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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job-search-strategist
by proyecto26Comprehensive job search strategy skill for analyzing job postings, discovering non-obvious insights, conducting conversational skills-matching interviews, identifying skill development needs and creating creative, personalized application strategies. This skill should be used when users want help with job applications, career transitions, analyzing job opportunities or developing targeted job search approaches that help them stand out from other candidates.
resume-builder
by proyecto26Comprehensive resume creation, review and optimization with support for multiple formats, ATS optimization, industry-specific guidance and career stage customization. Use this skill when users request help writing, creating, reviewing, improving or tailoring resumes for job applications.
tailored-resume-generator
by proyecto26Analyzes job descriptions and generates tailored resumes that highlight relevant experience, skills and achievements to maximize interview chances
prisma
by proyecto26Prisma ORM and PostgreSQL database operations. Use when working with database schema, migrations, queries, or the @projectx/db package.
temporal
by proyecto26This skill should be used when the user asks to "create a Temporal workflow", "write a Temporal activity", "debug stuck workflow", "fix non-determinism error", "Temporal TypeScript", "workflow replay", "activity timeout", "signal workflow", "query workflow", "worker not starting", "activity keeps retrying", "Temporal heartbeat", "continue-as-new", "child workflow", "saga pattern", "workflow versioning", "durable execution", "reliable distributed systems", mentions Temporal SDK development or implementing Temporal stuff (workflows, workers, activities), managing queries, updates and signals for existing workflows or updating the configuration for the Temporal worker and clients from our package packages/workflows such as WorkflowsModule, WorkerService, ClientService, or Workflow utils.
temporal-playground
by proyecto26Interactive visual playground for designing, editing, and generating Temporal workflows. Use when the user wants to visually build workflows, load existing project workflows onto a canvas, or generate workflow code from a visual spec. Includes its own MCP server (temporal-playground) for chat and connects to temporal-docs MCP for documentation.
react-router-v7
by proyecto26React Router v7 full-stack development with SSR. Use when working with routes, loaders, actions, SSR, Form components, fetchers, navigation guards, protected routes, URL search params, or the web app in apps/web.
nestjs
by proyecto26NestJS microservices development. Use when creating controllers, services, modules, guards, interceptors, or working with NestJS patterns in auth, order, or product services.
notebooklm
by proyecto26Interact with Google NotebookLM notebooks — chat with the AI, generate artifacts (slides, audio, video, mind maps, quizzes, flashcards, infographics, reports, data tables), manage sources (add URLs, YouTube, files, text), run research (fast/deep web research), and manage notes. Use when the user wants to query, create content from, or manage their NotebookLM notebooks and sources.
paper-comic
by proyecto26Generate educational comics from academic papers, using visual storytelling to explain core ideas and innovations. Supports 4 art styles: classic (clean lines), tech (futuristic), warm (friendly), chalk (blackboard). Uses genimg-gemini-web to generate images.
visual-architect
by proyecto26Transform research papers into professional visual schemas. Analyzes paper logic, selects optimal layout patterns, and generates detailed prompts for AI image generation.
deep-research
by proyecto26Generate format-controlled research reports with evidence tracking, citations, and iterative review. This skill should be used when users request a research report, literature review, market or industry analysis, competitive landscape, policy or technical brief, or require a strict report template and section formatting that a single deepresearch pass cannot reliably enforce.
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.