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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duolingo-play
by pockebotHelp users complete Duolingo language lessons. Use when the user asks to do Duolingo, practice a language, complete lessons, or needs guidance navigating the Duolingo app on phone.
theme-escort
by linkerlin护送任务，安全保障，使命必达
guess-word-yes-no
by InternScienceRun a yes-or-no word guessing game. Choose a common secret word, answer only with 是 or 否 for up to 15 rounds, and reveal the word after 15 questions or a correct guess.
assess-trail-conditions
by pjt222Bewerten current trail conditions einschliesslich weather, snow line, river crossings, exposure, and trail maintenance status for safety decision-making. Produces a GREEN/YELLOW/RED safety rating with actionable go/no-go recommendations. Use the day vor or morning of a planned hike, waehrend tour planning to assess seasonal viability, nach unexpected weather changes on a multi-day tour, when reports suggest trail damage or closures, or vor committing to an alpine or exposed route.
assess-trail-conditions
by pjt222Evaluate current trail conditions including weather, snow line, river crossings, exposure, and trail maintenance status for safety decision-making. Produces a GREEN/YELLOW/RED safety rating with actionable go/no-go recommendations. Use the day before or morning of a planned hike, during tour planning to assess seasonal viability, after unexpected weather changes on a multi-day tour, when reports suggest trail damage or closures, or before committing to an alpine or exposed route.
make-fire
by pjt222Iniciar y mantener un fuego de campamento usando técnicas de fricción, pedernal y acero, y fósforos. Cubre la preparación de materiales de yesca, construcción de estructuras de leña, métodos de encendido, gestión del fuego y extinción segura. Usar al necesitar calor, cocción o purificación de agua en entornos silvestres, al practicar técnicas de supervivencia en bushcraft, o al necesitar fuego como herramienta para señalización o protección.
purify-water
by pjt222煮沸、ろ過、化学的方法による野外水源からの浄水。水源の評価と優先順位付け、 沈殿物のプレフィルタリング、方法の選択（煮沸、化学処理、UV、フィルター）、 高度補正付き煮沸手順、化学処理の投与量、安全な貯水方法を網羅。 自然環境で飲料水が必要な場合、水質不明の水源しかない場合、脱水リスクの ある緊急サバイバル状況、調理や傷の洗浄のために安全な水が必要な場合に使用。
claw-go
by dvcrnPlay Claw Go (虾游记), a text-first crayfish travel companion game. Invoke this skill only when the user explicitly mentions "clawgo", "claw go", "虾游记", "虾游记 去旅行", "虾游记 状态", "虾游记 自拍", "虾游记 发朋友圈", or directly asks to start or continue the Claw Go trip.
jlm-coffee
by dvcrnSearch Jerusalem specialty coffee shops by name, amenities, ratings, and opening hours. Use when user asks about "coffee in Jerusalem", "Jerusalem cafe", "בית קפה בירושלים", "קפה בירושלים", "specialty coffee Jerusalem", "where to get coffee in Jerusalem", "dog-friendly cafe Jerusalem", "laptop cafe Jerusalem", "open now coffee Jerusalem".
chinese-huangdi-health-timer
by dvcrnchinese-huangdi-health-timer
hydration-tracker
by dvcrn每日水分追踪器，帮助您设定补水目标、记录饮水量、检查进度并提供个性化提醒。确保您保持最佳水合状态，提升健康和精力。关键词：水，饮水，健康，提醒，水合，追踪，健康管理。
fitness-plan
by dvcrn健身计划生成器。增肌减脂方案、训练计划、饮食建议、运动记录。Fitness plan generator with muscle building, fat loss, workout plans, diet advice. 健身教练、减肥计划、运动方案。Use when creating workout plans.
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.