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...
social-youtube-report
by evolution-foundationYouTube analytics report — queries channel stats, recent videos, engagement rates, top content. Generates HTML report. Use when user says 'youtube report', 'youtube metrics', 'youtube analytics', or any reference to YouTube performance analysis. Supports daily, weekly, and monthly periods.
ops-vendor-review
by evolution-foundationAvaliar um fornecedor — análise de custo, avaliação de risco e recomendação. Use quando revisar proposta de novo vendor, decidindo renovar ou substituir contrato, comparando dois vendors lado a lado, ou construindo breakdown de TCO e pontos de negociação antes da aprovação. Agente Nex.
gog-email-triage
by evolution-foundationTriage and prioritize inbox emails. Summarize unread messages, classify by urgency and category, propose actions (reply, archive, schedule, create task). Use when user wants to review inbox, process unread emails, or needs help prioritizing messages. Outputs structured summary with top priorities and suggested next actions.
create-command
by evolution-foundationCreate a new slash command for Claude Code. Guides the user through defining the command name, what it does, and generates the markdown file in .claude/commands/. Use when the user says 'create a command', 'new command', 'add a slash command', 'I want a shortcut for', or wants to create a reusable slash command.
data-validate
by evolution-foundationValida uma análise antes de compartilhar — metodologia, precisão e verificações de viés. Use quando revisar uma análise antes de uma apresentação para stakeholders, verificar cálculos e lógica de agregação, conferir se os resultados de uma query SQL parecem corretos, ou avaliar se as conclusões são de fato suportadas pelos dados. Sempre rodar esta skill antes de compartilhar análises baseadas em Stripe, Omie, Licensing ou Evo CRM.
data-write-query
by evolution-foundationEscreve SQL otimizado para o stack Evolution (PostgreSQL primário) com boas práticas. Use quando precisar traduzir uma necessidade de dados em SQL, construir uma query com múltiplas CTEs, joins e agregações, otimizar uma query contra tabelas grandes, ou obter sintaxe específica para consultas no banco do Evo CRM, Evo AI, ou qualquer serviço do stack Evolution. Dialetos secundários disponíveis: Snowflake, BigQuery, MySQL, DuckDB.
db-mongo
by evolution-foundationQuery MongoDB databases configured in .env (DB_MONGO_N_*). Use when the user asks to query, explore, or audit data in a MongoDB database. Picks connection by label (e.g. 'orders-dev', 'analytics-prod') or numeric index. Read-only by default — writes refused unless DB_MONGO_N_ALLOW_WRITE=true on that block.
db-postgres
by evolution-foundationQuery PostgreSQL databases configured in .env (DB_POSTGRES_N_*). Use when the user asks to query, explore, or audit data in a Postgres database. Picks connection by label (e.g. 'msgops-dev', 'bms-prod') or numeric index. Read-only by default — writes refused unless DB_POSTGRES_N_ALLOW_WRITE=true on that block.
dev-ccg
by evolution-foundationTri-model orchestration — run the same task through Claude + Codex + Gemini in parallel and synthesize the best answer. Use for high-stakes decisions where multi-model consensus reduces single-model bias.
dev-mcp-setup
by evolution-foundationConfigure MCP servers for the workspace — web search, filesystem, GitHub, Stripe, etc. Use when adding a new integration that needs MCP-level access.
fin-monthly-close-kickoff
by evolution-foundationMonthly close kickoff — initiates the month-end closing process with a checklist, simplified P&L (Stripe + Omie + Evo Academy), pending reconciliations, receivables, payables, and action items for the finance team. Trigger when user says 'monthly close', 'start closing', 'closing kickoff', or on the 1st of each month.
hr-performance-review
by evolution-foundationEstrutura uma avaliação de desempenho com auto-avaliação, template de gestor e prep para calibração. Use quando a temporada de reviews começa, ao escrever a avaliação de um liderado, ao preparar distribuição de ratings e casos de promoção, ou ao transformar feedback vago em exemplos comportamentais específicos.
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.