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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agent-ready-cloudflare
by fabricioctellesAudit and improve website readiness for AI agents using the Cloudflare "Is It Agent Ready?" scanner (isitagentready.com). Covers scanning via API, interpreting results, generating implementation prompts, and fixing every check. Use when the user mentions "agent ready", "isitagentready", "AI agent scan", "agent readiness", "agent-ready score", "MCP server card", "agent skills index", "markdown for agents", "content signals", "web bot auth", "agent discovery", "RFC 9727", "RFC 8288", "RFC 9728", "SEP-1649", "WebMCP", "x402", "UCP", "ACP", or wants to make a website discoverable and usable by AI agents.
auth-md
by fabricioctellesGenerate, validate, and explain `auth.md` files — the open protocol that lets AI agents register for services on behalf of users. Use this skill whenever the user wants to make their app agent-ready by publishing an `auth.md`, generate Protected Resource Metadata (RFC 9728), validate an existing `auth.md` against the protocol specification, implement agent registration endpoints, understand how the auth.md protocol works, or configure authentication flows for agents. Trigger on mentions of "auth.md", "agent registration", "agent auth", "make my app agent-ready", "ID-JAG", "agent verified flow", "user claimed flow", "protected resource metadata", "OTP claim", "agentic registration", "CIMD", "Client ID Metadata Document", "oauth-id-jag", "logout token", "agent revocation", "agent credential", "agent discovery", "/.well-known/oauth-protected-resource", "/.well-known/oauth-authorization-server", "/agent/auth", or any variation of AI agent authentication/registration in APIs.
coolify-operator
by fabricioctellesOperador mestre do Coolify para plataforma self-hosted de deployment. Use quando o usuário mencionar 'coolify', 'deploy no coolify', 'listar/reiniciar/redeploy aplicações', 'ver logs coolify', 'API/CLI coolify', 'gerenciar servidores/databases/apps coolify', ou 'coolify context'. Automatiza deployments e gerenciamento via API REST ou CLI oficial.
front-end-checklist
by fabricioctellesThis skill should be used when a developer or team needs to review, validate, or audit front-end code before launching a website or HTML page to production. Triggers on requests such as "run the front-end checklist", "validate my front-end", "check my site before launch", or when the user asks for a structured review of HTML, CSS, JavaScript, accessibility, performance, security, or design quality.
geo-optimization
by fabricioctellesOptimize content for AI-generated responses and LLM citations (ChatGPT, Perplexity, Google AI Overview, Claude, Gemini). Use when the user mentions 'GEO', 'AEO', 'AI SEO', 'LLM optimization', 'citation rate', 'AI visibility', 'optimize for ChatGPT', 'roundup pages', or wants to audit pages for AI discoverability. Includes terminology alignment, FAQ schemas, and community signal strategies.
humanizar
by fabricioctellesReescreve texto em português brasileiro para soar humano, natural e indetectável por ferramentas de IA. Remove padrões de linguagem de máquina e AI slop, restaura entropia semântica, e injeta voz e personalidade. Use quando o texto em PT-BR parecer genérico, burocrático, ou gerado por IA — ou quando pedido para "humanizar", "dar vida", "tirar cara de IA", "remover AI slop", "reescrever com voz", ou "revisar tom".
pier-cloud
by fabricioctellesEste skill deve ser usado quando o usuário precisar consumir a API Pier Cloud (Lighthouse) para gerenciamento de custos em nuvem — incluindo autenticação JWT, listagem de contextos, workspaces e visualizações de dados FinOps. Acionar sempre que houver necessidade de integrar, automatizar ou depurar chamadas à plataforma Pier Cloud via Python, Node.js ou cURL.
premium-proposal-builder
by fabricioctellesCreates and structures premium proposals, slide decks, and scrollable sites optimized for purchase decisions. Generates effective prompts for Lovable, Gamma, Pitch, Relume, and similar tools. Helps choose the right format (website vs deck), structure high-impact sections, and generate clear, reader-focused content. Use when the user wants to create a business proposal, improve a pitch, generate prompts for design tools, or adapt structure for different industries (agencies, SaaS, enterprise).
ralph-loop-kiro-specs
by fabricioctellesAutomated iterative agent runner for spec-based development in Kiro. Wraps kiro-cli in a self-correcting bash loop that picks up tasks from a Kiro spec, implements them one at a time, verifies against exit criteria, and accumulates corrections and codebase patterns across iterations. Use this skill when the user mentions "ralph loop", "ralph", "spec loop", "iterative spec runner", "run my spec tasks automatically", "kiro spec automation", "self-correcting agent loop", "implement spec tasks in a loop", "run kiro-cli in a loop", "automated task implementation", or wants to drive a Kiro spec to completion through repeated agent iterations. Also use when the user wants to set up, configure, troubleshoot, or understand the Ralph Loop workflow — including progress tracking, corrections, codebase patterns, timing logs, and the summary dashboard.
resume-ats-beater
by fabricioctellesEste skill deve ser usado para reescrever currículos com foco em compatibilidade ATS e impacto para recrutadores. Acionar em pedidos de otimização de currículo, melhoria para ATS, reescrita profissional do CV, adaptação para vaga-alvo, auditoria de compatibilidade ATS ou aumento de taxa de entrevista.
startup-idea
by fabricioctellesAnalise startups de forma completa e compreensiva com mentalidade Paul Graham +
substack-expert
by fabricioctellesThis skill should be used when creating, formatting, or optimizing content for a Substack newsletter. Covers post structure, SEO metadata (titles, slugs, meta descriptions), native engagement features (Notes, Polls, Chat), monetization tactics, and free-to-paid conversion strategies.
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.