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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the-challenger
by fimokleiPre-launch red team analysis that identifies failure modes and validates assumptions before resource commitment. Use when evaluating new products/features/strategies, before significant resource allocation, when stakeholders seem overly optimistic, or when cost of failure would be high (reputation, budget, market position).
optimize-docs
by fimokleiCondense markdown documentation for token efficiency while preserving all semantic meaning. Use when rules, documentation, or config files need optimization. Target 25-40% reduction through systematic condensation patterns.
inversion-exercise
by fimokleiFlip core assumptions to reveal hidden constraints and alternative approaches - "what if the opposite were true?"
intent-explorer
by fimokleiUse when starting a new feature, product idea, or problem exploration and the real user need is unclear. Trigger on "intent", "explore intent", "intentspec", "what should we build", "what's the real problem", "explore this idea", "user research", "discovery", "requirements grounding", or before any specification work.
inversion-strategist
by fimokleiFlip problems upside down - instead of "how to succeed", ask "how to definitely fail" then avoid those paths. Use when user says "invert", "inversion", "flip it", "opposite approach", "how would this fail", "avoid failure", "what NOT to do", "Munger", "anti-goals", "guarantee failure".
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by fimokleiTurn any rough prompt, half-formed idea, or task description into a finished, ready-to-send prompt optimized for Opus 4.7 (with adaptive thinking) inside the chat app — claude.ai, the Mac app, the iOS app — NOT the API. Use this skill whenever the user wants to write, rewrite, optimize, improve, sharpen, or polish a prompt for the chat app. Trigger phrases include "rewrite this prompt", "make this a better prompt", "optimize this prompt", "turn this into a prompt", "help me prompt this", "draft a prompt that...", "I want to ask...", or whenever the user pastes a draft prompt and asks for improvements. Also trigger when the user describes a task they plan to send into the chat app and clearly wants a reusable, well-structured prompt rather than a direct answer. The output is always a single, copy-pasteable prompt in a code block that the user sends as-is — never a template with placeholders. Always ends with the exact line "Think before answering (maximum reasoning)".
session-summarizer
by fimokleiUse when user runs /summarize command to capture session knowledge
collision-zone-thinking
by fimokleiForce unrelated concepts together to discover emergent properties - "What if we treated X like Y?"
pre-mortem-analyst
by fimokleiImagine the project already failed, then work backward to find why. More powerful than risk assessment because it assumes failure is certain. Use when user says "pre-mortem", "premortem", "imagine this failed", "what could go wrong", "risk analysis", "before we launch", "stress test", "what would kill this", "project risks".
jtbd-analyzer
by fimokleiUncover the real "job" customers hire your product to do. Goes beyond features to understand functional, emotional, and social motivations. Use when user says "jobs to be done", "jtbd", "why do customers", "what job", "customer motivation", "what problem", "user needs", "why do people buy".
idea-challenger
by fimokleiPre-launch red team analysis that identifies failure modes and validates assumptions before resource commitment. Use when evaluating new products/features/strategies, before significant resource allocation, when stakeholders seem overly optimistic, or when cost of failure would be high (reputation, budget, market position).
first-principles-decomposer
by fimokleiBreak any problem down to fundamental truths, then rebuild solutions from atoms up. Use when user says "firstp", "first principles", "from scratch", "what are we assuming", "break this down", "atomic", "fundamental truth", "physics thinking", "Elon method", "bedrock", "ground up", "core problem", "strip away", or challenges assumptions about how things are done.
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.