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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smoothui-component-craft
by educlopezCreate, improve, fix, or review SmoothUI components with production-quality animations, accessibility, and performance. Orchestrates interface-craft, web-design-guidelines, rams, and vercel-react-best-practices skills for high-quality output. Use when the user wants to build a new component, add a variant, improve an existing component, fix a component bug, or review component quality in the SmoothUI project. Triggers on "create component", "build component", "new component", "add component", "improve component", "fix component", "review component", "add variant", "refactor component", or any component work in the smoothui monorepo.
codevator
by educlopezControl codevator — background music and sounds for AI coding agents. Use when the user mentions music, sounds, elevator music, background audio, coding music, volume, mute, sound modes, lo-fi, nature sounds, ambient, retro, focus music, or /codevator. Also use when the user wants to set up codevator with a new agent, check playback stats, manage sound profiles, import custom sounds, or preview available sounds.
ui-craft
by educlopezUse for UI design and implementation work to avoid generic AI-looking interfaces. Provides anti-slop rules, a required discovery phase before coding, and guidance for layout, typography, color, motion, accessibility, dashboards, tables, landing pages, theming, and polish. Trigger when editing UI code or reviewing and refining components, pages, screens, layouts, animations, responsive behavior, or design systems.
ui-craft-dense-dashboard
by educlopezDense dashboard / admin / Bloomberg / Retool / data-heavy internal tools. Locked knobs: CRAFT=7, MOTION=3, DENSITY=9. IBM Plex + mono numbers, semantic palette, 4/8px grid, sparklines, tabular-nums. Trigger on: dashboard, admin panel, data-dense, analytics, Bloomberg-like, Retool-like.
ui-craft-editorial
by educlopezEditorial / magazine / long-form / Medium / Substack / content-heavy UIs. Locked knobs: CRAFT=9, MOTION=4, DENSITY=3. Serif display + humanist body, wide reading column, drop caps, OpenType. Trigger on: editorial, magazine, long-form, blog, Medium-like, Substack-like.
ui-craft-minimal
by educlopezMinimal / clean / Linear / Notion / Vercel / whitespace-heavy UIs. Locked knobs: CRAFT=8, MOTION=3, DENSITY=2. Monochrome + one accent, Inter/Geist, hairline borders over shadows. Trigger on: minimal, clean, Linear-like, Notion-like, Vercel-like, whitespace-heavy.
ui-craft
by educlopezUse for UI design and implementation work to avoid generic AI-looking interfaces. Provides anti-slop rules, a required discovery phase before coding, and guidance for layout, typography, color, motion, accessibility, dashboards, tables, landing pages, theming, and polish. Trigger when editing UI code or reviewing and refining components, pages, screens, layouts, animations, responsive behavior, or design systems.
unhappy
by educlopez"State-first design pass — inventories and implements all non-happy states (loading, empty, error, partial, conflict, offline) before the happy path, and refactors impossible boolean state to proper state machines. Use when starting a new screen, reviewing an existing one for edge-case gaps, or when the user says "handle the error state" / "add loading states" / "what happens when data is missing". Invoke when the user asks for unhappy on their UI, or mentions 'unhappy' alongside design / UI / frontend work."
ui-craft-dense-dashboard
by educlopezDense dashboard / admin / Bloomberg / Retool / data-heavy internal tools. Locked knobs: CRAFT=7, MOTION=3, DENSITY=9. IBM Plex + mono numbers, semantic palette, 4/8px grid, sparklines, tabular-nums. Trigger on: dashboard, admin panel, data-dense, analytics, Bloomberg-like, Retool-like.
ui-craft-editorial
by educlopezEditorial / magazine / long-form / Medium / Substack / content-heavy UIs. Locked knobs: CRAFT=9, MOTION=4, DENSITY=3. Serif display + humanist body, wide reading column, drop caps, OpenType. Trigger on: editorial, magazine, long-form, blog, Medium-like, Substack-like.
ui-craft-minimal
by educlopezMinimal / clean / Linear / Notion / Vercel / whitespace-heavy UIs. Locked knobs: CRAFT=8, MOTION=3, DENSITY=2. Monochrome + one accent, Inter/Geist, hairline borders over shadows. Trigger on: minimal, clean, Linear-like, Notion-like, Vercel-like, whitespace-heavy.
adapt
by educlopez"Responsive layout pass covering breakpoints, touch targets, safe areas, and fluid type. Use when the UI has layout or touch issues on mobile/tablet, when adding a new screen that hasn't been tested across viewports, or when the user says "make it responsive" / "fix mobile layout". Invoke when the user asks for adapt on their UI, or mentions 'adapt' alongside design / UI / frontend work."
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.