Loading...
Loading...
Found 90 Skills
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.
This skill should be used when user asks to "query MongoDB", "show database collections", "get collection schema", "list MongoDB databases", "search records in MongoDB", or "check database indexes".
MongoDB schema design patterns and anti-patterns. Use when designing data models, reviewing schemas, migrating from SQL, or troubleshooting performance issues caused by schema problems. Triggers on "design schema", "embed vs reference", "MongoDB data model", "schema review", "unbounded arrays", "one-to-many", "tree structure", "16MB limit", "schema validation", "JSON Schema", "time series", "schema migration", "polymorphic", "TTL", "data lifecycle", "archive", "index explosion", "unnecessary indexes", "approximation pattern", "document versioning".
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.
MongoDB development guidelines with Payload CMS, Mongoose, aggregation pipelines, and TypeScript best practices.
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.
MongoDB document database with aggregation pipeline and Atlas. Use for document storage.
MongoDB Atlas cloud database management including clusters, schemas, aggregation pipelines, and Prisma ORM integration. Activate for MongoDB queries, schema design, indexing, and Atlas administration.
MongoDB transaction correctness, consistency, and retry safety. Use when implementing multi-document writes, debugging transaction failures, choosing readConcern/writeConcern, handling TransientTransactionError or UnknownTransactionCommitResult, or deciding when transactions are required. Triggers on "transaction", "withTransaction", "session", "read concern", "write concern", "causal consistency", "snapshot", "retry commit", "ACID", "TransientTransactionError", and "UnknownTransactionCommitResult".
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.
Guide for implementing MongoDB - a document database platform with CRUD operations, aggregation pipelines, indexing, replication, sharding, search capabilities, and comprehensive security. Use when working with MongoDB databases, designing schemas, writing queries, optimizing performance, configuring deployments (Atlas/self-managed/Kubernetes), implementing security, or integrating with applications through 15+ official drivers. (project)
Comprehensive guide for database management patterns covering PostgreSQL and MongoDB including schema design, indexing, transactions, replication, and performance tuning