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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polymarket-monitor
by mjunaidcaUse this skill whenever the user wants to monitor, watch, or track Polymarket prediction market prices over time. This includes setting up price alerts, watching for significant price movements, tracking spread changes, monitoring volume spikes, or getting notified about market activity. Trigger on: monitor prices, price alert, watch market, track prices, notify me, price change, polymarket alerts, market watch, price movement, volume spike, spread monitoring, track odds, prediction market alerts, continuous monitoring, price tracker, market surveillance.
shadcn-ui
by mjunaidcaBuild beautiful, accessible UIs with shadcn/ui components. Use this skill when creating forms, dialogs, tables, sidebars, or any UI components in Next.js. Covers installation, component patterns, react-hook-form integration with Zod validation, and dark mode setup.
kagent
by mjunaidcaKubernetes-native AI agent framework for building, deploying, and managing AI agents on Kubernetes. This skill should be used when deploying AI agents as Kubernetes resources, analyzing cluster health with AI, and automating complex K8s operations. Use this skill for Phase IV advanced AIOps and agent-based cluster management.
fetching-library-docs
by mjunaidcaToken-efficient library API documentation fetcher using Context7 MCP with 77% token savings. Fetches code examples, API references, and usage patterns for published libraries (React, Next.js, Prisma, etc). Use when users ask "how do I use X library", need code examples, want API syntax, or are learning a framework's official API. Triggers: "Show me React hooks", "Prisma query syntax", "Next.js routing API". NOT for exploring repo internals/source code (use researching-with-deepwiki) or local files.
better-auth-setup
by mjunaidcaGuide implementation of OAuth 2.1 / OIDC authentication using Better Auth with the OIDC Provider plugin. Use this skill when setting up centralized authentication for multiple apps, implementing SSO across a platform, creating an OAuth authorization server, or integrating Better Auth as an identity provider. Covers PKCE for public clients, JWKS configuration, token management, email verification, and common pitfalls like preserving PKCE parameters during sign-in redirects.
better-auth-sso
by mjunaidcaIntegrate with Better Auth SSO for OAuth2/OIDC authentication. Use this skill when implementing SSO login flows, PKCE authentication, token management, JWKS verification, or global logout in Next.js applications connecting to a Better Auth server.
working-with-spreadsheets
by mjunaidcaCreates and edits Excel spreadsheets with formulas, formatting, and financial modeling standards. Use when working with .xlsx files, financial models, data analysis, or formula-heavy spreadsheets. Covers formula recalculation, color coding standards, and common pitfalls.
nx-monorepo
by mjunaidcaNx monorepo management skill for AI-native development. This skill should be used when working with Nx workspaces, project graphs, affected detection, code generation, and caching. Use when: analyzing dependencies, running affected commands, generating code, configuring Nx Cloud, or optimizing build performance. Invoke nx-mcp tools for documentation queries.
blueprint-skill-creator
by mjunaidcaCreates blueprint-driven skills for infrastructure and deployment tasks. This skill should be used when creating new skills that require templates, patterns, or reference configurations (e.g., Dockerfiles, Helm charts, Kubernetes manifests, CI/CD pipelines). It enforces impact analysis before containerization, identifies environment requirements, network topology changes, and auth/CORS implications. Use this skill when building deployment-related skills or when containerizing applications.
kubectl-ai
by mjunaidcaAI-powered Kubernetes operations using kubectl-ai from Google Cloud Platform. This skill should be used when managing Kubernetes clusters with natural language commands, generating manifests, troubleshooting issues, and performing AI-assisted DevOps. Use this skill for Phase IV AIOps integration with Minikube and cloud clusters.
nextjs-16
by mjunaidcaBuild Next.js 16 applications with the correct patterns. Use this skill when creating pages, layouts, middleware (now proxy.ts), dynamic routes, or upgrading from Next.js 15. Covers breaking changes like async params/searchParams, Turbopack defaults, proxy.ts (replacing middleware.ts), and cacheComponents.
urdu-translator
by mjunaidcaTranslate educational content to Urdu while preserving technical accuracy. Use for multilingual content delivery.
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.