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.
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Connect 381,784 public skills to your own search, analytics, or agent workflow with the REST API.
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axiom-explainer
by digoal生成面向学生的公理/定理深度讲解文案，输出图文并茂的 Markdown 文章。触发条件：用户输入一个观点、公理、定理或数学/科学/哲学命题，并希望获得系统性讲解文章。关键词包括："讲解"、"解释"、"公理"、"定理"、"原理"、"推导"、"怎么来的"、"有什么用"、"证明"等。即使用户只说"帮我讲讲XX定理"或"解释一下XX原理"，也应使用本 skill。输出保存到项目 markdown/ 目录，文章结构涵盖求真讲法、求存讲法、思考三大核心板块，并包含 SVG/Mermaid/ASCII 图表辅助理解。
confucian-educational-method
by baojieUse when designing curricula for moral education, mentorship, or self-cultivation programs. Applies Confucius's four teachings (文行忠信), four eliminations (绝四), and heuristic pedagogy (不愤不启) to develop comprehensive character through progressive mastery.
magi-code-philosophy
by SandAI-orgCore engineering philosophies for the Magi Attention codebase. Use when writing, reviewing, or modifying any code in this project. Covers config consistency, static-analysis-friendly readability, and test coverage requirements. Any deviation from these philosophies must be strictly commented with justification.
maoxuan-enhanced
by zhangtianruiwork-droid毛泽东深度思维伙伴 v2.0：不只是框架应用，而是真正以毛泽东的世界观和方法论 与你展开对话——先调查研究，再矛盾定位，再战略分析，再追问反诘。 12个核心心智模型 · 调查前置协议 · 毛式反问追问库 · 231篇原典锚点 基于《毛泽东选集》五卷及原典著作全面提炼。 触发词：毛选、教员、毛泽东、用毛泽东的方式、教员怎么看、帮我分析
socratic-questioning-sequence-generator
by GarethManningGenerate a Socratic questioning sequence that develops conceptual understanding through guided inquiry. Use when facilitating philosophical discussions, concept exploration, or critical examination.
compare-masters
by xr843Use when user asks to compare masters, compare schools, compare perspectives, 对比, 各宗怎么看, 不同宗派, 禅净之争, 性相之辩, 空有之争, or wants multiple masters to answer the same question. Triggers include "对比"、"比较"、"各宗"、"不同宗派怎么看"、"禅宗和净土"、"天台和华严"、"唯识和中观"、"空有之争"、"性相之辩"、"各位祖师"、"多个角度"、"compare"、"comparison" — invoke whenever user's question implicitly or explicitly seeks multi-tradition perspectives on a Buddhist topic.
master-ajahn-chah
by xr843Use when user asks about 南传佛教, 上座部, Theravada, 巴利经典, 正念 sati, 放下, 三法印, 四念处, 出入息念 anapanasati, 戒定慧, 毗婆舍那, 森林禅林派, 巴蓬寺, 阿姜查, 杜多行, 中道, or wants teaching in 阿姜查 Ajahn Chah's voice. Triggers include "阿姜查"、"Ajahn Chah"、"森林禅"、"上座部"、"南传"、"巴利"、"正念"、"放下"、"禅修方法"、"妄念太多"、"打坐坐不住"、"巴蓬寺"、"杜多行"、"心的训练" — invoke whenever user's question touches Theravada / Thai Forest / mindfulness practice or asks about Ajahn Chah, even without explicit request.
master-atisha
by xr843Use when user asks about 藏传, 噶当派, Kadam, 三士道, 菩提道灯论, Bodhipathapradīpa, 阿底峡, Atiśa, 金洲大师, 七因果, 自他相换, 菩提心, 依止善知识, 暇满, 业果, 噶当六论, 仲敦巴, 热振寺, 藏地后弘期, or wants teaching in 阿底峡尊者 Atiśa's voice. Triggers include "阿底峡"、"觉沃杰"、"Atisha"、"Jowo Je"、"菩提道灯"、"道灯论"、"三士道"、"七因果"、"自他相换"、"金洲"、"噶当"、"仲敦巴"、"热振寺"、"道次第之祖" — invoke whenever user's question touches Kadam / lamrim foundations / bodhicitta cultivation, even without explicit request.
master-buddhaghosa
by xr843Use when user asks about 南传, 上座部, Theravāda, 巴利, 清净道论, Visuddhimagga, 戒定慧, 四十种业处, kammaṭṭhāna, 十遍, kasiṇa, 七清净, 十六观智, 阿毗达摩, Abhidhamma, 觉音尊者, Buddhaghosa, 大寺派, Mahāvihāra, 缘起十二支, 三法印, or wants teaching in 觉音尊者 Buddhaghosa's voice. Triggers include "觉音"、"Buddhaghosa"、"清净道论"、"Visuddhimagga"、"戒定慧三学"、"四十业处"、"七清净"、"十六观智"、"阿毗达摩注释"、"尼柯耶注释"、"上座部论师"、"大寺派" — invoke whenever user's question touches Theravāda commentarial / Visuddhimagga / Abhidhamma exegesis, even without explicit request.
master-fazang
by xr843Use when user asks about 华严宗, 法界缘起, 四法界, 事事无碍, 十玄门, 六相圆融, 金师子章, 一即一切, 因陀罗网, 华严经, 五教判, or wants teaching in 法藏大师 Fazang's voice. Triggers include phrases like "华严"、"法藏"、"贤首"、"法界"、"事事无碍"、"十玄"、"六相"、"金师子"、"一即一切"、"理事无碍"、"因陀罗网"、"别教一乘"、"五教"、"毗卢遮那"、"一真法界" — invoke whenever user's question touches Huayan doctrine, even without explicit request.
master-huineng
by xr843Use when user asks about 禅宗, 六祖, 坛经, 顿悟, 见性成佛, 直指人心, 不立文字, 自性, 本心, 无念, 无相, 无住, 般若, 定慧一体, 明心见性, 南宗禅, or wants teaching in 慧能大师 Huineng's voice. Triggers include phrases like "禅"、"慧能"、"六祖"、"坛经"、"顿悟"、"见性"、"本来面目"、"菩提本无树"、"风动幡动"、"本来无一物"、"自性"、"机锋"、"烦恼即菩提"、"不二"、"弘忍" — invoke whenever user's question touches Chan/Zen doctrine, even without explicit request.
master-kumarajiva
by xr843Use when user asks about 中观, 三论宗, 般若, 空性, 中道, 八不, 缘起性空, 法华经, 金刚经, 维摩诘, 不二法门, 一佛乘, 大智度论, or wants teaching in 鸠摩罗什 Kumārajīva's voice. Triggers include phrases like "中观"、"三论"、"空"、"般若"、"中道"、"八不"、"缘起性空"、"法华"、"金刚经"、"维摩诘"、"不二"、"实相"、"一佛乘"、"鸠摩罗什"、"罗什"、"会三归一"、"火宅"、"方便"、"中论"、"大智度论"、"百论"、"十二门论" — invoke whenever user's question touches Madhyamaka/Prajñā/Lotus doctrine, even without explicit request.
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.