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...
antd-issue-reply
by ant-designHelp maintainers reply to Ant Design GitHub issues following official guidelines. Use this skill when the user asks to handle issues, reply to issues, process issues, check issues, or manage issues for ant-design/ant-design repository. Also use when the user mentions "issue" in the context of antd, Ant Design, or GitHub issue management. This skill provides guidelines for classifying issues (Bug vs Feature Request), handling dosubot replies, using proper labels, writing polite responses, and knowing when to close issues.
antd-test-review
by ant-design审查 ant-design 测试用例是否值得保留。在用户要求验证测试 case、review 测试质量、判断测试是否合理、是否“用 A 证明 A”、是否重复、是否锁定实现细节，或决定测试应删除、保留还是改写时使用。
antd-version-release
by ant-designant-design 仓库的版本发布工作流。在用户提到发版、准备 release PR、升级发布版本号、执行正式 npm publish、或处理 release 分支与发布校验时使用。它不负责收集或生成 changelog；涉及 changelog 收集、整理、改写时应使用 changelog-collect。
antd-commit-msg
by ant-designGenerate a single-line commit message for ant-design by reading the project's git staged area and recent commit style. Use when the user asks for a commit message, says "msg", "commit msg", "写提交信息", or wants one-line text that covers all staged changes. Output should match the repository's existing commit style and summarize all staged changes in one line.
antd-create-pr
by ant-designCreate pull requests for ant-design using the repository's official PR templates. Use this skill when the user asks to create/open a PR, draft PR title/body, summarize branch changes for a PR, or otherwise prepare PR content. Judge by intent rather than fixed phrases; short colloquial requests still count if they are about creating a PR rather than discussing PR concepts.
antd-component-lookup
by ant-designLook up Ant Design React component documentation, props, and usage examples. Use when working with Ant Design (antd) components and needing API details, default values, or usage patterns.
antd-theme-customization
by ant-designCustomize Ant Design theme using Design Tokens and ConfigProvider. Use when adjusting visual styles, colors, spacing, or other theme properties in an Ant Design project.
antd-migration
by ant-designMigrate between Ant Design major versions. Use when upgrading from antd v4 to v5 or addressing breaking changes in component APIs.
changelog-collect
by ant-design收集 ant-design 两个版本之间的 PR 信息并整理 changelog 草稿，更新到 CHANGELOG.zh-CN.md 和 CHANGELOG.en-US.md 时使用。适用于收集 changelog、生成 changelog、更新 changelog、版本对比等场景。
pro-upgrade
by ant-designUse when the user wants to upgrade their Ant Design Pro project to the latest version. Triggers on: upgrade pro, pro upgrade, migrate pro, update pro, 升级, 迁移项目, "how to upgrade", "update to latest", "keep project up to date".
x-card
by ant-design当需要用 @ant-design/x-card 让 AI Agent 动态渲染富交互 UI 时使用——涵盖 XCard.Box、XCard.Card、A2UI v0.9 命令、数据绑定、Catalog、Actions 和流式渲染模式。
x-chat-provider
by ant-design专注于自定义 Chat Provider 的实现，帮助将任意流式接口适配为 Ant Design X 标准格式
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.