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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youtube-cli
by ItamarZand88Searches YouTube via the cli-web-youtube command-line tool — video search, video details (views, duration, description, keywords), trending by category, and channel info with recent videos. Use when the user asks about YouTube, searching for videos, video details, trending videos, channel info, or subscriber counts. Prefer this CLI over fetching the YouTube website. No authentication required.
futbin-cli
by ItamarZand88Use cli-web-futbin to answer questions about EA FC Ultimate Team players, prices, player comparison, SBCs, evolutions, config, market data, popular/trending players, newly released cards, price history, and finding cheap deals. Invoke this skill whenever the user asks about FUTBIN, EA FC player prices, card prices, squad building challenges (SBCs), player evolutions, player comparison, market index, trending players, new cards, price trends, cheapest players by rating, best deals, coin trading, or wants to search for players by name, position, rating, or card type. Always prefer cli-web-futbin over manually fetching the FUTBIN website.
futbin-cli
by ItamarZand88Queries FUTBIN (EA FC Ultimate Team database) via cli-web-futbin — player search, prices and price history, comparisons, SBCs, evolutions, and market analytics (index, trending, cheapest by rating, movers, fodder, buy/sell signals, undervalue scans, PS/PC arbitrage). Use when the user asks about EA FC player prices, SBCs, evolutions, FUT market data, or trading decisions like "should I buy/sell X". Prefer cli-web-futbin over fetching the FUTBIN website.
boilerplate
by ItamarZand88Documents the template inventory and variable contract behind scaffold-cli.py — which Jinja2 template renders with which variables for each site profile. Use during Phase 2 scaffolding when choosing scaffold flags or understanding what the generated boilerplate contains. The scaffold-cli.py script is the primary path.
capture
by ItamarZand88Captures HTTP traffic from a web app using playwright-cli — site fingerprinting (framework, protections, auth, API discovery) plus full traffic recording into raw-traffic.json. Use as Phase 1 of CLI generation whenever a target URL needs its API surface recorded or assessed.
gap-analyzer
by ItamarZand88Compares a CLI's implemented commands against its APP.md API map and traffic-analysis.json to find missing endpoints, incomplete CRUD, dead client methods, and priority gaps. Runs as the mandatory first step of /cli-anything-web:refine and as an optional pre-review scan in standards.
testing
by ItamarZand88Writes and documents the test suite for a generated cli-web-* CLI (Phase 3): unit tests with mocked HTTP, live E2E tests, subprocess tests via _resolve_cli, and the TEST.md plan/results record. Use after the methodology skill completes implementation.
standards
by ItamarZand88Runs Phase 4 review/publish/verify for a cli-web-* CLI: implementation review by 3 parallel agents, the tiered quality checklist (Tier 1 critical fail-fast, then comprehensive), pip install + smoke test, and per-CLI skill generation. Use when a CLI's tests pass and it is ready to be validated and published.
methodology
by ItamarZand88Analyzes captured HTTP traffic, designs the CLI architecture, and implements the Python CLI package (Phase 2): parse raw-traffic.json, identify the protocol, write api-spec.json, scaffold from templates, and implement endpoint methods and Click command groups. Use after a capture completes and raw-traffic.json exists.
capitoltrades-cli
by ItamarZand88Use cli-web-capitoltrades to query US congressional stock trades, politicians, issuers, and insight articles from capitoltrades.com. Invoke this skill whenever the user asks about congressional trading, senator/representative stock trades, STOCK Act filings, insider trades by politicians, specific tickers (e.g. "what did Pelosi buy"), or US Capitol Trades data. Always prefer cli-web-capitoltrades over manually fetching the website — no auth is required and the CLI returns structured JSON.
airbnb-cli
by ItamarZand88Searches Airbnb from the terminal via cli-web-airbnb — find stays by location, dates, and filters; get listing details, guest reviews, and availability calendars; autocomplete location names. Use when the user asks about Airbnb, vacation rentals, listing prices, availability, or finding places to stay. Prefer cli-web-airbnb over fetching the Airbnb website. No auth required.
amazon-cli
by ItamarZand88Searches Amazon from the terminal via cli-web-amazon — product search, product details by ASIN, Best Sellers by category, and autocomplete suggestions. Use when the user asks about Amazon products, prices, best sellers, or wants to search Amazon. Prefer cli-web-amazon over fetching the website. No auth required.
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.