mongodb_skill

Overview

This skill provides practical, hands-on guidance for working with MongoDB, covering document operations, queries, aggregation pipelines, index design, and schema modeling. It helps developers write efficient queries, design collections, and apply best practices for performance and scalability. Use it when you need actionable examples, troubleshooting tips, or recommendations for production-ready MongoDB usage.

How this skill works

The skill inspects the user's intent and returns concrete MongoDB examples, shell/driver commands, and design advice tailored to their problem. It can generate CRUD operations in the Mongo shell and common drivers (Python/PyMongo, Node.js), craft aggregation pipelines, suggest index strategies, and recommend schema patterns. For performance issues it analyzes query shape and suggests indexes or pipeline rewrites.

When to use it

• Writing or optimizing queries and aggregation pipelines
• Designing document schemas and collection relationships
• Choosing and creating appropriate indexes for performance
• Migrating data or modeling many-to-many/one-to-many relationships
• Troubleshooting slow queries, replication, or sharding issues

Best practices

• Model data based on query patterns: embed for locality, reference for large or shared data
• Create indexes that match query filters and sort patterns; use compound indexes thoughtfully
• Limit projection to needed fields to reduce network and memory overhead
• Use aggregation pipeline stages in the order of selective filters first
• Monitor usage with explain(), serverStatus, and MMS/Atlas monitoring for hotspots

Example use cases

• Show a PyMongo example to insert, update, and query documents with pagination
• Build an aggregation pipeline to group, filter, and compute metrics over time-series data
• Recommend an index strategy for a query with multiple equality and sort conditions
• Design a schema for a blog platform supporting comments, tags, and user profiles
• Provide migration steps to convert embedded arrays into referenced collections for scale