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mongodb/mongodb-schema-design

Padrões e anti-padrões de design de esquema do MongoDB. Use ao projetar modelos de dados, revisar esquemas, migrar do SQL ou solucionar problemas de desempenho causados por problemas de esquema.

O que é mongodb-schema-design?

Esta skill fornece orientação abrangente sobre design de esquema do MongoDB, cobrindo padrões comprovados e anti-padrões comuns. Ela é ativada por palavras-chave como 'design schema', 'embed vs reference', 'revisão de esquema', 'arrays ilimitados', 'one-to-many', 'estrutura de árvore', 'limite de 16MB', 'validação de esquema', 'JSON Schema', 'séries temporais', 'migração de esquema', 'polimórfico', 'TTL', 'ciclo de vida de dados', 'explosão de índices' e 'versionamento de documentos'. Útil para desenvolvedores que projetam modelos de dados, revisam esquemas, migram de bancos SQL relacionais ou enfrentam problemas de desempenho relacionados ao esquema. A skill explica quando usar documentos embutidos versus referências, como modelar relacionamentos um-para-muitos e muitos-para-muitos, como evitar armadilhas como arrays que crescem sem limites e documentos que excedem 16 MB, e como aplicar padrões como aproximação, versionamento de documentos e gerenciamento de ciclo de vida de dados com índices TTL. Também aborda validação de esquema com JSON Schema e otimização de índices para evitar explosão de índices.

Funciona com~Claude Code~Codex CLI~Cursor
Part ofDesign & UI
npx skills add https://github.com/mongodb/agent-skills/tree/main/skills/mongodb-schema-design
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Documentação

O que mongodb-schema-design faz?

Padrões e anti-padrões de design de esquema do MongoDB. Use ao projetar modelos de dados, revisar esquemas, migrar do SQL ou solucionar problemas de desempenho causados por problemas de esquema. Ativado por "design schema", "embed vs reference", "modelo de dados MongoDB", "revisão de esquema", "arrays ilimitados", "one-to-many", "estrutura de árvore", "limite de 16MB", "validação de esquema", "JSON Schema", "séries temporais", "migração de esquema", "polimórfico", "TTL", "ciclo de vida de dados", "arquivo morto", "explosão de índices", "índices desnecessários", "padrão de aproximação", "versionamento de documentos".

Individual skills in this repo

This repo contains 5 individual skills — each has its own dedicated page.

mongodb/mongodb-connection

Optimize MongoDB client connection configuration (pools, timeouts, patterns) for any supported driver language. Use this skill when working/updating/reviewing on functions that instantiate or configure a MongoDB client (eg, when calling `connect()`), configuring connection pools, troubleshooting connection errors (ECONNREFUSED, timeouts, pool exhaustion), optimizing performance issues related to connections. This includes scenarios like building serverless functions with MongoDB, creating API endpoints that use MongoDB, optimizing high-traffic MongoDB applications, creating long-running tasks and concurrency, or debugging connection-related failures.

mongodb/mongodb-mcp-setup

Guide users through configuring key MongoDB MCP server options. Use this skill when a user has the MongoDB MCP server installed but hasn't configured the required environment variables, or when they ask about connecting to MongoDB/Atlas and don't have the credentials set up.

mongodb/mongodb-natural-language-querying

Generate read-only MongoDB queries (find) or aggregation pipelines using natural language, with collection schema context and sample documents. Use this skill whenever the user asks to write, create, or generate MongoDB queries, wants to filter/query/aggregate data in MongoDB, asks "how do I query...", needs help with query syntax, or discusses finding/filtering/grouping MongoDB documents. Also use for translating SQL-like requests to MongoDB syntax. Does NOT handle Atlas Search ($search operator), vector/semantic search ($vectorSearch operator), fuzzy matching, autocomplete indexes, or relevance scoring - use search-and-ai for those. Does NOT analyze or optimize existing queries - use mongodb-query-optimizer for that. Does NOT handle aggregation pipelines that involve write operations. Requires MongoDB MCP server.

mongodb/mongodb-query-optimizer

Help with MongoDB query optimization and indexing. Use only when the user asks for optimization or performance: "How do I optimize this query?", "How do I index this?", "Why is this query slow?", "Can you fix my slow queries?", "What are the slow queries on my cluster?", etc. Do not invoke for general MongoDB query writing unless user asks for performance or index help. Prefer indexing as optimization strategy. Use MongoDB MCP when available.

mongodb/mongodb-search-and-ai

Guides MongoDB users through implementing and optimizing Atlas Search (full-text), Vector Search (semantic), and Hybrid Search solutions. Use this skill when users need to build search functionality for text-based queries (autocomplete, fuzzy matching, faceted search), semantic similarity (embeddings, RAG applications), or combined approaches. Also use when users need text containment, substring matching ('contains', 'includes', 'appears in'), case-insensitive or multi-field text search, or filtering across many fields with variable combinations. Provides workflows for selecting the right search type, creating indexes, constructing queries, and optimizing performance using the MongoDB MCP server.

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