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...
youtube
by npc-liveYouTube 内容创作全套。包括视频标题/描述/标签写作、Shorts 文案、 社区帖子（Community Post）写作、缩略图文案策略、SEO 优化、 推荐算法适配、频道增长策略、平台合规规则。 建议配合 copywriting-base 使用以获取通用文案能力。 触发词：YouTube、油管、YT、视频标题、视频描述、Shorts、社区帖子。
xiaohongshu
by npc-live小红书内容创作全套。包括种草文案风格、图文/视频格式规范、标题优化、标签策略、 审核规避（禁用词+限流规则）、CES 算法适配、最佳发布时间。 建议配合 copywriting-base 使用以获取通用文案能力。 触发词：小红书、RED、种草、笔记、小红书文案、小红书运营。
next-variant
by npc-live两个入口，一个出口。给定一个网站 URL 或一段内容描述，输出可用于生成 UI 的 skill 组合。
scene-video-generator
by npc-live根据分镜描述生成视频片段。支持多个 AI 视频生成后端：即梦 Jimeng、Kling 可灵、Runway、Pika、Vidu。输入场景描述+可选的数字人口播，输出视频片段。触发词：AI视频、生成视频、分镜视频、scene video、text to video、图生视频。
binance-square
by npc-live币安广场 (Binance Square) 内容创作全套。包括短帖/长文/视频描述写作、 Web3/加密货币专业文案风格、加密合规审核（NFA/DYOR）、标签策略、 推荐算法适配、风控规则。 建议配合 copywriting-base 使用以获取通用文案能力。 触发词：币安广场、Binance Square、BSQ。
Twitter/X 内容创作全套。包括推文/Thread 写作、简洁犀利的文案风格、 算法适配（回复权重>RT>Like）、hashtag 策略、风控规则、最佳发布时间。 建议配合 copywriting-base 使用以获取通用文案能力。 触发词：Twitter、X、推文、Tweet、Thread、推特。
solana-wallet
by npc-liveManage Solana and Polygon wallets, run Polymarket weather arbitrage, post to X/Twitter, and execute Raydium swaps — all from natural language.
solana-payments-wallets-trading
by npc-livePay people in SOL or USDC, buy and sell tokens, check prices, discover trending and new tokens, create and manage Solana wallets, stake SOL, earn yield through lending and managed vaults, borrow against collateral, set up DCA (dollar-cost averaging) and limit orders, provide liquidity across multiple DEXes, trade prediction markets, pay for APIs via x402, set up security permissions and spending limits, and track portfolio performance — all from the command line. No API keys, no private key env vars. Use when the user wants to send crypto, swap or trade tokens, browse what's trending, check balances, earn yield, borrow, set up recurring buys or limit orders, provide liquidity, bet on predictions, pay for web resources, or see how their holdings are doing.
tavily-search
by npc-live网页搜索与内容抓取工具。当用户需要搜索互联网信息、抓取网页内容、 查找最新资讯、研究某个话题、或获取某个 URL 页面的详细内容时触发。 底层使用 Tavily Search / Crawl API，通过 tavily-cli 执行。 触发关键词：搜索、查一下、找一下、抓取、crawl、search、查资料、联网查。
video-highlight
by npc-live给视频生成高光片段或封面图。触发词：帮我做视频高光、给视频加文字、做封面、做缩略图、thumbnail、cover图、提取高光、视频加字幕。
cover-gen
by npc-live社交媒体封面生成 + 视频首帧插入。从视频成片提取关键帧，按各平台规格 AI 生成封面， 最终将封面作为视频第一帧（0.1秒）合成到视频中。底层使用 media_gen (Gemini/OpenAI) + FFmpeg。 触发词：封面、cover、生成封面、封面制作、首帧、cover gen、thumbnail、视频封面。
digital-avatar
by npc-live数字人/虚拟形象生成和口播视频制作。支持多个后端：可灵 Kling、即梦 Jimeng、HeyGen、D-ID、Synthesia。输入形象描述或真人照片，输出数字人资源ID或口播视频片段。触发词：数字人、虚拟人、AI主播、avatar、口播视频、talking head。
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.