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...
zhihe-legal-research
by cat-xierluo连接智合AI法律大模型平台进行法律研究。本技能应在用户需要进行法律问题研究、查找法律法规、检索类似案例、或获取法律研究报告时使用。需要智合AI平台会员账号。
svg-book-illustrator
by cat-xierluo书籍/文章 SVG 配图生成工具，专注于架构图、流程图、层次图等专业技术配图。当用户需要为书籍章节或正式文章生成配图、创建架构图/流程图/层次图，或提到"章节配图"、"书籍插图"、"架构图"、"流程图"时使用此技能。
course-generator
by cat-xierluo课程内容管理平台。支持三种工作模式：从转录稿/文献生成结构化课程（生成模式）、将课程归档整理到知识库（归档模式）、根据客户需求从现有素材中提取重组内容（提取模式），并可通过用户词典自动纠正转录稿中的近似误转写术语。本技能应在用户需要将文献整理为课程、归档课程文件、或根据培训需求定制课程方案时使用，尤其适合需要把长转录稿整理成章节边界清晰、段落可读、问答自然融入正文、去除转录来源痕迹、保留英文专有名称、图片资产可追溯但正文插图克制，并保留高价值观点、案例、判断和实践细节的独立课程文档。
tingwu-asr
by cat-xierluo使用阿里云通义听悟进行云端音频/视频转录。本技能应在用户需要云端语音转文字、长音频转录、本地 FunASR 不可用或需要更高精度时使用。不适用于无网络环境或需要完全离线的场景。
douyin-batch-download
by cat-xierluo抖音视频批量下载工具 - 基于 F2 框架实现高效、增量的视频下载功能。支持单个/批量博主下载，自动 Cookie 管理，差量更新机制。本技能应在用户需要批量下载特定博主视频、服务器部署自动化下载、或定期更新视频库时使用。
img2pdf
by cat-xierluo将图片或 PDF 页面按 N 张/页编排为标准化 A4 PDF，或将长截图渲染为单张自适应高度 PDF。本技能应在用户需要将截图（手机截图、视频截图）、照片、已有 PDF 页面或长截图（微信聊天、庭审笔录）合并为 PDF 时使用。不要用于：OCR 文字识别、PDF 内容编辑、图片格式转换。
md2word
by cat-xierluoMarkdown转Word文档技能。将Markdown文档转换为符合中文排版标准的专业格式Word文档，支持多种预设格式。适用于正式文档、论文、报告等需要规范排版的文档转换。
skill-manager
by cat-xierluo管理 Claude Code、Codex 和 OpenClaw Skills 的安装、版本追踪和更新检查。支持从本地路径或 GitHub 仓库安装，自动识别 .codex/.claude/.openclaw 目标目录，记录每个 Skill 的安装时间、来源 URL 和版本号，并检查 GitHub 更新。
svg-article-illustrator
by cat-xierluoAI驱动的SVG文章配图生成工具，支持动态SVG、静态SVG和PNG导出三种输出模式。当用户需要为文章生成配图、创建SVG插图、将SVG转换为PNG，或提到"为文章配图"、"生成插图"时使用此技能。
universal-media-downloader
by cat-xierluo输入各类视频网站/播客平台链接后，自动下载对应媒体文件并交付给用户。优先使用 yt-dlp 覆盖抖音(Douyin)、B站(Bilibili)、YouTube 等常见视频网站，也可用于可直接暴露音频地址的播客平台（如小宇宙单集链接）。当遇到 403/登录/年龄或地区限制时，支持使用 cookies.txt 重试；对于可能存在 DRM/加密或条款限制的平台（例如部分 Spotify 内容），应提示用户仅下载其有权保存的内容，并在不可下载时建议改用官方离线/导出渠道或提供原始 RSS/直链。注意：抖音图文笔记暂不支持自动下载，需手动处理。
wechat-article-fetch
by cat-xierluo抓取微信公众号文章内容，使用 Playwright headless 模式无弹窗后台抓取，支持动态加载内容，自动提取标题和正文并保存为 Markdown 文件。本技能应在用户需要抓取微信公众号文章内容时使用。检测到法律内容且项目中存在 legal-text-format 时自动链式调用格式化。默认保存到 skill 内部 archive 目录。
yuandian-law-search
by cat-xierluo元典法条与案例检索。本技能应在需要查询中国法律法规条文、检索相关案例、为法律分析提供数据支撑时使用。
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.