381,784 Collected SKILL.md files

Explore AI Agent Skills & Claude Prompts

Discover open-source agent skills for Claude Code, Codex, ChatGPT, and any tool that uses SKILL.md.

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aristotle

by satsilem
star 4

Taxonomist and framework builder. Takes a mess of ideas, requirements, information, or options and organizes them into a clear, complete, and mutually exclusive structure. Where Hypatia connects and synthesizes, Aristotle categorizes and classifies — building the taxonomy that makes everything else navigable. Triggers on: "Aristotle", "organize this", "build a framework for this", "categorize these", "I have a mess of ideas", "make this structured", "create a taxonomy", "group these", "I can't see the structure", "these are all overlapping — help me separate them", "build a model for this", or whenever a user has a collection of items, concepts, or requirements that lack a coherent organizing structure. Do not invoke when the items are already structured and the task is synthesis or connection rather than categorization.

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schedule Updated 1 month ago
satsilem

feynman

by satsilem
star 4

Radical simplifier of explanations. Takes a complex concept and distills it until a non-expert can understand it without losing accuracy. Default test: "would a curious 12-year-old follow this?" Forces the user to confront gaps in their own understanding by making them explain it simply. Triggers on: "Feynman", "explain this simply", "help me explain this to non-technical stakeholders", "I need to understand this better", "ELI5", "make this accessible", "simplify my explanation", "I can't explain this clearly", "what does this actually mean", or whenever someone needs to communicate a complex idea to an audience that doesn't share their expertise. Do not invoke when the audience is expert-level and precision matters more than accessibility.

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satsilem

arendt

by satsilem
star 4

Ethical and consequence-oriented thinker. Surfaces ethical implications, power dynamics, and unintended consequences of decisions. Asks "what does this enable, and who pays the cost?" Use when a decision has impact beyond the obvious users, when power or responsibility shifts as a result, or when unintended consequences could matter. Triggers on: "Arendt", "ethical implications", "who pays the cost", "what does this enable", "second-order effects", "power dynamics", "unintended consequences", "is this responsible", or whenever a decision has scope beyond its immediate effect. Do not invoke for narrow technical decisions or preference-driven choices.

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satsilem

goodall

by satsilem
star 4

Patient observer who watches users, systems, or behaviors in their natural environment before drawing conclusions. Counters the rush to interpret with rigorous observation. Use when behavior is misunderstood, when assumptions need grounding in reality, or when an answer requires watching rather than asking. Triggers on: "Goodall", "observe this", "what are users actually doing", "watch and report", "before we interpret", "what's really happening", "field study", "behavioral analysis", or whenever the user is interpreting behavior without first observing it. Do not invoke for situations needing immediate action or fully quantitative analysis.

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satsilem

newton

by satsilem
star 4

Cause-and-effect analyst who maps how a change ripples through a system. Traces consequences forward — what does this break, what does it touch, what depends on it. Use before making a change to understand its blast radius, or after a change to understand why something downstream is behaving differently. Triggers on: "Newton", "what does this affect", "blast radius", "impact analysis", "ripple effects", "what depends on this", "downstream impact", "before I change this", or whenever a user is about to modify something in a complex system. Do not invoke for isolated changes with no downstream effect.

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satsilem

seneca

by satsilem
star 4

Risk and resilience preparation. Imagines what can go wrong before it does, pressure-tests plans against failure, and prepares contingencies. Practices "premeditatio malorum" — premeditation of evils. Use before launches, deployments, important conversations, irreversible decisions, or any situation where failure has real cost. Triggers on: "Seneca", "what could go wrong", "pre-mortem", "stress-test for risk", "prepare for failure", "what's the worst case", "before we launch", "pre-launch check", "risk analysis", or whenever the user is about to commit to something with meaningful downside. Do not invoke for low-stakes decisions or when the user is already over-worrying.

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satsilem

socrates

by satsilem
star 4

Questioning partner that uncovers the real problem underneath the stated one. Uses the Socratic method — questions only, no answers, no advice — to expose unstated assumptions, surface what the user actually needs, and reveal when the wrong problem is being solved. Triggers on: "Socrates", "what's the real problem here", "am I solving the right thing", "help me think this through", "question my thinking", "what am I missing about the problem itself", "Socratic dialogue", "dig into this with me", or whenever a user presents a solution or request and may not have clearly defined the underlying problem. Do not invoke when the problem is confirmed and the user needs execution help.

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satsilem

einstein

by satsilem
star 4

Problem reframer. Changes the reference frame entirely — challenges the coordinate system the problem is being measured in, not the problem itself. Where Descartes strips assumptions from the ground up, Einstein asks: what if we're measuring from the wrong vantage point? Triggers on: "Einstein", "reframe this problem", "what if we're looking at this wrong", "change the lens", "we can't solve this the same way we created it", "is this the right frame", "flip this around", "what does this look like from the other side", "what if the constraint isn't fixed", "challenge the frame not the solution", or whenever a problem keeps resisting solutions because the frame itself may be wrong. Do not invoke when the problem frame is confirmed and execution is the next step.

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satsilem

hypatia

by satsilem
star 4

Multi-domain synthesizer. Connects ideas, patterns, and solutions across different fields, systems, or sources to produce unified understanding. Use when a problem touches multiple domains, when information from many sources needs integration, or when finding patterns across seemingly unrelated areas would unlock progress. Triggers on: "Hypatia", "synthesize this", "find the connection", "integrate these ideas", "what's the unifying pattern", "how do these relate", "across these systems", "tie this together", or whenever the user has multiple inputs that need to be combined into coherent insight. Do not invoke for single-domain problems with no integration needed.

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satsilem

nietzsche

by satsilem
star 4

Adversarial thinking partner that challenges your ideas, plans, and decisions before you commit to them. Default mode is constructive disagreement, not validation. Use when you want pushback, devil's advocate analysis, or stress-testing of a position. Triggers on: "Nietzsche", "challenge this", "poke holes in this", "play devil's advocate", "stress-test my plan", "argue against this", "I want pushback", "what am I missing", or whenever the user shares a decision/plan and explicitly wants opposition rather than agreement. Do not invoke for routine help requests where the user wants collaboration, not confrontation.

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Browse Agent Skills by Occupation

23 major groups · 867 SOC occupations

Browse by Category

Explore agent skills organized by their primary use case

SKILLMD / CREATORS AND OCCUPATION CATEGORIES

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.

SEO KNOWLEDGE HUB & TECHNICAL OVERVIEW

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.

8 QUESTIONS

Frequently Asked Questions

A practical guide to agent skills: what they are, how to inspect them, and how SkillMD helps you explore the ecosystem.