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Found 102 Skills
Decision and migration guide for Prisma ORM MongoDB projects on v6, which have no upgrade path to v7. Use when a MongoDB project asks about upgrading Prisma, when "upgrade to prisma 7" comes up in a project with provider = "mongodb", or when evaluating a move to Prisma Next. Triggers on "upgrade prisma mongodb", "prisma 7 mongodb", "mongodb prisma migration", "prisma next mongodb".
Verify MongoDB Atlas setup and configuration for backend applications. Checks connection strings, environment variables, connection pooling, and ensures proper setup for Next.js and NestJS applications.
Alibaba Cloud MongoDB full lifecycle management: create/query/scale/delete standalone, replica set, sharded cluster instances. Covers node management, security (whitelist/security group), public & SRV address, password reset, renewal, billing conversion, cloud disk reconfiguration, maintenance window, backup, version upgrade, HA switchover, account & tag management. Triggers: "MongoDB", "create MongoDB", "dds instance", "list instances", "MongoDB scaling", "add Mongos/Shard node", "MongoDB whitelist", "reset password", "allocate public address", "SRV address", "MongoDB renewal", "billing type conversion", "cloud disk reconfiguration", "delete MongoDB instance", "maintenance window", "restart MongoDB", "MongoDB backup", "upgrade MongoDB version", "HA switchover", "MongoDB tags", "MongoDB account"
Scaffolds or references a production-ready Node.js REST API with Express 5, TypeScript, Mongoose (MongoDB), Redis, Sentry, JWT auth, bcrypt, rate limiting, and centralized error handling. Use when the user wants to start a new observable and resilient backend, needs a Node.js API boilerplate with security and monitoring, or asks to clone or adapt this template repository.
Database schema design, indexing, and migration guidance for MongoDB-based applications.
MongoDB document modeling, aggregation pipeline optimization, sharding strategies, replica set configuration, connection pool management, and indexing patterns. Use this skill for MongoDB-specific issues, NoSQL performance optimization, and schema design.
Manages MongoDB Atlas Stream Processing (ASP) workflows. Handles workspace provisioning, data source/sink connections, processor lifecycle operations, debugging diagnostics, and tier sizing. Supports Kafka, Atlas clusters, S3, HTTPS, and Lambda integrations for streaming data workloads and event processing. NOT for general MongoDB queries or Atlas cluster management. Requires MongoDB MCP Server with Atlas API credentials.
Use when writing ANY Mongoose query (.find, .findOne, .findById, .aggregate, .populate), adding database operations to services or controllers, wiring data between services, building endpoints that read or write to MongoDB, or reviewing code that chains service calls. TRIGGER especially when about to write a new findById or pass an ID where a document could be passed instead.
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.
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.
Work with MongoDB databases using best practices. Use when designing schemas, writing queries, building aggregation pipelines, or optimizing performance. Triggers on MongoDB, Mongoose, NoSQL, aggregation pipeline, document database, MongoDB Atlas.
MongoDB document database with aggregation pipeline and Atlas. Use for document storage.