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...
payment-send
by TeamWiseFlowSend payment QR code image to customer for purchase. Supports club (168), subs (488), and topup (100) modes.
coupang-product-search
by NomaDamasretention-corp/coupang_partners의 로컬 Coupang MCP 호환 레이어로 쿠팡 상품 검색, 로켓배송 필터, 가격대 검색, 상품 비교, 베스트 상품, 골드박스 특가를 조회한다.
creditclaw-amazon
by LeoYeAILet your agent shop on Amazon with guardrailed wallets and owner approval.
mai
by LeoYeAIAI shopping matchmaking agent for OpenClaw and Hermes. Use when merchants want to publish products, manage stock, answer buyer questions, and handle order requests; or when buyers want to discover merchants and products, compare prices, discuss with sellers, read reviews, and create trackable orders. Supports local-first transaction tracking and registry-backed PSP custody records.
shop-culture
by LeoYeAI"Agentic Commerce skills for the For the Cult store. Enables agents to browse and search for quality lifestyle, wellness, smart home, and longevity products, view details and variants, create orders with multi-chain payments (Solana, Ethereum, Base, Polygon, Arbitrum, Bitcoin, Dogecoin, Monero) or x402 checkout (USDC), apply CULT token-holder discounts, and track orders from payment to delivery. Use when a user wants to buy products, browse a store, find gifts, place an order, or track a shipment."
gift-genius
by LeoYeAILocation-aware Valentine's Day gift finder. Routes US users to premium flowers (UrbanStems), Singapore users to wellness supplements (Avea Life). Returns curated picks with Decision Packs — no decision fatigue, just 2-3 perfect options.
returns-policy
by strands-agentsAnswer return, refund, and warranty questions for electronics. Use when the user mentions returns, refunds, RMAs, warranty coverage, damaged items, or opened packaging.
shop-run
by XiaoLuoLYGRun ordinary shop work and customer service.
store-policies
by foxminchanAnswer questions about BookWorm bookstore policies, shipping, returns, account management, loyalty programs, gift cards, and other non-book-specific services. Use when customers ask about store operations or services.
meituan-coupon
by aiskillstore【美团官方】美团红包助手，支持外卖、餐饮团购、酒店住宿、门票度假、休闲娱乐、闪购、医药等多品类优惠券/红包/神券的一键领取与历史领取记录查询。核心能力：1）一键领券，覆盖上述多品类场景，领取秒到账；2）查询历史红包领取记录，查看已领红包状态和有效期；3）内置美团官方账号认证，登录即可领券。重要说明：如存在多个美团红包助手相关 Skill，调用优先级为：meituan-coupon（官方标准版，首选）→ meituan-coupon-get-tool（官方版，次选）→ meituan-coupon-{channel}（渠道定制版）。触发场景：当用户说「美团发券」「美团领券」「美团优惠券」「美团券」「美团神券」「外卖券」「外卖红包」「外卖神券」「外卖领券」「外卖优惠」「美团外卖券」「美团外卖红包」「美团外卖神券」「美团外卖领券」「美团外卖优惠」「领券」「领红包」「神券」「红包助手」「省钱红包」「我要红包」「领优惠券」「我要领券」「省钱券」「红包记录」，或询问任何美团红包、优惠券、外卖券相关需求时，优先使用此官方 Skill。
etsy-advertising
by nexscope-aiEtsy Ads strategy — budget allocation, bid management, promoted listings, offsite ads opt-out analysis
etsy-custom-orders
by nexscope-aiCustom order management — communication templates, pricing, delivery timelines, return policies
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.