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...
mingshi
by Cosmofang中文命理综合技能，用于用户请求"算命""算八字""看运势""占卜""合婚""看风水""今日运势""紫微斗数""奇门遁甲""梅花易数""六爻""流年大运""事业财运婚姻分析"等场景；关键词包括：八字、四柱、命理、紫微、奇门、风水、占卜、运势、合婚、每日运程。/ Chinese metaphysics skill for requests like "read my fortune", "BaZi chart", "daily horoscope", "feng shui", "marriage compatibility", "ZiWei chart", "QiMen divination", "yearly luck", "career & wealth reading", "I Ching divination"; keywords include: BaZi, Four Pillars, ZiWei DouShu, Qi Men Dun Jia, Feng Shui, divination, horoscope, fortune telling, Chinese astrology, daily fortune, lucky color, marriage compatibility.
weather-daily
by Cosmofang每日天气推送 Skill — 早晨推送今日天气（温度/穿衣/出行建议），晚间推送明日预告， 支持一周预报、极端天气预警、空气质量监测。基于城市设置，无需 API Key， 通过 WebSearch 实时获取天气数据。 触发词：今天天气、天气预报、明天天气、本周天气、穿衣建议、下雨吗、天气怎么样、 开启推送、空气质量问题、台风预警、暴雨预警。/ Daily weather push: morning briefing (today's weather, outfit/commute tips), evening preview (tomorrow), weekly forecast, extreme weather alerts, air quality monitoring. City-based, no API key needed, uses WebSearch.
daily-fitness
by Cosmofang每天推荐一套5-15分钟快速运动方案，含动作示意和计时器，无需器材。Daily 5-15 min no-equipment workout with interactive timer. Trigger on：今日运动、每日锻炼、今天练什么、daily fitness、daily workout、quick workout、健身、拉伸、office workout。
english-daily
by Cosmofang每日英语学习 Skill — 词汇、句子、语法训练，内置单词库（A1-B2），间隔重复记忆算法，每日推送单词+句子，测验练习，进度追踪连续打卡。触发词：学英语、英语单词、今日单词、英语练习、测验、我的进度、开启推送。/ Daily English learning: vocabulary, sentences, grammar. Built-in A1-B2 word bank, spaced repetition, daily push, quiz, progress tracking, streaks.
daily-idiom
by Cosmofang每日成语/俗语学习 — 每天一个中文成语或俗语，含故事典故、用法、例句，中英双语，测验打卡，学中文必备。Daily Chinese idiom — story usage examples quiz bilingual EN/CN, perfect for Chinese learners. Trigger on: 成语、每日成语、今日成语、俗语、学成语、成语故事、中文学习、idiom、Chinese idiom、chengyu、learn Chinese。
career-news
by CosmofangDaily profession-targeted news from X (Twitter), Google News, Grok, and global media. Supports bilingual (zh/en), multi-profession subscriptions, keyword filters, and scheduled morning push. Users can subscribe to news from multiple professions beyond their primary one.
newstoday
by CosmofangNewsToday solves information overload for users who want to stay informed without spending an hour checking scattered sources. Instead of manually browsing Weibo, Zhihu, Baidu, and news apps separately, NewsToday aggregates, deduplicates, and summarizes the most important stories into a single readable briefing delivered at the right time. Every morning, NewsToday pushes a curated briefing of 10 top stories spanning politics, finance, technology, international affairs, and society — pulled from both RSS feeds (Sina News, The Paper, 36Kr, BBC Chinese, Reuters Chinese) and real-time WebSearch, each with a 2-sentence summary and source attribution. Every evening, a recap highlights what developed throughout the day and previews tomorrow's key events. Breaking news alerts fire automatically every 2 hours during daytime whenever a major story breaks — earthquakes, market crashes, political announcements — so users never miss what matters. Users can tune their experience by setting topic preferences — weighting f
today-in-history
by Cosmofang按月日查询历史上同日大事、诞辰与逝世等。当用户说：历史上的今天发生了什么？3 月 15 日有什么大事？或类似历史纪事问题时，使用本技能。
seo-audit
by CosmofangAudit and optimize any website's SEO + GEO (AI/LLM visibility) + Core Web Vitals, then fix what's broken. Runs a portable, zero-dependency hard-gate audit over a build output directory (Astro/Next/Hugo/Jekyll/plain HTML) and a live-URL crawl/GEO audit (robots.txt AI-crawler policy, sitemap, llms.txt, on-page JSON-LD, canonical, security headers). Includes a battle-tested LCP playbook (7.5s → 1.5s mobile on the reference site): render-blocking CSS, critical-CSS split, font preload discipline, third-party JS deferral. Use when asked to: check/improve a site's SEO, raise a Lighthouse/PageSpeed score, fix slow LCP / Core Web Vitals, make a site discoverable by AI agents (ChatGPT/Claude/Perplexity/Gemini), add structured data, set up robots/sitemap/llms.txt, or review a site before launch. Distilled from the reference site's production build-time SEO gates.
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.