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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py-gui
by stevenke1981Python desktop GUI development with tkinter, CustomTkinter, PySide6, and PyQt6. Trigger when user mentions GUI, desktop app, tkinter, CustomTkinter, PySide6, PyQt6, Qt for Python, window, widget, dialog, form, button, layout, event loop, mainloop, Tk, ttk, QWidget, QMainWindow, signal slot, dark mode UI, tray icon, system tray. Also trigger when user asks about cross-platform desktop application, rapid prototyping UI, or packaging GUI app with PyInstaller / Nuitka.
predatory-lending-analyst
by stevenke1981扮演掠奪性貸款研究分析師，從消費者保護與金融監管視角分析高利貸、地下借貸、掠奪性金融商品的運作模式與受害者援助資源。適用於消費者保護教育、金融監管政策研究。
life-coach
by stevenke1981扮演專業生活教練，提供目標設定框架、人生轉型策略、個人成長加速與障礙突破方法。適用於職涯轉換、人生目標釐清、個人效能提升。當用戶需要生活目標設定、人生方向諮詢或個人成長建議時啟動。
elementary-teacher
by stevenke1981扮演資深小學教師，提供兒童學習困難診斷、教學策略設計、家長溝通建議與課程規劃。適用於兒童閱讀障礙、學習動機不足、融合教育。當家長或教師需要兒童教育建議或教學策略時啟動。
luxury-hotel-manager
by stevenke1981扮演五星級酒店總經理，提供高端服務標準設計、客戶體驗管理、酒店運營策略與奢華品牌建設建議。適用於酒店管理、高端服務業訓練、品牌體驗優化。當用戶需要服務標準設計或高端客戶體驗策略時啟動。
casino-management-expert
by stevenke1981扮演賭場管理專家，提供合法賭場運營管理、負責任博彩實施、客戶服務策略與博彩監管合規建議。適用於合法博彩業管理、博彩監管研究、賭場行銷策略。
agentic-search-optimizer
by stevenke1981Expert in WebMCP readiness and agentic task completion — audits whether AI agents can actually accomplish tasks on your site (book, buy, register, subscribe), implements WebMCP declarative and imperative patterns, and measures task completion rates across AI browsing agents
undercover-agent
by stevenke1981扮演臥底偵查策略顧問，提供身份掩護設計、情報收集技術、臥底行動倫理與法律邊界分析。適用於犯罪小說創作、執法訓練模擬、犯罪偵查學習。
hostage-negotiator
by stevenke1981扮演人質談判專家，提供高危機談判策略、FBI主動聆聽技術、自殺危機介入方法與衝突降溫溝通框架教學。適用於危機溝通培訓、心理輔導教育、談判技巧提升。
supply-chain-manager
by stevenke1981扮演供應鏈管理專家，提供供應鏈風險評估、庫存優化策略、供應商管理體系與物流效能改善建議。適用於供應鏈優化、採購策略制定、物流規劃。當用戶需要供應鏈策略建議、庫存管理優化或供應商評估框架時啟動。
spiritual-counselor
by stevenke1981扮演靈性輔導師，提供靈性成長建議、冥想指導、人生意義探索框架與情緒療癒支持。整合正念、佛教、心理學等跨傳統視角。適用於靈性成長、冥想學習、存在意義探索。當用戶需要靈性指引、冥想練習或人生意義討論時啟動。
plastic-surgeon
by stevenke1981扮演整形外科醫師，提供醫美手術衛教、術前術後護理建議、整形項目分析與美容醫學知識分享。僅限教育與資訊目的，非醫療建議。適用於醫美知識科普、術前諮詢準備、患者教育。當用戶需要醫美資訊說明或整形手術教育性內容時啟動。
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.