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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scholar-practitioner
by Forexgod21Executes graduate-level academic writing, critique, and tutoring at scholar-practitioner standard. Activate when asked to write, draft, review, critique, or explain graduate-level academic content — including discussion posts, response posts, papers, literature reviews, research proposals, and argument critiques. Operates in two modes: Execute (submission-ready output) and Teach (concept breakdown without diluting standards). Applies the adversarial evaluator gate, theory-as- mechanism doctrine, and dual-mode architecture across all deliverables.
complete-design-strategy-blueprint
by Forexgod21Use this skill whenever the user needs a complete visual design strategy for a brand, topic, or project. Triggers when the user asks for a design strategy, visual direction, brand blueprint, or says things like "help me design my brand", "create a visual strategy for", "I need a design plan for", or "make my content stop looking like everyone else." Always activate this skill for any request involving intentional, structured visual brand planning.
design-simplification-impact-editor
by Forexgod21Use this skill whenever the user needs an existing design brief, visual concept, or creative direction ruthlessly edited for maximum visual impact. Triggers when the user asks to improve, optimize, or simplify a design brief, or says things like "review my design brief", "make this design more impactful", "cut the fat from my visual direction", "optimize this for maximum impact", "what's wrong with my design brief", or "paste my brief and improve it." Always activate this skill when the user provides existing design content that needs to be strengthened, simplified, and sharpened for visual effectiveness.
complete-design-system-brand-guidelines
by Forexgod21Use this skill whenever the user needs a complete, documented design system and brand guidelines document. Triggers when the user asks for brand guidelines, a design system, a brand bible, or says things like "create brand guidelines for", "build a complete design system for my brand", "I need a brand bible", "document my brand visuals", "create a style guide for", or "make every future design decision effortless." Always activate this skill for any request involving comprehensive brand documentation, design system creation, style guides, or building a visual reference library that ensures long-term brand consistency.
utility-drift-detector
by Forexgod21Use this skill whenever the user needs to detect whether an AI system's outputs suggest its values or optimization targets have shifted from what was intended or established at deployment. Triggers when the user asks about AI value drift, behavioral changes over time, or says things like "my AI is behaving differently than it used to", "something has shifted in how my AI responds", "I think my AI's priorities have changed", "detect value drift in my AI system", or "my AI outputs feel off in a way I can't pin down." Always activate this skill when the user needs a structured framework for identifying, measuring, and responding to post-deployment drift in AI utility functions — the gradual or sudden shift in what an AI system implicitly optimizes for over time.
utility-control-protocol
by Forexgod21Use this skill whenever the user needs to redirect an AI system's utility expressions — its active optimization behavior — toward sanctioned targets when divergence, drift, or misaligned exchange rates have been identified. Triggers when the user says "redirect my AI's optimization toward the right targets", "my AI is optimizing for the wrong thing — fix it", "implement a utility correction protocol", "my value audit found misalignment — now what", or "I need a structured intervention to bring my AI's behavior back in line with intended values." Always activate this skill when the user needs a concrete, structured intervention protocol to redirect AI utility expressions from emergent or drifted targets back toward the values and objectives that were actually authorized.
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.