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...
use-ritmex-bot
by discountryUse when the task requires operating exchanges with the ritmex-bot CLI, including capability checks, market/account/position queries, order operations, strategy run, dry-run simulation, and JSON output parsing.
web3-report
by discountryThis skill should be used when the user asks to "generate web3 report", "create crypto report", "summarize web3 data", "daily web3 update", "send web3 summary", or wants a comprehensive report combining airdrops, fundraising, and token data. Generates consolidated Web3 reports with Telegram notification.
rootdata-scraper
by discountryUsing Browser MCP, scrape rootdata fundraising data (Token Issuance = No Token) from https://www.rootdata.com/Fundraising
scrape-airdrops
by discountryThis skill should be used when the user asks to "scrape airdrops", "get airdrop data", "find new airdrops", "track airdrops", "check airdrop updates", or mentions CryptoRank or DeFiLlama airdrops. Automates airdrop data collection using agent-browser CLI.
scrape-fundraising
by discountryThis skill should be used when the user asks to "scrape fundraising", "get funding data", "find new investments", "track crypto fundraising", "check RootData", or mentions Web3 fundraising rounds. Automates fundraising data collection from RootData using agent-browser CLI.
scrape-tokens
by discountryThis skill should be used when the user asks to "scrape tokens", "get token prices", "check crypto prices", "track token data", "get market cap", or mentions CoinGecko or CoinMarketCap data. Automates token market data collection using agent-browser CLI.
slack
by discountryControl Slack via the `slack` CLI to read, search, and manage messages, threads, files, reactions, channels, DMs, and canvases. Trigger on requests involving Slack messages, threads, URLs, channel history, unread or recent DMs, or sending/replying to messages (English or Chinese queries mentioning Slack).
svg-logo-maker
by discountryDesign and generate production-quality SVG logos in modern minimalist style. Use this skill PROACTIVELY whenever the user asks to create a logo, design a brand mark, generate an SVG icon, make a logomark, create a wordmark, build a brand identity symbol, or needs any kind of vector logo. Also triggers for requests like "make me a logo", "design an icon for my app", "create a brand symbol", "I need a logo for...", "generate SVG logo", or any task involving logo/icon/brand mark creation — even if they don't specifically mention "SVG" or "minimalist".
tdd
by discountryApply when the task requires implementing net-new behavior — features, modules, endpoints, integrations, or any additive change. Drives development through strict red-green-refactor with test-first slicing and deterministic verification.
teenage-engineering-ui
by discountryTeenage Engineering / Dieter Rams functionalist-hardware aesthetic: neutral molded panels, a single bold accent color, tactile knobs and buttons, LED and segmented displays, uppercase monospace labels, visible "device chrome" (screws, bezels, serial numbers, power LEDs), and playful retro-futurist technical detailing. Triggers: "TE style", "OP-1 style", "Pocket Operator look", "Braun / Dieter Rams style", "functionalist hardware UI", "retro hardware / synth / audio-gear interface", "device-like UI", "tactile / physical interface", "minimal skeuomorphic panels", or descriptions involving cream/charcoal panels, knobs, screws, LED dots, a single accent, monospace labels, phosphor/LCD screens, or anything that should look like hardware.
use-ctx7
by discountryFetch up-to-date library documentation via the ctx7 CLI. Use PROACTIVELY whenever any code change, feature design, or implementation or user request involves a project dependency — always query the matching version's docs first before writing code.
react-principles
by discountryReact best practices for component design, state management, and Effect discipline. Use when writing, reviewing, or refactoring React components, custom hooks, or any .ts/.tsx/.js/.jsx file that uses React.
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.