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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absolute
by maddhruvA focused development workflow engine for AI coding agents, invoked as `/absolute <command> [target]`. One skill, eleven commands. One sets it up: `init` (interview how you want absolute to behave + detect the stack once, then write JSON config — `.absolute.config.json` per project and `~/.absolute/config.json` for user defaults and per-project overrides — that every other command reads instead of re-detecting; non-blocking, the others soft-recommend it). Five cover the build loop you run every day — think → spec → plan → build → polish → document: `work` (end-to-end, phase-gated SDLC: relentless design interview → reviewed spec → dependency-graphed task board → safe-wave TDD execution → verification), `spec` (lightweight standalone design spec: codebase scan → bounded clarify pass → write a reviewed design doc to docs/plans → scored reviewer subagent → stop, no build), `ui` (polished, intentional interface design with concrete CSS/Tailwind values — typography, color, layout, dark mode, accessibility, animati
absolute-simplify
by maddhruvAutonomously simplifies code in your working changes or targeted files. Detects staged or unstaged git changes, analyzes for simplification opportunities following clean code and clean architecture principles, applies improvements directly, runs tests to verify nothing broke, and shows a structured summary with reasoning. Triggers on "simplify this", "refactor this", "clean up my changes", "absolute-simplify", "simplify my code", "make this cleaner", "tidy this up", "reduce complexity", "flatten this", "remove dead code", or when code needs clarity improvements, nesting reduction, or redundancy removal. Language-agnostic at base with deep opinions for JS/TS/React, Python, and Go.
absolute-work
by maddhruvEnd-to-end, phase-gated software development lifecycle for AI agents. Turns a ticket, task, plan, or migration into a validated design, a dependency-graphed task board, and verified code. Triggers on "build this end-to-end", "plan and build", "break this into tasks", "pick up this ticket", "grill me on this", "run this migration", "absolute-work this", or any multi-step development task. Relentlessly interviews to a shared design, writes a reviewed spec, decomposes into atomic tasks on a persistent markdown board, then peels tasks one safe wave at a time with test-first verification. Handles features, bugs, refactors, greenfield projects, planning breakdowns, and migrations.
absolute-documentations
by maddhruvDiátaxis-driven documentation writing, improvement, and auditing for AI agents. Writes public-facing product docs (tutorials, how-to guides, reference, explanation) and repo developer docs (README, CONTRIBUTING, ARCHITECTURE, ADRs, changelogs, runbooks), improves existing pages to their quadrant's standard, and audits whole doc sites against the Diátaxis map. Detects the docs stack (Fumadocs, Docusaurus, Starlight, MkDocs, VitePress, Mintlify, plain Markdown) and follows its conventions. Triggers on "write docs", "document this", "write a tutorial", "write a README", "improve this doc", "audit our docs", "restructure the documentation", or "absolute-documentations this".
absolute-ui
by maddhruvUse this skill when building user interfaces that need to look polished, modern, and intentional - not like AI-generated slop. Triggers on UI design tasks including component styling, layout decisions, color choices, typography, spacing, responsive design, dark mode, accessibility, animations, landing pages, onboarding flows, data tables, navigation patterns, and any question about making a UI look professional. Covers CSS, Tailwind, and framework-agnostic design principles.
ultimate-ui
by maddhruvUse this skill when building user interfaces that need to look polished, modern, and intentional - not like AI-generated slop. Triggers on UI design tasks including component styling, layout decisions, color choices, typography, spacing, responsive design, dark mode, accessibility, animations, landing pages, onboarding flows, data tables, navigation patterns, and any question about making a UI look professional. Covers CSS, Tailwind, and framework-agnostic design principles.
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.