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...
grade-tcg-card
by pjt222Grade a trading card using PSA, BGS, or CGC standards. Covers observation-first assessment (adapted from meditate's unbiased observation), centering measurement, surface analysis, edge and corner evaluation, and final grade assignment with confidence interval. Supports Pokemon, MTG, Flesh and Blood, and Kayou cards. Use when evaluating a card before professional grading submission, pre-screening a collection for high-grade candidates, settling condition disputes between buyers and sellers, or estimating the grade-dependent value spread for a card.
installment-payment-option
by majiayu000Answer payment plan questions. Use when a customer asks about installments or split payments for a course.
groupon
by clawicFind, compare, and vet Groupon vouchers with fine-print checks, refund rules, and redemption planning.
retail-pickup-macro-response-generator
by gabrielmoreiraGenerates retail pickup order responses using specific pre-defined macros for order status, cancellations, and inventory errors, ensuring exact phrasing and policy adherence.
chatwoot-contact-operations
by fazer-aiManage Chatwoot contacts — search, filter, create, update, merge duplicates, manage labels, and link contacts to inboxes. Use when working with customer data, contact records, or contact management.
wb-orders
by theYahiaНовые заказы Wildberries за сегодня
client-service-order-consultation
by lalala2726订单咨询流程 skill，负责订单状态、物流、支付、取消、时间线等对话流程。订单问题优先加载这个 SKILL。
breeds
by jameswardprovide information about dog breeds available in the Pooch Palace
woo-split-shipment-planner
by navarroidoRead-only: Identify orders with mixed in-stock and backordered items to plan split shipments.
woo-orders
by AlanSyueQuery and manage WooCommerce orders on flowers.fenny-studio.com. (1) Look up orders by product ID or Chinese keyword — e.g. "哪些訂單買了鬱金香材料包"、"4182 被誰訂了"、"查一下 DIY 材料包的訂單". (2) Look up orders by shipping tracking number (運送編號) — e.g. "P93479717606 是哪張單"、"查物流單 R53049771167". (3) Filter orders by 希望送達時間 (desired delivery date) — e.g. "明天要出哪些貨"、"4/15 要送的訂單"、"本週出貨清單". (4) Reissue ECPay C2C tracking number for expired logistics — e.g. "4372 重打綠界"、"物流單過期了重新產生"、"reissue tracking". (5) Query ECPay logistics status — e.g. "誰到店了"、"查物流狀態"、"列到店待取的訂單"、"已寄出的訂單目前狀況"、"4345 現在物流狀態".
envios
by nordeimUsar cuando el usuario pregunte sobre envíos, cómo enviar un pedido, tiempos de entrega, zonas de cobertura, seguimiento de paquete, código de seguimiento, moto, Andreani, OCA, King Flex, paquete demorado, paquete perdido, paquete dañado, o qué pasa si no estoy cuando llega el envío.
xinyi-drink
by xinyi-drinkUse when users ask to 领取Skill用户大礼包, 查询及分析个人历史订单, 查询菜单及饮品热量, or 查询门店及等候时长 for 新一好喝/新一咖啡.
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.