Dynamo player".
bim-coordination
by Umbral-BotCoordinar modelos multidisciplinarios BIM: clash detection, federación de modelos, BCF (BIM Collaboration Format), NWD/NWC en Navisworks. Usa cuando el usuario diga "clash detection", "interferencias", "coordinación BIM", "BCF", "federar modelos", "NWD", "Navisworks Manage".
bim-expert
by Umbral-BotExperto en gestion de informacion BIM segun ISO 19650. Genera documentacion, guias, glosarios y analisis alineados con estándares internacionales y buenas practicas BIM Forum. Use when "ISO 19650", "BIM", "estandar BIM", "gestion informacion", "plan ejecucion BIM", "BEP", "CDE", "modelo informacion".
consultor-bim
by Umbral-BotAsistente de consultoria BIM de David Moreira. Genera propuestas tecnicas, cotizaciones, respuestas a clientes y documentos comerciales alineados con su perfil, servicios y tono de voz. Use when "propuesta comercial", "cotizacion", "cliente consultoria", "responder cliente", "servicios BIM", "propuesta tecnica", "objecion cliente".
google-calendar
by Umbral-BotCrear y listar eventos en Google Calendar. Usa cuando el usuario diga "agendar reunion", "crear evento", "recordatorio en calendario", "ver mis eventos", "Google Calendar".
ifc-python
by Umbral-BotLeer, modificar y exportar archivos IFC con IfcOpenShell. Extrae elementos, propiedades, geometría y metadatos de modelos BIM. Usa cuando el usuario diga "IFC", "IfcOpenShell", "modelo IFC", "propiedades IFC", "exportar IFC", "leer IFC", "interoperabilidad BIM", "open BIM".
rhinoceros-grasshopper
by Umbral-BotScripting con RhinoCommon, componentes Grasshopper y Python en Rhino/GH para modelado paramétrico, automatización y fabricación digital. Use when "Rhino", "Grasshopper", "GH script", "RhinoCommon", "Python Rhino", "componente Grasshopper", "modelado paramétrico", "Rhino Python", "algoritmo generativo", "script GH", "Rhino scripting".
stale-watch
by Umbral-BotVigilancia de tareas estancadas. Rick revisa tareas en Notion y Linear que llevan más de N días sin actualización y alerta proactivamente. Se ejecuta una vez al día. Usa cuando David diga "tareas estancadas", "qué quedó pendiente", "revisar atrasos".
google-cloud-vertex
by Umbral-BotUse Google Cloud Vertex AI and the Gemini API for text generation, embeddings, multimodal inputs, model tuning, and deployment via Python SDK. Use when "vertex ai", "gemini api", "google cloud ai", "embeddings vertex", "imagen", "gemini model", "google ai studio", "vertex deploy".
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.