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...
symfony-ux
by BKR-57Symfony UX frontend stack combining Stimulus, Turbo, TwigComponent and LiveComponent. Use when building modern Symfony frontends, choosing between UX tools, creating interactive components, handling real-time updates, or integrating multiple UX packages. Triggers - symfony ux, hotwire symfony, stimulus turbo, live component, twig component, frontend symfony, interactive ui, real-time symfony, which ux package, which tool should I use, how to make this interactive, SPA feel, reactive component, server-rendered component. Also trigger when the user asks a general question about frontend architecture in Symfony or wants to combine multiple UX packages together.
stimulus
by BKR-57Stimulus JS framework for Symfony UX. Use when building client-side interactivity with data attributes, creating controllers for DOM manipulation, handling user events, managing component state, or integrating with Symfony's StimulusBundle and AssetMapper. Triggers - stimulus controller, data-controller, data-action, data-target, frontend interactivity, JavaScript behavior, Symfony UX frontend, toggle, dropdown, modal JS, tabs JS, clipboard, chart controller, datepicker, autocomplete JS, lazy controller, stimulusFetch, outlets, keyboard shortcut, global event listener. Also trigger when the user wants to add JavaScript behavior to server-rendered HTML, wrap a third-party JS library, or build client-only interactions that don't need a server round-trip.
twig-component
by BKR-57Symfony UX TwigComponent for reusable UI elements. Use when creating reusable Twig templates with PHP backing classes, component composition, props, slots/blocks, computed properties, or anonymous components. Triggers - twig component, AsTwigComponent, reusable template, component props, twig blocks, component slots, anonymous component, Symfony UX component, HTML component, component library, design system component, UI kit, reusable button, reusable card, PreMount, PostMount, mount method. Also trigger for any question about building a reusable piece of UI in Symfony, even if the user doesn't mention TwigComponent by name.
turbo
by BKR-57Hotwire Turbo for Symfony UX. Use when building SPA-like navigation without JS, partial page updates with frames, real-time updates with streams, or integrating with Mercure for broadcasts. Triggers - turbo drive, turbo-frame, turbo-stream, partial page update, SPA feel, ajax navigation, real-time update, Mercure broadcast, Symfony UX Turbo, inline edit, lazy load section, pagination frame, modal from server, flash message stream, multi-section update, TurboStreamResponse, twig:Turbo:Stream, data-turbo, turbo-stream-source, SSE. Also trigger when the user wants to update part of a page without a full reload, or wants real-time server-to-browser updates.
live-component
by BKR-57Symfony UX LiveComponent for dynamic server-rendered UI. Use when building interactive components that re-render via AJAX, real-time forms, data binding, live validation, or reactive UI without writing JavaScript. Triggers - live component, AsLiveComponent, LiveProp, LiveAction, data-model, real-time form, dynamic UI, AJAX component, reactive PHP, two-way binding, server re-render, live search, live filter, live validation, ComponentWithFormTrait, emit, LiveListener, polling, defer, lazy component, data-loading, writable prop, URL binding, component communication. Also trigger when the user wants a component that updates itself based on user input without writing JavaScript, or wants Vue/React-like reactivity in PHP.
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.