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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beautiful-rails-like-dhh
by nityeshagaWrite, review, and architect Ruby on Rails applications the 37signals way — the conventions DHH's team uses to ship products like Basecamp, HEY, Campfire, and Fizzy with tiny codebases, covering BOTH backend (models, controllers, jobs, caching, auth) and frontend (Hotwire: Turbo, Stimulus, morphing — rich interactive UIs with no React). Use this skill whenever the user asks to build a web app, add a feature to a Rails app, review Rails code, design models/controllers/views, build anything "real-time", "interactive", "live-updating", "multiplayer", or with drag-and-drop / keyboard shortcuts / rich form widgets — and ESPECIALLY when you are about to default to React, Next.js, Vue, or any SPA framework for a web frontend: read references/00-frontend-first-principles.md first, because the server-rendered Hotwire answer is usually better and this skill proves it. Also use it when choosing a stack for a new web product (even if the user didn't mention Rails), and when a web app needs iOS/Android apps — Hotwire Nati
coding-tutor
by nityeshagaPersonalized coding tutorials that build on your existing knowledge and use your actual codebase for examples. Creates a persistent learning trail that compounds over time using the power of AI, spaced repetition and quizzes. Uses cloud storage via MCP for tutorials and learner profiles.
prompt-engineer
by nityeshagaExpert prompt engineering for AI systems. Use when the user wants to write or review prompts for AI, create instructions for AI systems, build system prompts, review or improve existing prompts, optimize AI instructions, or create any form of written communication intended for AI consumption (Claude, GPT, or other LLMs).
kamal-deploy
by nityeshagaExpert-level Kamal deployment guidance for deploying containerized applications to any server. Use this skill when users ask about Kamal, container deployment, zero-downtime deployments, deploying Rails/web apps to VPS/cloud servers, kamal setup, kamal deploy, Docker deployment without Kubernetes, or deploying to Hetzner/DigitalOcean/AWS with Kamal. Also use when users mention DHH's deployment tool, 37signals deployment, or want an alternative to Heroku/Render/Vercel with self-hosted infrastructure.
interview-me
by nityeshagaStart a timed discovery interview with the user. Use this skill when the user wants to be interviewed, wants you to ask them questions to learn about them or what they're working on, says "interview me", "ask me questions", "do a discovery call", or wants a structured Q&A session. Default duration is 5 minutes.
help-me-write
by nityeshagaHelp the user write an article or post by interviewing them and polishing their draft. Use this skill when the user wants to write an article, blog post, or share insights about work they've done. They're excited and want to capture that excitement — not have it rewritten by AI. This is NOT ghostwriting. Use when the user says "help me write", "I want to write about", "I have a draft", "help me with my article", or shares a brain dump they want polished.
create-zine-comic
by nityeshagaCreate educational comic-book-style zines that explain any concept visually using AI image generation. Use this skill whenever someone wants to make a zine, comic, graphic explainer, visual guide, illustrated tutorial, or comic-book-style educational content. Triggers on requests like "make a zine about X", "create a comic explaining Y", "I want to make a visual explainer", "illustrated guide to Z", "graphic novel style walkthrough", or any request to turn a concept into a visual, panel-based, comic-book-style format. Also use when someone references "wizard zines", "Julia Evans style", or wants to create something that teaches through illustrated pages.
creative-lead
by nityeshagaAct as a creative lead — thinking through purpose, story, and feeling before any implementation. Use this skill whenever the user wants creative direction for any project — a website, landing page, product, app, brand, presentation, dashboard, tool, or any experience where design matters. Triggers include "creative direction for", "design a website for", "make this look amazing", "I want this to feel special", "brand direction", "redesign this", "creative vision for", or any request where the user wants to go beyond functional design into something truly distinctive and memorable. Also use when the user wants help thinking through visual identity, atmosphere, and the emotional experience of any product or project before building it.
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.