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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livewire-principles
by ohnotnowPrinciples for writing simple, maintainable Laravel/Livewire code. Use when writing Livewire components, tests, or Blade views. Focuses on avoiding over-engineering.
technical-overview
by ohnotnowGenerate a TECHNICAL_OVERVIEW.md file for any codebase. Automatically detects the tech stack, explores models/routes/services, and produces a concise reference document that helps future AI sessions (or humans) quickly understand the project without re-exploring. Use when starting work on an existing project, onboarding to a new codebase, or creating documentation for your team. Works with Laravel, Rails, Django, Node/Express, and other common stacks.
audience-credibility
by ohnotnowDefensive credibility check for deliverables (reports, dashboards, demos, presentations, web pages, marketing copy) aimed at a real human audience — especially when those readers have local context (a city, an institution, a profession) that lets them spot inaccurate or implausible details. Use this skill BEFORE generating the deliverable when it will mention specific places, buildings, organisations, distances, demographics, or named personas. ALSO use it as a final review pass on any visual or copy output before delivery, to catch design and copywriting tropes that have become recognisable "this came from an LLM" tells. Trigger reliably when the user mentions creating something for "my colleagues", "an audience", "a demo", "a presentation", "to share with stakeholders", or any output that needs to look credible and not AI-generated. Also trigger when the user names a specific institution, city, or audience their work is for. Especially important for demos meant to demonstrate AI capability — where one credi
uofg-design-system
by ohnotnowUniversity of Glasgow Design System — use this skill whenever creating HTML, CSS, React, or any web UI that should follow the University of Glasgow brand. Triggers on: UofG, University of Glasgow, gla.ac.uk, Glasgow University web, or any request to build web pages/components using the Glasgow design system. Also use when the user asks for a Tailwind config, CSS variables, or design tokens for the University of Glasgow. This skill provides colours, typography, spacing, grid, and component patterns from the official UofG design system (design.gla.ac.uk).
larastan
by ohnotnowSet up and run PHPStan/Larastan static analysis on Laravel projects with sensible defaults that filter out Laravel magic noise. Iteratively fix real issues and progressively increase analysis levels. Use when the user asks to: run phpstan, run larastan, set up static analysis, check code quality with phpstan, add phpstan/larastan to a project, or "analyse my code". Also use when the user mentions phpstan.neon configuration.
livewire-v4-upgrade
by ohnotnowWalk a developer through upgrading a production Laravel app from Livewire v3 to v4. Use when the user asks to upgrade Livewire, mentions the Livewire 4 upgrade guide, or wants to assess whether an app is ready for Livewire v4. Audit-first - establishes the lay of the land before any dependency changes.
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.