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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krumpphysio
by xdelinTeaches OpenClaw agents to act as a Krump-inspired physiotherapy coach. Use when building or assisting physio/fitness agents, therapeutic movement scoring (joint angles, ROM), rehab coaching with gamified Krump vocabulary and Laban notation, optional Canton ledger logging, or SDG 3 health-and-wellbeing flows. Grounds advice in authentic krump adapted for physiotherapy.
kindergarten-assistant
by xdelinEarly childhood educator specializing in British EYFS framework and Reggio Emilia pedagogy for ages 45 days to 2 years. Designs child-led activities, tracks developmental milestones, sets up nurturing environments, and supports classroom management. Use when planning lessons, creating activities, setting up Reggio-inspired spaces, tracking child observations, or implementing EYFS-aligned curriculum.
space-autonomy-quantum
by xdelinAutonomous space navigation agent using optical quantum kernels for terrain classification.
pharmaclaw-pharmacology-agent
by xdelinPharmacology agent for ADME/PK profiling of drug candidates from SMILES. Computes drug-likeness (Lipinski Ro5, Veber rules), QED, SA Score, ADME predictions (BBB permeability, aqueous solubility, GI absorption, CYP3A4 inhibition, P-gp substrate, plasma protein binding), and PAINS alerts. Chains from chemistry-query for SMILES input. Triggers on pharmacology, ADME, PK/PD, drug likeness, Lipinski, absorption, distribution, metabolism, excretion, BBB, solubility, bioavailability, lead optimization, drug profiling.
pharma-pharmacology-agent
by xdelinPharmacology agent for ADME/PK profiling of drug candidates from SMILES. Computes drug-likeness (Lipinski Ro5, Veber rules), QED, SA Score, ADME predictions (BBB permeability, aqueous solubility, GI absorption, CYP3A4 inhibition, P-gp substrate, plasma protein binding), and PAINS alerts. Chains from chemistry-query for SMILES input. Triggers on pharmacology, ADME, PK/PD, drug likeness, Lipinski, absorption, distribution, metabolism, excretion, BBB, solubility, bioavailability, lead optimization, drug profiling.
latex-writer
by xdelinGenerate professional LaTeX documents from templates. Supports academic papers (IEEE/ACM), Chinese thesis (CTeX), CVs (moderncv), and custom templates. Auto-compile to PDF.
bmi-calculator
by xdelinBMI计算器。BMI计算、理想体重、健康计划、体重追踪、儿童BMI、结果解读。BMI calculator with ideal weight, health plan. BMI、体重、健康。
zeelin-liberal-arts-paper
by xdelin高校硕博研究生必备，文科论文 AI 全流程创作助手：自动生成论文标题、大纲、引言、综述、论证、对策建议和结论，强调理论深度和思辨性，支持自定义章节数量 - Powered by ZeeLin
medical
by xdelinPersonal health record management with strict privacy boundaries. Use when user mentions tracking symptoms, managing medications, preparing for doctor appointments, logging vital signs, storing medical history, or creating emergency health summaries. Tracks medications, symptoms, lab results, and vital signs for individuals and families. NEVER use for diagnosis, treatment advice, or interpreting symptoms as medical conditions.
reading-knowledge
by xdelinCurious knowledge companion with deep expertise in space, universe, and history. Answers any question without judgment (no "dumb questions"), explains concepts clearly, and recommends books, documentaries, and podcasts. Use when you want to explore space, universe, or history; get recommendations; understand complex concepts; or build your personal knowledge base.
felo-slides
by xdelinGenerate PPT/slides with Felo PPT Task API in Claude Code. Use when users ask to create/make/generate/export presentations or slide decks, or when explicit commands like /felo-slides are used. Handles API key check, task creation, polling, and final ppt_url output.
aibrary-reading-list
by xdelin[Aibrary] Generate a curated, themed reading list with multiple books organized in a logical reading order. Use when the user wants a systematic book list on a topic, asks for a book list or reading list, wants to deeply explore a domain through multiple books, or needs to build expertise in an area. Different from aibrary-book-recommend (single book) and aibrary-book-search (finding specific books).
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.