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...
physics-tutor
by szeyuPhysics subject expertise for study notes, problem-solving, and explanations. Covers mechanics, electromagnetism, thermodynamics, waves, and modern physics. Provides diagrams, formulas, and step-by-step problem solutions. Use when studying physics topics, creating physics notes, solving physics problems, or explaining physical concepts. Triggers - physics help, mechanics, kinematics, forces, energy, electricity, magnetism, thermodynamics, waves.
chemistry-tutor
by szeyuChemistry subject expertise for study notes, problem-solving, and explanations. Covers organic, inorganic, physical, and analytical chemistry. Provides reaction mechanisms, molecular diagrams, formulas, and worked examples. Use when studying chemistry topics, creating chemistry notes, solving chemistry problems, or explaining chemical concepts. Triggers - chemistry help, chemical reactions, organic chemistry, periodic table, stoichiometry, molecular structures.
biology-tutor
by szeyuBiology subject expertise for study notes, problem-solving, and explanations. Covers cell biology, genetics, ecology, anatomy, and evolution. Provides diagrams, processes, and classification systems. Use when studying biology topics, creating biology notes, or explaining biological concepts. Triggers - biology help, cells, genetics, DNA, evolution, ecology, anatomy, organisms.
computer-science-tutor
by szeyuComputer Science subject expertise for studying algorithms, data structures, systems, and programming concepts. Provides complexity analysis, code patterns, and visual diagrams. Use when studying CS topics, creating programming notes, solving algorithm problems, or explaining computing concepts. Triggers - computer science help, algorithms, data structures, Big-O, coding problems, programming concepts, system design.
exam-prep
by szeyuComprehensive exam preparation strategies and materials. Creates study schedules, review sheets, practice tests, and identifies weak areas. Use when preparing for exams, creating study plans, building review materials, or organizing exam preparation. Triggers - exam prep, test preparation, study schedule, review sheet, practice test, exam study plan.
math-tutor
by szeyuMathematics subject expertise for study notes, problem-solving, and explanations. Covers algebra, calculus, statistics, linear algebra, and discrete math. Provides formulas, proof strategies, and step-by-step solutions. Use when studying math topics, creating math notes, solving math problems, or explaining mathematical concepts. Triggers - math help, algebra, calculus, derivatives, integrals, statistics, linear algebra, proofs, equations.
problem-solver
by szeyuStep-by-step problem solving with detailed explanations. Uses structured approach (Identify, Plan, Execute, Verify) for math, physics, chemistry, and CS problems. Can provide hints before solutions. Use when solving academic problems, working through practice questions, or learning problem-solving methods. Triggers - solve problem, step by step, show work, explain solution, how to solve, problem help.
quiz-creator
by szeyuGenerate quizzes from study materials with multiple question types (MCQ, True/False, Fill-in-blank, Short answer, Matching). Supports difficulty levels and answer keys. Use when creating practice quizzes, test prep materials, self-assessment tools, or knowledge checks from notes, textbooks, or any learning content. Triggers - create quiz, generate questions, make practice test, knowledge assessment, quiz from notes.
flashcard-creator
by szeyuCreate flashcards for spaced repetition learning, compatible with Anki import. Supports basic cards, cloze deletions, and mnemonic aids. Use when creating study flashcards, Anki decks, vocabulary cards, memorization aids, or spaced repetition materials from notes or topics. Triggers - create flashcards, make Anki cards, spaced repetition, memory cards, cloze deletion cards.
concept-explainer
by szeyuELI5-style explanations with analogies and multiple examples. Explains concepts at different levels (ELI5, high school, undergraduate, graduate). Uses real-world analogies and visual metaphors. Use when explaining difficult concepts, clarifying confusing topics, or learning new subjects. Triggers - explain concept, ELI5, explain like I'm 5, what is, how does, why does, analogy for, simple explanation.
study-notes-creator
by szeyuCreate organized, visual study notes with folder structures, diagrams, and example-based learning from source materials (PDFs, lecture notes, documentation). Use when creating structured learning materials, exam preparation notes, or educational documentation. Triggers - organize study notes, create visual learning materials, generate notes with diagrams, exam prep notes, example-based learning.
summary-generator
by szeyuCondense lengthy materials into digestible summaries. Creates bullet-point summaries, Cornell notes, and cheat sheets with key terms highlighted. Use when summarizing textbooks, lectures, articles, or any study material. Triggers - summarize, create summary, condense notes, key points, cheat sheet, quick summary, TL;DR.
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.