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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s4h-game-theory-auction
by human-avatarAnalyses bidding strategy and auction design — how much to bid, how to avoid the winner's curse, and how to design revenue-maximising or efficient auctions. Triggers: 'bidding strategy', 'auction analysis', 'how much should I bid', 'auction design', 'winner's curse', 'sealed bid', 'how do I avoid overbidding', 'procurement auction', 'design an auction', 'competitive offer'.
s4h-sensory-structured-observation
by human-avatarApplies disciplined observation to a situation — suspending interpretation to see what's actually there before deciding what it means. Triggers: 'observe this carefully', 'structured observation', 'what do you actually see', 'suspend interpretation', 'look more carefully'.
s4h-cognition-attention
by human-avatarMaps the attention economy of a mind or situation — what captures it, what depletes it, and how to protect it. Use when asked 'why can't I focus', 'attention keeps getting pulled away', 'how do I protect deep work', 'what's stealing my focus', 'I keep getting distracted', or when designing environments, workflows, or communications that need to respect cognitive bandwidth.
s4h-cognition-cognitive-load
by human-avatarManages the limits of working memory — chunking, offloading, and reducing unnecessary complexity to free capacity for what matters. Use when asked 'this is too complex to hold in my head', 'I keep losing track of where I am', 'how do I make this simpler to think about', 'the design is overwhelming', 'people aren't retaining this', or when information architecture, learning design, or communication complexity needs to be optimised for working memory limits.
s4h-cognition-mental-models
by human-avatarSurfaces and audits the internal representations that drive perception and decision-making. Use when asked 'what assumptions am I making', 'why do I keep seeing this the same way', 'what model is driving this decision', 'I think I'm missing something about how this works', 'what's my mental model here', or when a belief or decision pattern needs to be examined from the inside.
s4h-creativity-plus-minus-interesting
by human-avatarApply Edward de Bono's Plus/Minus/Interesting (PMI) tool for balanced evaluation of any idea, proposal, plan, or decision. Use when the user wants to evaluate something fairly, is tempted to immediately accept or reject an idea, needs to think through pros and cons more carefully, or wants to avoid snap judgments. Plus/Minus/Interesting is the antidote to confirmation bias in evaluation.
s4h-creativity-provocation
by human-avatarApply Edward de Bono's Provocation Operation (Po) to use deliberately absurd or impossible statements as springboards to new ideas. Use when the user wants to break out of conventional thinking, says 'let's try something radical', wants to use provocation as a creative tool, or is stuck and needs an unconventional jolt. Also trigger when the user uses the prefix 'Po:' before a statement.
s4h-creativity-random-entry
by human-avatarApply Edward de Bono's Random Entry technique — use an unrelated word, object, or image as a creative springboard to break out of cognitive ruts. Use when the user is stuck, wants unexpected inspiration, asks for a random creative prompt, wants to approach something from a completely fresh angle, or says they've exhausted their usual thinking. The randomness is the point — don't skip it.
s4h-creativity
by human-avatarEntry point for the creativity toolkit. Routes to the right creative thinking technique based on your situation. Use when you say 'creativity', 'think creatively', 'I need fresh ideas', 'help me think differently', 'I'm stuck', or want creative help without knowing which specific tool applies. For comprehensive multi-method sessions, this runs them in sequence.
s4h-creativity-water-logic
by human-avatarApply Edward de Bono's water logic for flow-based, non-judgmental exploration. Use when the user is in early-stage exploration and premature categorization is killing promising directions, wants to follow where ideas lead without forcing conclusions, is working on something open-ended where 'is this right?' is the wrong question, or needs to map possibilities before judging them. Water logic is the alternative to rock logic.
s4h-decision-option-mapping
by human-avatarEnsures all real options are visible before choosing — countering the false dichotomy that limits consideration to the first two options that came to mind. Triggers: 'what are all the options', 'false dichotomy check', 'expand the option set', 'what else could we do', 'options inventory'.
s4h-ecology-interdependence
by human-avatarMaps dependency webs and the cascading effects of removing or changing a node in the web. Use when asked 'who depends on whom', 'what cascades if we change X', 'downstream effects', 'what holds this together', 'ripple effects', or 'what breaks if we remove this'.
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.