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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hcq-ciq-module
by drogafarto-webPlaybook do hc quality para construir ou estender módulos de CIQ laboratorial (hematologia, coagulação, uroanálise, imunologia, insumos, novos). Use sempre que adicionar um módulo, integrar rastreabilidade de insumos em forms, construir export de formulário FR-*, ou modificar audit trail. Define convenções de Firestore, tipos, rules, hooks, Cloud Functions, assinatura/chain hash e gate pré-merge. Referência canônica — se conflitar com implementação atual, o código em produção venceu e a skill deve ser atualizada.
gsd-graphify
by drogafarto-webBuild, query, and inspect the project knowledge graph in .planning/graphs/
gsd-inbox
by drogafarto-webTriage and review open GitHub issues and PRs against project templates and contribution guidelines.
hcq-pdf-export-scaffold
by drogafarto-webGera scaffold de export PDF de compliance (FR-10, FR-50, relatório CIQ, backup diário) para hc quality — layout tokens compartilhados, componente React com react-to-print, QR de validação, endpoint público validateFR, golden test com snapshot, smoke render script. Replica layout físico Labclin pixel-a-pixel. Discrimina A4 vs. tabloide, dual-row vs. single, cursor-based layout com safeBottomY. Codifica padrão extraído dos 6 sprints de refactor do PDF backup diário.
hc-quality-smoke
by drogafarto-webTeste de fumaça end-to-end do HC Quality (sistema de CIQ laboratorial em produção). Navega todos os módulos (Hematologia, CIQ-Imuno, Coagulação, Uroanálise, Insumos, Equipamentos, BulaParser, Reports, Admin), executa fluxos críticos com imagens reais de corridas + mocks, e entrega relatório por critério de aceite com evidência em screenshot. Requer Playwright.
hc-quality-academia-espaco-viva
by drogafarto-webUse when managing, configuring, or troubleshooting the Actuar software and hardware integration for the Academia Espaço Viva project
hc-quality-coagulation-sgq
by drogafarto-webDedicated skill to handle HC Quality's Coagulation Clotimer Duo run screens, SMTP/Resend notification systems, and SGQ document management workflows under ANVISA RDC 978 and LGPD compliance.
hcq-ciq-audit-trail
by drogafarto-webGera e valida audit trail tamper-evident para módulos CIQ do hc quality — logicalSignature client-side (SHA-256 canonical), event doc imutável em subcoleção, Cloud Function trigger que calcula chainHash idempotente, rules Firestore que bloqueiam mutação, verificador CLI. Use sempre que adicionar um ponto de gravação de estado (criar/abrir/fechar/descartar/anular/aprovar) em módulo CIQ ou rastreabilidade. Referência canônica da seção 8 do playbook hcq-ciq-module, expandida com scaffolds executáveis.
hcq-deploy-gates
by drogafarto-webExecuta o gate pré-merge e pré-deploy do hc quality — typecheck, lint com baseline de 88 warnings pré-existentes, 274 testes unit baseline, build app + functions, verificadores de chain hash, scan de secrets no diff, emulator rules test. Bloqueia regressão. Use antes de abrir PR, antes de mergear, e antes de cada etapa de deploy (rules → functions → hosting). Relatório em formato checklist pronto pra colar na PR.
hcq-firestore-rules-generator
by drogafarto-webGera bloco de rules Firestore para um módulo CIQ do hc quality — match por labId, RBAC via member doc (isActiveMemberOfLab + isAdminOrOwner), events subcoleção imutável, config doc com flag enabled, audit subcoleção append-only, bloqueio de chainHash client-side, validação de payload por isValidRun, collectionGroup rule para events. Use ao criar módulo novo, ao ampliar um existente com subcoleção nova, ou ao auditar rules pré-deploy. Complementa hcq-ciq-audit-trail (rules do events) e hcq-module-generator (bloco gerado no scaffold).
hcq-insumo-picker-integrator
by drogafarto-webIntegra o InsumoPicker em um form de módulo CIQ existente no hc quality — adiciona campo nullable no schema Zod, componente UI no form, onSelect handler que pré-preenche campos legados sem substituir, gate CQ-pendente (bloqueia uso de controle com CIQ não aprovado), validação de validade/reagente ativo. Use ao extender módulos existentes (coagulacao, uroanalise, ciq-imuno) com rastreabilidade, ou quando um módulo novo gerado pelo hcq-module-generator precisa do Picker plugado.
hcq-module-generator
by drogafarto-webGera scaffold completo de um novo módulo CIQ no hc quality (ex: bioquímica, parasitologia, microbiologia) — pasta feature, service client-direct, hooks de subscription e save, schema Zod, form com InsumoPicker, rules Firestore por módulo, Cloud Function trigger de chainHash, constantes, testes skeleton, feature flag. Use quando for criar um módulo CIQ do zero. Aplica o playbook hcq-ciq-module de forma executável, sem divergir das invariantes. Discrimina CIQ quantitativo vs. categórico (R/NR).
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.