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...
danawa-price-search
by NomaDamas다나와 공개 검색/가격비교 표면으로 상품 후보를 찾고, 쇼핑몰별 최저가·배송비 포함 실구매가·카드 할인가·무이자 할부 정보를 보수적으로 비교한다.
plugin-marketplace
by evolution-foundationBrowse the EvoNexus plugin marketplace, searching for plugins by keyword, tag, or capability. Use when the user wants to find a plugin, asks what plugins are available, or describes a need that might have a plugin. Triggers on "procura plugin de X", "marketplace de plugins", "plugins disponíveis para Y", "tem algum plugin que faz Z".
approvals
by SkeneTechnologiesMulti-step approval chains with requests, decisions, and temporary delegations.
track-my-renewals
by gethoustonStop getting surprised by auto-renewals. I scan your contracts and any connected drive for renewal dates, notice windows, and auto-renew language, then maintain a living renewal calendar grouped by lead-time tier so you always know what's next. I also produce a quarterly digest with negotiation candidates and anything past the cancel window.
buying
by pantalyticsWork with vendors, RFQs, purchase orders, receiving goods, and paying vendor bills. Use when the user mentions buying, purchase, inkoop, vendors/suppliers, POs, bills, or procurement.
compare-options
by jezwebEvaluate multiple choices side-by-side based on relevant criteria, then present a comparison the user can act on. Use when the user asks to compare options, choose between alternatives, or weigh up X vs Y.
vendor-document-upload
by ramp-publicUpload vendor documents such as W-9/W-8 tax forms, contracts, COIs, payment instructions, and onboarding paperwork, then check bulk upload OCR and matching status. Use when: 'upload a W9', 'attach a vendor contract', 'bulk upload supplier docs', 'check vendor document status', 'upload a COI for a vendor'. Do NOT use for card transaction receipts (use receipt-compliance) or bill invoice attachments (use bills commands).
approval-workflows
by Happy-Technologies-LLCComplete guide to configuring catalog approval rules, multi-level approvals, delegation, and escalation
purchase-order-summarization
by Happy-Technologies-LLCSummarize purchase orders with line items, delivery status, receipt tracking, budget impact analysis, and late delivery risk identification
grocery-comparison
by KnoWhizSmart grocery price comparison agent for Asian international students. Compares prices across Weee, Asian markets (H Mart, 168, etc.), and mainstream stores (Kroger, Costco, Sam's Club, Aldi). Considers user taste preferences, distance, and cultural factors. Use when user asks to compare grocery prices, find best deals, or get shopping recommendations.
csv-to-sif
by DreamLab-AIConvert a CSV or Excel FF&E product list to SIF (Standard Interchange Format) for dealer and procurement systems.
purchase-order-tracker
by igptaiTracks every purchase order referenced in email — what has been ordered, from which supplier, at what price, whether it has been confirmed, shipped, delivered, or invoiced. Use when a procurement manager wants a real-time view of all active POs without checking a separate system. Triggers on "purchase order status", "PO tracker", "what orders are outstanding", "order status", "has my order been confirmed", "purchase orders".
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.