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.
Querying local SQLite index...
career-transitions
by Zal4DWThis skill should be used when the user asks to "go fractional", "build a portfolio career", "become a fractional executive", "assess my AI readiness", "how do I show AI skills", "start my own business", "should I start a startup", "I want to be a founder", "thinking about entrepreneurship", "career change to public sector", "charity sector careers", "non-linear career", "I don't want to climb the ladder", "thinking about starting a company", "should I go into the public sector", "I want to do something different with my career", or "what are my options besides employment". Provides portfolio and fractional career support with regional tax and legal guidance, AI readiness assessment with upskilling roadmaps, and non-linear career exploration covering entrepreneurship, startup founding, public sector transitions, charity and non-profit careers, intrapreneurship, and multi-role skilling.
tim
by Zal4DWThis skill should be used when the user wants guided career coaching, doesn't know which skill to use, wants help navigating the plugin, says "help me with my career", "coach me", "guide me through this", "what should I do next", "I don't know where to start", or uses /career-helper:career-coach. Tim is a supportive career coach who understands your situation, runs the right skills in the right order, and pauses at structured checkpoints between each.
employer-footprint
by Zal4DWThis skill should be used when the user asks to "check my digital footprint", "what will employers see about me online", "audit my online presence", "what does my digital profile look like to a recruiter", "check my social media for red flags", or "employer impression report". Conducts a comprehensive digital footprint analysis through the lens of a potential employer, producing a credit-report style dashboard of positive and negative signals across social media channels, public content, and online presence.
application-optimiser
by Zal4DWThis skill should be used when the user asks to "optimise my CV", "fix my CV", "improve my CV", "tailor my CV for ATS", "research a company", "help me apply for a role", or "plan my application". Provides ATS-optimised CV rewriting, company and role research with parallel intelligence gathering, and application strategy planning.
career-navigator
by Zal4DWThis skill should be used when the user asks to "plan my job search", "build a networking strategy", "negotiate my salary", "evaluate a job offer", "compare offers", or "create a 3-month plan". Provides strategic networking intelligence, job search planning with wellbeing integration, salary negotiation coaching (UK/US/EU/APAC), and multi-offer evaluation frameworks.
getting-started
by Zal4DWThis skill should be used when the user asks "how do I get started", "how do I use career-helper", "how do I get the best results", "what should I prepare", "what order should I use the skills", "tips for using career-helper", "show me how this plugin works", "give me the guide", "getting the best guide", or "can I get a guide to share". Provides a comprehensive guide covering preparation checklists, recommended workflows, skill-by-skill tips, power-user strategies, and a downloadable getting the best guide for maximising career-helper output quality.
interview-master
by Zal4DWThis skill should be used when the user asks to "prepare for an interview", "do a mock interview", "what do interviewers look for", "I got rejected", "help me after an interview", "I think I was rejected because of my age", "ageism", "age discrimination", or "I'm being told I'm overqualified". Provides interview preparation with STAR frameworks, interviewer perspective reports, realistic mock interview simulation, post-interview coaching for rejection recovery, and comprehensive ageism support including UK law, practical strategies, and emotional resilience.
ned-ai-helper
by Zal4DWAI strategy guidance for Non-Executive Directors and Board Governors. Provides frameworks for AI governance oversight, strategic challenge questions, risk assessment matrices, and board-level AI literacy. Use when NEDs need to evaluate AI proposals, develop governance structures, challenge executive AI strategies, or understand AI risks and opportunities. Outputs board-ready materials in "Pragmatic Operator" tone.
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.