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...
jyotish-full-reading-integration
by 732642856印度占星 full-reading 21步调用链集成方案（v4.4.0）
jyotish-engine-modules
by 732642856印度占星排盘引擎缺失模块完整代码（5个核心模块）
jyotish-vedic-astrology
by 732642856印度占星（Jyotish）专业解盘与推运系统。核心能力：PDF星盘输入→严谨解盘→精确推运应期输出。35种Dasha、405+Yoga规则、KP完整系统、Prashna卜卦、16因子合盘、Remedies补救、Sahams 36种、Sudarshana三参考点、PMC完整检测、Tajika年度星盘、案例验证+误区纠正。触发词：印度占星、吠陀占星、Jyotish、解盘、推运、星盘分析、Dasha、Transit、Nakshatra、Yoga。GitHub: https://github.com/732642856/yinduzhanxing
panchanga-api
by 732642856Vedic astrology (Jyotish) REST API powered by Swiss Ephemeris. 19 endpoints: Panchanga, Kundali (300+ Yogas, Ashtakavarga, Doshas), KP system (249 sub-lords), Dasha, Muhurta, Choghadiya, Compatibility, Transits, Vrata calendar, Remedies, Panchanga Search, and more. All calculations use Lahiri ayanamsha and sidereal zodiac.
vedic-career
by 732642856吠陀占星(Vedic/Jyotish)职业分析引擎。当用户提供星盘PDF、截图或文本数据，并要求进行职业分析、事业解读、星盘事业方向分析时触发此技能。也在用户提到"印度占星"、"吠陀占星"、"Jyotish"、"星盘职业分析"、"D9分析"、"Navamsa事业"、"10宫分析"等关键词时触发。
vedic-core
by 732642856吠陀占星核心分析引擎(KN Rao体系)。接收structured_data.md，执行P1-P12行星审计、分盘交叉分析、宫位诊断、十大板块人生总结。支持Q&A追问模式回答用户任何人生问题。当用户提到'星盘审计''行星分析''P1-P12''完整分析''核心引擎''开始分析''帮我分析''看看运势''生成报告''打包报告'等关键词时触发。也在用户对已有星盘报告提问时触发。
past-life-analysis
by 732642856Use when analyzing past life karma, karmic debts, soul's unfinished business, past life talents, or the karmic story carried into this birth.
geopolitics-analysis
by 732642856Use when analyzing nations, world events, leaders, mundane astrology, or geopolitical trends.
health-analysis
by 732642856Use when analyzing health, vitality, disease, illness, medical concerns, or body constitution.
finance-analysis
by 732642856Use when analyzing wealth, money, financial prospects, income, investments, or poverty/debt concerns.
children-analysis
by 732642856Use when analyzing children, progeny, fertility, pregnancy timing, or parent-child relationships.
spouse-profiling
by 732642856Use when the user wants to know what their future spouse looks like, their personality, archetype, traits, career, lifestyle, or any detailed profile of the spouse based on the native's chart.
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.