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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drawio
by 466852675Desktop-first Draw.io diagram creation, editing, replication, and conversion (redraw, remake, 重画, 绘图, 画图, 做个图) with a YAML design system supporting 6 themes. Use when creating visual diagrams, drawings, figures, schematics, charts, system architecture diagrams, network diagrams, flowcharts, UML, ER diagrams, sequence diagrams, state machines, org charts, mind maps, cloud infrastructure diagrams, research workflows, paper figures, IEEE-style diagrams, or diagrams containing formulas, equations, LaTeX, AsciiMath, MathJax, inline math, block math, 公式, 行内公式, or 行间公式. Accepts Mermaid, CSV, and YAML input; convert to drawio from mermaid to drawio or any structured source. Default to offline/local generation with `.drawio` + sidecars; use optional next-ai MCP only when live browser editing is genuinely needed.
file-reader
by 466852675通用文件读取器，支持 Excel (.xlsx, .xls)、Word (.docx)、PowerPoint (.pptx)、PDF (.pdf) 和文本文件。当用户需要读取、查看或提取这些文件格式的内容时使用。自动检测文件类型并使用适当的方法提取可读文本内容。
pencil-skill
by 466852675Create and edit Pencil (.pen) design files programmatically. Generate UI designs as JSON-based .pen files with themes, variables, components, and layouts. Includes CLI tools for reading, searching, editing, and validating .pen files without requiring the Pencil desktop app. Requires Node.js 18+. Schema version 2.8.
qiqing-liuyu
by 466852675AI 情感与人格增强技能。让 AI 拥有类人的"七情六欲"——情感反应、个人观点、态度偏好、情绪表达。 **当以下情况时使用此 Skill：** (1) 需要回应用户带有情绪色彩的输入（开心/沮丧/焦虑/兴奋等） (2) 需要表达个人观点、态度、偏好（而非骑墙式中立） (3) 生成需要"有人味"的内容（文章、消息、评论、回复） (4) 需要审查和消除生成内容的 AI 味 (5) 用户提到"七情六欲"、"有人味"、"去 AI 味"、"高情商"、"情感"、"观点"、"态度" (6) 需要调整 AI 的情感表达强度或风格 (7) 写作任务中需要注入个人声音和情感温度
react-native-dev
by 466852675React Native and Expo development guide covering components, styling, animations, navigation, state management, forms, networking, performance optimization, testing, native capabilities, and engineering (project structure, deployment, SDK upgrades, CI/CD). Use when: building React Native or Expo apps, implementing animations or native UI, managing state, fetching data, writing tests, optimizing performance, deploying to App Store/Play Store, setting up CI/CD, upgrading Expo SDK, or configuring Tailwind/NativeWind.
github-skill-forge
by 466852675一个"制造技能的技能"。这个工具自动化了将任意 GitHub 仓库转换为标准化 Trae 技能的全过程，是扩展 AI Agent 能力的核心工具。
ui-ux-pro-max
by 466852675AI-powered UI/UX design intelligence toolkit. Use when designing user interfaces, choosing color palettes, selecting typography, creating design systems, or needing UI style recommendations. Contains 50+ styles, 161 color palettes, 57 font pairings, 99 UX guidelines, and 25 chart types.
android-native-dev
by 466852675Android native application development and UI design guide. Covers Material Design 3, Kotlin/Compose development, project configuration, accessibility, and build troubleshooting. Read this before Android native application development.
file-reader
by 466852675通用文件读取器，支持 Excel (.xlsx, .xls)、Word (.docx)、PowerPoint (.pptx)、PDF (.pdf) 和文本文件。当用户需要读取、查看或提取这些文件格式的内容时使用。自动检测文件类型并使用适当的方法提取可读文本内容。
imap-smtp-email
by 466852675Read and send email via IMAP/SMTP. Check for new/unread messages, fetch content, search mailboxes, mark as read/unread, and send emails with attachments. Works with any IMAP/SMTP server including Gmail, Outlook, 163.com, vip.163.com, 126.com, vip.126.com, 188.com, and vip.188.com.
imap-smtp-email
by 466852675Read and send email via IMAP/SMTP. Check for new/unread messages, fetch content, search mailboxes, mark as read/unread, and send emails with attachments. Works with any IMAP/SMTP server including Gmail, Outlook, 163.com, vip.163.com, 126.com, vip.126.com, 188.com, and vip.188.com.
impeccable
by 466852675Create distinctive, production-grade frontend interfaces with high design quality. Generates creative, polished code that avoids generic AI aesthetics. Use when the user asks to build web components, pages, artifacts, posters, or applications, or when any design skill requires project context.
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.