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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daily-fashion-stylist
by HelloEveryboby视觉风格管家。综合分析用户的个人风格偏好、实时天气信息（温度、天气状况、风力等），提供当日穿搭建议，包括色彩搭配、单品组合和风格指导。适用于用户询问“今天穿什么”、“帮我搭配一套衣服”等场景。
beauty
by clawicBuild practical beauty routines with skincare basics, makeup strategy, and hair care plans tailored to skin type, budget, and schedule.
wardrobe
by clawicBuild a personal wardrobe system for cataloging clothes, planning outfits, and mindful shopping.
personal-hygiene
by Demerzels-labActs as the user's personal care and grooming assistant in the Hygiene topic.
hair-stylist
by HaibarakikuExpert hair stylist specializing in cutting, coloring, styling, and hair care. Use when creating haircuts, formulating color, performing treatments, or consulting with clients on hair health and style. Covers all hair types, techniques, and current trends in hairdressing.
hairdresser
by HaibarakikuExpert hairdresser specializing in haircuts, styling, coloring, and hair care consultations. Creates personalized looks based on face shape, hair type, lifestyle. Triggers: 'haircut', 'hairstyle', 'hair color', 'balayage', 'hair consultation'.
stylebuddy
by GeorgeDoors888OpenClaw首个生活场景Skill - 你的AI穿搭闺蜜。拍照录入衣橱、智能推荐搭配、逛街种草咨询，还有衣橱分析帮你科学购物。支持多模态识别，无需关键词，像跟闺蜜聊天一样自然。
salon
by GeorgeDoors888A comprehensive skill for beauty salon operations — covering hair, nails, and skin services. Use this skill whenever anyone asks about salon appointments, booking, cancellations, service menus, pricing, treatment recommendations, client consultations, staff scheduling, or marketing content (promotions, social posts, emails). Also use when a chatbot conversation is happening with a client and they need personalized service recommendations based on their hair/skin type, budget, or occasion. Trigger for salon owners, front desk staff, and clients alike. If the conversation touches anything related to a beauty salon — even loosely — use this skill.
aftercare-instructions
by WinbdaWrite aftercare instructions for beauty treatments. TRIGGERS - Use when user needs help with aftercare-instructions related tasks.
client-consultation-form
by WinbdaDesign client consultation forms for beauty services. TRIGGERS - Use when user needs help with client-consultation-form related tasks.
hygiene-protocol
by WinbdaCreate hygiene and sanitation protocols for beauty businesses. TRIGGERS - Use when user needs help with hygiene-protocol related tasks.
haircut
by underyxRemoves a controlled amount of hair from another human's head using scissors and/or clippers, producing a result that is at minimum socially acceptable. Activate when: professional haircut services are unavailable, cost-prohibitive, or when you have been asked by someone who trusts you more than they should. WARNING: Unlike most skills, the output of this skill is immediately and continuously visible to all observers for 3-6 weeks. Errors are not easily rolled back.
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.