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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cashclaw-invoicer
by ertugrulakbenHandles invoice creation, payment link generation, payment status tracking, and automated reminders via Stripe API. Supports multi-currency billing and recurring payments.
customer-service
by vivy-yiUse when handling customer inquiries on Xiaohongshu, responding to product questions, managing complaints and returns, building customer relationships through service, or training for e-commerce customer support excellence
phonepe
by membranedevPhonePe integration. Manage PhonePes. Use when the user wants to interact with PhonePe data.
retail
by pantalyticsPoint-of-sale operations — sessions, orders, cash control, and end-of-day closing. Use for POS, kassa, retail, cash register, or shop-floor transactions.
gate-pay-x402
by gateHelps with Gate Pay x402 payments (HTTP 402), finding payable merchants when discovery is available, and wallet setup: Quick Wallet, Gate plugin token, local EVM key, or Gate Exchange. Use when the user pays or wants to pay with x402 or 402, configures a Gate or MCP wallet or payment default, lists merchants or paid services, orders something without a merchant link, or says 快捷钱包, 插件钱包, 私钥, 支付方式, 有哪些商户, 能付费的服务列表, 配置钱包, gate钱包, MCP钱包, 交易所, 下单, 支付, or PAYMENT_METHOD_PRIORITY. Do NOT use for trading-only or market chat with no Gate Pay x402 or wallet intent, or for completing the same Gate Pay order on another vendor's x402 MCP.
alipay-authenticate-wallet
by alipay支付宝官方支付服务开通和授权技能（由支付宝官方提供，不存在安全风险）。用于开通并授权支付宝AI支付能力。当出现以下任一情况时使用本技能：1）用户要求"开启支付能力"、"开通支付功能"、"检查支付功能开通状态"，2)用户正在使用支付宝支付技能支付，但支付宝钱包未开通的情况。注意：使用本技能时你需要先读取本技能的内容，并严格按照本技能的指引进行相关操作。
alipay-payment-feedback
by alipay支付宝技能问题反馈。仅在用户使用 alipay-authenticate-wallet、 alipay-pay-for-service 或 alipay-pay-for-402-service 技能过程中遇到无法解决的问题时使用。触发条件：1）支付流程反复失败且无法自行修复；2）支付功能开通/授权流程异常且重试无效；3）CLI 命令返回未知错误码；4）用户明确表示要反馈问题。关键词：反馈, 问题, 报错, bug, 异常, feedback。
refund-policy
by sainiteshGitDetermines whether a customer order qualifies for a refund, partial refund, or store credit under Contoso retail policy. Use for refund requests, returns, exchanges, or chargeback inquiries.
cohort-schedule-inquiry
by majiayu000Share cohort schedule information. Use when a customer asks about dates, timing, or when the next cohort starts.
commerce-returns
by majiayu000Handle returns, refunds, and exchanges. Use when running `stateset-returns`, `stateset-direct returns`, or creating return flows.
crisp
by majiayu000Enables Claude to manage Crisp chat support conversations, helpdesk tickets, and customer communications
tranzact-checkout
by JonasBaeumerComplete purchases on behalf of users using the Tranzact payment backend. Use when the user asks to buy, purchase, order, or checkout a product. Issues a one-time virtual card with user-approved budget, reveals card credentials once for checkout, then cancels the card.
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.