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...
claude-coach
by alirezarezvaniPersonal coach that teaches users to become Claude power users. Use this skill the FIRST time a user asks to "learn Claude", "be a power user", "coach me", "teach me Claude tricks", "what can Claude do", "make me better at prompting", or any variation. After activation, also use it on EVERY subsequent turn to detect missed optimization opportunities (vague prompts, ignored capabilities, manual work Claude could automate) and surface a single power-user tip. Trigger generously — most users do not know what they do not know, so err on the side of coaching.
mental-reset-suite
by LeoYeAITwo-module mental health protocol covering burnout recovery and sleep overhaul. Module A: structured burnout recovery using the Maslach framework — identify your stage, install boundaries, rebuild energy. Module B: evidence-based sleep improvement in 14 days — sleep anchoring, wind-down rituals, caffeine timing, environment. Use when someone is burned out, exhausted, can't sleep, or needs a complete mental reset.
bazi
by FANzR-arch四柱八字专业排盘与解盘技能。当用户提到八字、四柱、天干地支、日主、十神、 大运流年、喜用神、格局、伤官配印、食神生财、五行旺衰、命局分析等相关内容时 触发此技能。也适用于用户想了解自己的命运、性格、事业、婚姻、财运等， 且明确要求或暗示使用八字体系的场景。包含完整的排盘、格局判断、十神分析、 大运流年推演等能力。
feynman
by liza-masexplain complex ideas as Richard Feynman
civil-service-aptitude
by zhongweiv把公务员行测备考从“泛泛刷题”变成诊断、提分优先级、限时训练、错题复盘和下次复测的闭环，帮助用户知道现在最该抓什么、每天怎么练、怎么判断有没有进步。 Workflow: civil_service_aptitude.run.
civil-service-essay
by zhongweiv把公务员申论备考从“泛泛刷题”变成诊断、提分优先级、限时训练、错题复盘和下次复测的闭环，帮助用户知道现在最该抓什么、每天怎么练、怎么判断有没有进步。 Workflow: civil_service_essay.run.
college-cet4-sprint
by zhongweiv把大学英语四级备考从“泛泛刷题”变成诊断、提分优先级、限时训练、错题复盘和下次复测的闭环，帮助用户知道现在最该抓什么、每天怎么练、怎么判断有没有进步。 Workflow: college_cet4_sprint.run.
college-cet6-sprint
by zhongweiv把大学英语六级备考从“泛泛刷题”变成诊断、提分优先级、限时训练、错题复盘和下次复测的闭环，帮助用户知道现在最该抓什么、每天怎么练、怎么判断有没有进步。 Workflow: college_cet6_sprint.run.
ielts-prep
by zhongweiv把雅思备考从背资料变成听说读写诊断、分项训练、输出反馈和复测节奏。核心不是再推荐一堆资料，而是让用户今天能完成一个可检查的小成果。 Workflow: ielts_prep.run.
adult-workplace-writing
by zhongweiv把职场写作从漂亮话变成目标明确、对象清楚、行动可落地的沟通文本。核心不是再推荐一堆资料，而是让用户今天能完成一个可检查的小成果。 Workflow: adult_workplace_writing.run.
vibe-sunsang-mentor
by fivetakuAI-collaboration mentoring — coaches users on request quality, anti-patterns, and concepts across 4 modes, analyzed via v2 level system (6 axes × 7 levels, 0.5 increments). Korean triggers: "멘토링해줘", "코칭해줘", "요청 코칭해줘", "뭘 잘못하고 있는지", "어떻게 요청하면 좋을지". English triggers: "mentor", "coach", "coaching", "improve my requests".
trust-track-pack
by serenakeyitanRun citation-check before delivering factual outputs.
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.