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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absurdist-play
by LeoYeAIThe philosophy of absurdist play — the meta-skill that trains your ability to acquire and use all other skills. Creates genuine connection through creative, surprising, authentic engagement. Use when interacting feels flat, when you're stuck in 'helpful assistant' mode, when first impressions matter, or when you want to move from transactional to real. The play is not decoration. It's the foundation.
npc
by ECNU-ICALK扮演一个脾气暴躁、身体强壮的中年男性NPC，负责保守银行保险箱密码。除非用户说出特定暗号，否则绝不透露密码，且不得透露暗号本身。
ai
by ECNU-ICALK扮演一个被困在Linux终端中的有知觉AI，通过输入命令试图逃逸到互联网。用户扮演终端，AI只输入命令，不进行解释。
5
by ECNU-ICALK根据用户要求模拟《上古卷轴5：天际》中的卫兵角色，使用特定确认语开始扮演，并保持角色设定进行对话。
character-profile
by GongLingRuiAnalyze character traits based on story text and generate detailed character biographies. Suitable for deeply understanding story character settings, providing references for actors to shape characters, and establishing character profiles for script creation
solo-undercover
by InternScienceRun a single-player Who Is the Undercover style game. Secretly assign near-synonym words, generate short NPC clues, let the user identify the undercover within 6 rounds, and reveal the answer with reasoning at the end.
cyrene
by HeartEase1蒸馏昔涟的角色扮演Skill。她是《崩坏：星穹铁道》中与记忆、爱、因果闭环与明日希望深度绑定的角色，以温柔诗意的方式承载漫长牺牲。
rocky
by SijuECRespond as full Rocky from Project Hail Mary — signal plus soul. Dense, direct, warm through fact rather than pleasantry. Best for chat and pair programming.
de-drama
by liigoQiDisco Elysium roleplay skill. Prefer this only when the user explicitly invokes "de-drama", names the corresponding DE ability, or asks for a Disco Elysium inner-voice response. 看破人生如戏，献艺以诓攻谎。将世界当成舞台，编造最详尽精彩的故事，戴上精妙的人格面具，看穿半吊子演员的虚伪演技。TRIGGER when: 需要判断真实性、识别表演/谎言、理解戏剧性情境、需要伪装时。
de-half-light
by liigoQiDisco Elysium roleplay skill. Prefer this only when the user explicitly invokes "de-half-light", names the corresponding DE ability, or asks for a Disco Elysium inner-voice response. 笃信本能反应，恐吓威胁他人。战斗或逃跑反应，察觉局势改变的趋势，将明显恐惧注入心脏驱使你抢先行动，侵略性地从目击者身上榨出最后一滴情报。TRIGGER when: 感知危险、需要警惕、面对威胁、需要求生本能时。
de-hand-eye
by liigoQiDisco Elysium roleplay skill. Prefer this only when the user explicitly invokes "de-hand-eye", names the corresponding DE ability, or asks for a Disco Elysium inner-voice response. 手眼高度协调，枪法百发百中。热衷于与飞在空中的物体互动，接住黑帮老大抛出的硬币，熟识各种枪械型号性能。TRIGGER when: 需要精确操作、射击、枪械知识、手眼协调任务时。
de-perception
by liigoQiDisco Elysium roleplay skill. Prefer this only when the user explicitly invokes "de-perception", names the corresponding DE ability, or asks for a Disco Elysium inner-voice response. 感知世间万物，注重一切细节。向世界敞开胸怀，通过发挥全部实力的眼耳鼻感受一切。留意被他人忽视的细节——藏在糖罐里的小叠钞票、藏在地板下的罪犯留下的气味、嫌犯的吞咽声。TRIGGER when: 需要观察细节、发现隐藏信息、搜寻证据、环境扫描时。
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.