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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chef-assistant
by NVIDIAUse when cooking or planning meals, troubleshooting recipes, learning culinary techniques
ingredient-substitution-engine
by revfactory식재료 대체 방안과 알레르기·식이 제한 대응 가이드. 'recipe-writer'와 'meal-designer' 에이전트가 식이 제한에 맞는 레시피를 작성하거나 대체 재료를 선정할 때 이 스킬의 대체 매트릭스와 변환 규칙을 반드시 활용해야 한다. '재료 대체', '알레르기 대응', '비건 대체' 등에 사용한다. 단, 칼로리 계산이나 장보기 목록은 이 스킬의 범위가 아니다.
alfworld-appliance-preparer
by taomiaoThis skill prepares an appliance (like a microwave, oven, or toaster) for use by ensuring it is in the correct open/closed state. Trigger this when the agent needs to use an appliance for heating, cooling, or cooking and must first open or close it. It takes an appliance identifier as input and outputs a confirmation that the appliance is ready.
recipe-generator
by cclank自动生成高品质菜谱的技能。当用户需要创建详细的菜谱、烹饪教程、食谱配方时使用。输入菜品名称后，检索权威来源（米其林、舌尖上的中国等）的制作工艺，生成包含完整准备工作、详细制作步骤、注意事项和专业技巧的菜谱文档，并最终生成传统中式风格的菜谱海报生图提示词。
arabic-cooking
by Moshe-shipوصفات عربية — ابحث واقترح وصفات من المطبخ العربي (سعودي، مصري، شامي، مغربي، خليجي). استخدم عندما يسأل المستخدم عن طبخ أو وصفة أو مكوّنات.
add-recipe
by richardblythman**Recipe Formatter & Adder**: Takes a recipe from any source (URL, photo, description, cookbook reference) and creates a properly formatted, nutrition-calculated recipe file in the knowledge base. Also creates any missing component files for ingredients. Use this skill whenever the user wants to add a new recipe, save a recipe they found, format a recipe for the database, log a meal they cooked, create a recipe from ingredients, or build out their recipe collection. Also trigger when the user shares a recipe link, photo of a recipe, or describes a meal they want to add. Trigger for "add recipe", "save this recipe", "I made X tonight and want to save it", "format this recipe", "new recipe", or when the user shares food-related URLs or images.
diagnose
by julianleopoldDiagnose espresso extraction issues by correlating machine telemetry with taste feedback. Use when user says: "what went wrong", "analyze that shot", "why did it taste [sour/bitter/flat]", "my shots are inconsistent", or asks about pressure spikes, flow issues, or extraction problems. Fetches shot data via analyze_shot MCP tool, interprets patterns, and provides actionable recommendations.
feedback
by julianleopoldGather shot feedback, analyze extraction, recommend adjustments, and record results. Use when user says: "/feedback", "I just pulled a shot", "how was that", "it tasted [sour/bitter/flat/good]", provides a star rating, shares taste observations, or asks "what should I adjust" after a shot. Owns the full shot feedback loop: gathering, analysis, tasting notes, and drink format.
knowledge-lookup
by julianleopoldAnswer espresso knowledge questions from the authoritative knowledge files. Use when the user asks about: temperature, pressure, ratios, grind settings, freshness, extraction theory, puck prep, channeling, baskets, decaf, blends, milk steaming, drink specs, profiles, shot styles, or any espresso concept. Routes to the correct knowledge file and answers from its content rather than from memory or training data.
sharpen-knife
by pjt222Sharpen and maintain knives using whetstones, field stones, and improvised abrasives. Umfasst blade anatomy, bevel assessment, whetstone technique (coarse to fine progression), stropping, sharpness testing, field sharpening methods, and ongoing edge maintenance. Verwenden wenn a knife fails the fingernail test, when cutting tasks require excessive pressure, vor a trip where a sharp blade is essential, nach heavy use, or when a blade has visible nicks or a rolled edge. Applicable to bushcraft blades, folding knives, and garden cutting tools.
sharpen-knife
by pjt222Afilar y mantener cuchillos usando piedras de afilar, piedras de campo y abrasivos improvisados. Cubre anatomía de la hoja, evaluación del bisel, técnica de piedra de afilar (progresión de grueso a fino), asentado, pruebas de filo, métodos de afilado en campo y mantenimiento continuo del filo. Usar cuando un cuchillo no pasa la prueba de la uña, cuando las tareas de corte requieren presión excesiva, antes de un viaje donde una hoja afilada es esencial, después de uso intenso, o cuando una hoja tiene mellas visibles o un filo doblado. Aplicable a cuchillos de bushcraft, navajas plegables y herramientas de corte de jardín.
coffee-operations
by oschrenkBrew coffee, manage recipes, and log brews.
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.