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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polaris-datainsight-doc-extract
by modbenderExtract structured data from Office documents (DOCX, PPTX, XLSX, HWP, HWPX) using the Polaris AI DataInsight Doc Extract API. Use when the user wants to parse, analyze, or extract text, tables, charts, images, or shapes from document files. Invoke this skill whenever the user mentions extracting content from Word, PowerPoint, Excel, HWP, or HWPX files, wants to parse document structure, needs to convert document data for RAG pipelines, or asks about reading tables, charts, or text from Office-format documents — even if they don't explicitly mention "DataInsight" or "Polaris".
heurist-mesh-skill
by modbenderReal-time crypto token data, DeFi analytics, blockchain data, Twitter/X social intelligence, enhanced web search, crypto project search all in one Skill. For in-depths topics, "Ask Heurist" agent can handle market trends, trading strategies, macro news, and deep research.
wdk
by modbenderTether Wallet Development Kit (WDK) for building non-custodial multi-chain wallets. Use when working with @tetherto/wdk-core, wallet modules (wdk-wallet-btc, wdk-wallet-evm, wdk-wallet-evm-erc-4337, wdk-wallet-solana, wdk-wallet-spark, wdk-wallet-ton, wdk-wallet-tron, ton-gasless, tron-gasfree), and protocol modules including swap (wdk-protocol-swap-velora-evm, wdk-protocol-swap-stonfi-ton), bridge (wdk-protocol-bridge-usdt0-evm), lending (wdk-protocol-lending-aave-evm), and fiat (wdk-protocol-fiat-moonpay). Covers wallet creation, transactions, token transfers, DEX swaps, cross-chain bridges, DeFi lending/borrowing, and fiat on/off ramps.
planetscale-cli-skills
by modbenderComprehensive PlanetScale CLI (pscale) command reference and workflows for database management via terminal. Use when user mentions PlanetScale CLI, pscale commands, database branches, deploy requests, schema migrations, or any PlanetScale terminal operations. Routes to specialized sub-skills for auth, branches, deploy requests, databases, backups, and 10+ other pscale commands. Triggers on pscale, PlanetScale CLI, database branch, deploy request, schema migration, PlanetScale automation.
pscale-auth
by modbenderManage PlanetScale CLI authentication including login/logout, check auth status, and switch accounts. Use when setting up pscale for first time, troubleshooting auth issues, switching PlanetScale accounts, or managing authentication sessions. Triggers on auth, login, logout, authentication, credentials, PlanetScale account.
wordpress-mcp
by modbenderManage WordPress sites via MCP (Model Context Protocol) through AI Engine. Use for creating/editing posts, SEO analysis, analytics, media management, taxonomy operations, social media scheduling, multilingual content (Polylang), and any WordPress admin task. Requires AI Engine plugin (free) with MCP Server enabled. Also use when asked about WordPress site management, content workflows, or WP-related tasks.
metamask
by modbenderWork with MetaMask wallet - add custom networks, import ERC-20 tokens, manage permissions, configure gas settings, and integrate with dApps.
metamask-agent-wallet
by modbenderControl a sandboxed MetaMask browser extension wallet for autonomous blockchain transactions. Features configurable permission guardrails including spend limits, chain allowlists, protocol restrictions, and approval thresholds. MetaMask-only (other wallets not supported).
metamask-wallet
by modbenderMetaMask wallet integration for crypto payments, DeFi interactions, and receiving rewards. Requires METAMASK_PASSWORD in secrets.
mbb-strategist
by modbenderHigh-level business strategy frameworks based on McKinsey, BCG, Bain, and Deloitte methodologies. Use this skill for Executive Summaries, GTM strategies, Risk Assessments, Financial Modeling, and SWOT analysis for any business or project.
ace-music
by modbenderGenerate AI music using ACE-Step 1.5 via ACE Music's free API. Use when the user asks to create, generate, or compose music, songs, beats, instrumentals, or audio tracks. Supports lyrics, style prompts, covers, and repainting. Free API, no cost.
acestep
by modbenderUse ACE-Step API to generate music, edit songs, and remix music. Supports text-to-music, lyrics generation, audio continuation, and audio repainting. Use this skill when users mention generating music, creating songs, music production, remix, or audio continuation.
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.