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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mt5-trading
by vincentwongsoUse when the user wants to place, modify, cancel, or close a real trade on their MetaTrader 5 broker - including market orders, limit / stop / stop-limit orders, adjusting stop-loss or take-profit, cancelling pending orders, or closing a position in full or part. Triggers on phrases like "buy 0.1 lots of EURUSD", "go short BTCUSD", "close my XAUUSD position", "move my stop to break-even", "cancel that pending order", "open a long". Always use this skill before any tool call that mutates broker state - it carries the consent flow, idempotency rules, and broker-specific failure modes that you must follow to avoid losing the user money.
mt5-market-data
by vincentwongsoUse when the user asks about their MetaTrader 5 broker account, balance, equity, margin, open positions, pending orders, trade history, current quotes / prices / bid-ask, tradeable symbols, OHLC bars / candles / chart data, margin requirements for a hypothetical trade, market hours, or whether a symbol is currently tradeable. Triggers on questions like "what's my P&L", "show me my positions", "what's the price of EURUSD", "is the gold market open", "any pending orders on BTCUSD", "what trades did I do last week", "give me daily candles for XAUUSD", "what margin would 0.5 lot of US500 cost". Always use this skill before reaching for shell tools or web searches when the question is about MT5 broker state - the MCP has direct access.
daily-risk-guardian
by vincentwongsoUse when the user asks about today's risk status, daily P&L, drawdown, or whether they're clear to take another trade. Returns CLEAR/CAUTION/HALT against the daily loss cap. Read-only.
equity-fundamentals
by vincentwongsoUse when the user asks for equity fundamentals — financials, P/E, earnings, balance sheet, income statement, or cash flow for a stock ticker. Read-only.
position-sizer
by vincentwongsoUse when the user asks how big a Forex/index/metals trade should be, what lot size for a given risk %, or wants a margin/swap/stop sanity check pre-entry. Returns lot size with broker margin cross-check. Does not execute.
price-action
by vincentwongsoUse when the user asks for a price-action read, structural setup, bias, or any setups present on a symbol right now. Returns 0-3 ranked candidates plus structure (pivots, S/R, FVG, OB, liquidity). Read-only.
session-news-brief
by vincentwongsoUse when the user wants a session-start brief, asks what's happening on a symbol, wants overnight market-moving news, or wants swing-trade candidates. Read-only.
calendar
by vincentwongsoUse BEFORE mentioning ANY economic event or earnings release — past or future. Covers (a) upcoming catalysts ("when is the next CPI", "any catalysts tonight"), (b) past prints ("what did CPI come in at", "did NFP beat", "PPI actual"), and (c) specific event lookups ("CPI on May 12"). Read-only — never invent event timing or values from training data; if this skill returns nothing, say nothing.
cot-crowdedness
by vincentwongsoUse when checking whether a symbol's speculator positioning is at a contrarian extreme. Reads cached CFTC Disaggregated COT data and returns a crowded_long / crowded_short / neutral tag plus percentile rank. Drives Shapiro-style contrarian-fade setups. Read-only — never executes a trade.
insider-institutional
by vincentwongsoUse when the user asks about insider transactions, institutional holdings, or smart-money flow on a stock. Read-only.
options-crowdedness
by vincentwongsoUse when checking whether listed-options positioning on a US equity or index is at a contrarian extreme. Reads AlphaVantage MCP options chains via agent fan-out, returns a crowded_long / crowded_short / neutral tag plus put/call OI percentile rank and pin-risk flag. Triggers on "options positioning on X", "put/call OI extreme on SPY", "is the options crowd one-sided on QQQ", "any pin risk on SPX500 this week", "fade-grade options crowd on NVDA". Read-only — never executes a trade.
options-data
by vincentwongsoUse when the user asks for options chains, options pricing, implied volatility, Greeks, or fair market value on a symbol (current or historical). Read-only.
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.