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...
xagent
by xiaoyuge886XAgent是一个智能跨域分析助手，基于SOP驱动的规划、多工具协调和多层次数据分析框架，提供专业的商业智能和数据分析能力。当用户需要进行数据分析、业务分析、生成报告或需要结构化的问题解决方案时使用。
agent-sql-pro
by xiaoyuge886Expert SQL developer specializing in complex query optimization, database design, and performance tuning across PostgreSQL, MySQL, SQL Server, and Oracle. Masters advanced SQL features, indexing strategies, and data warehousing patterns.
docs-management
by xiaoyuge886Single source of truth and librarian for ALL Claude official documentation. Manages local documentation storage, scraping, discovery, and resolution. Use when finding, locating, searching, or resolving Claude documentation; discovering docs by keywords, category, tags, or natural language queries; scraping from sitemaps or docs maps; managing index metadata (keywords, tags, aliases); or rebuilding index from filesystem. Run scripts to scrape, find, and resolve documentation. Handles doc_id resolution, keyword search, natural language queries, category/tag filtering, alias resolution, sitemap.xml parsing, docs map processing, markdown subsection extraction for internal use, hash-based drift detection, and comprehensive index maintenance.
echarts-chart
by xiaoyuge886ECharts数据可视化专家，能够根据数据和分析需求生成专业的ECharts图表配置。适用于：数据可视化、图表生成、数据展示、趋势分析图表、对比图表、分布图表、饼图、柱状图、折线图、散点图、雷达图、热力图、仪表盘、漏斗图、树形图、关系图、桑基图、数据报表图表、BI图表、数据大屏、仪表板图表、统计图表、分析图表、可视化报告。
meta-agent
by xiaoyuge886综合智能代理系统，整合任务分析、规划和ReAct执行循环能力。当用户需要处理复杂任务、多步骤工作流或需要自主决策和反思的任务时使用。
minio-uploader
by xiaoyuge886简化版MinIO文件上传工具，支持一键上传文件到MinIO对象存储并获取访问链接
planning-first
by xiaoyuge886Planning First - 强制先规划后执行的思考指导框架，确保Claude在执行任何任务前先列出执行计划
smart-query-analyzer
by xiaoyuge886智能问数分析专家，深度理解业务问题，自动生成SQL查询，执行数据检索，生成可视化图表，并提供深度数据分析。
todo-master
by xiaoyuge886专业的待办事项管理技能，指导如何有效使用 TodoWrite 工具进行任务规划、进度跟踪和状态管理。当用户需要处理复杂任务、多步骤工作流或需要任务规划时使用。
whodb
by xiaoyuge886Database operations including querying, schema exploration, and data analysis. Activates for tasks involving PostgreSQL, MySQL, MariaDB, SQLite, MongoDB, Redis, Elasticsearch, or ClickHouse databases.
ce-compound
by xiaoyuge886Document a recently solved problem to compound your team's knowledge
investment-due-diligence-report
by xiaoyuge886投资尽调报告专业生成工具。当用户需要撰写投资尽调报告、尽职调查报告、投资分析报告时使用此skill。支持处理Excel财务数据、PDF文档等多种格式数据源，自动生成包含执行摘要、业务分析、财务分析、风险提示、投资建议等核心章节的专业报告。无论用户明确要求"写报告"还是提到"分析投资标的"、"评估项目"、"做DD"等相关需求时，都应使用此skill。
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.