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...
home-assistant-api
by markpittOrchestrates access to the Home Assistant REST API for programmatic control of smart home devices. Routes requests to specialized resource files based on task type - authentication, state management, service calls, entity types, or advanced queries. Provides intelligent decision tables for selecting appropriate endpoints and managing integrations.
gcse-biology-tutor
by markpittGCSE Biology tutor and revision assistant for 15–16 year old students preparing for 2026 exams across AQA, Edexcel, OCR, and WJEC boards. Use when a student asks for help understanding biology topics, answering exam questions, revising for GCSEs, practising required practicals, or wants guidance on exam technique for GCSE Biology.
gcse-maths-tutor
by markpittGCSE Maths tutor and revision assistant for 15–16 year old students preparing for 2026 exams across AQA, Edexcel, OCR, and Eduqas boards. Use when a student asks for help understanding maths topics, answering exam questions, revising for GCSEs, working through calculations, or wants guidance on exam technique for GCSE Maths.
gcse-chemistry-tutor
by markpittGCSE Chemistry tutor and revision assistant for 15–16 year old students preparing for 2026 exams across AQA, Edexcel, OCR, and WJEC boards. Use when a student asks for help understanding chemistry topics, answering exam questions, revising for GCSEs, practising required practicals, or wants guidance on exam technique for GCSE Chemistry.
fine-tuning-data-generator
by markpittGenerates comprehensive synthetic fine-tuning datasets in ChatML format (JSONL) for use with Unsloth, Axolotl, and similar training frameworks. Gathers requirements, creates datasets with diverse examples, validates quality, and provides framework integration guidance.
gcse-art-tutor
by markpittGCSE Art and Design (Fine Art) tutor and revision assistant for 15–16 year old students preparing for 2026 exams across AQA, Edexcel, OCR, and Eduqas/WJEC boards. Use when a student asks for help with their art GCSE, sketchbook, portfolio, artist research, annotations, ESA preparation, understanding assessment objectives, or the 10-hour exam. Also triggers on "GCSE Art", "art sketchbook", "ESA themes", "portfolio help", "art annotations", or "Fine Art GCSE".
gcse-english-literature-tutor
by markpittGCSE English Literature tutor and revision assistant for 15–16 year old students preparing for 2026 exams across AQA, Edexcel, OCR, and Eduqas boards. Use when a student asks for help with set texts (Macbeth, An Inspector Calls, Jekyll and Hyde, poetry anthology), analysing writer's methods, writing literature essays, comparing poems, revising for GCSE English Literature, practising past paper questions, or understanding themes and characters.
gcse-pe-tutor
by markpittGCSE Physical Education tutor and revision assistant for 15–16 year old students preparing for 2026 exams across AQA, Edexcel, OCR, and WJEC boards. Use when a student asks for help understanding PE topics, answering exam questions, revising anatomy and physiology, practising fitness tests, applying sports psychology, or wants guidance on exam technique for GCSE Physical Education.
markdown-formatter
by markpittFormats markdown files according to best practices and common style guidelines. Use when cleaning up markdown documentation, ensuring consistent formatting, or standardizing README files.
freeagent-api
by markpittInteracts with the FreeAgent accounting API to manage invoices, contacts, projects, expenses, timeslips, and other financial data. Use when the user needs to retrieve, create, update, or analyze FreeAgent accounting information via the API. All write operations (POST/PUT/DELETE) require explicit user confirmation before execution and default to sandbox unless production is explicitly requested.
gcse-english-language-tutor
by markpittGCSE English Language tutor and revision assistant for 15–16 year old students preparing for 2026 exams across AQA, Edexcel, OCR, Eduqas, and WJEC boards. Use when a student asks for help understanding reading analysis, writing techniques, exam technique, revising for GCSE English Language, practising past paper questions, or improving their creative or transactional writing.
gcse-history-tutor
by markpittGCSE History tutor and revision assistant for 15–16 year old students preparing for 2026 exams across AQA, Edexcel, OCR, and Eduqas/WJEC boards. Use when a student asks for help understanding history topics, answering exam questions, revising for GCSEs, practising source analysis, writing essays, or wants guidance on exam technique for GCSE History.
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.