mongodb-development

name: mongodb-development description: MongoDB development workflow covering schema design, collections, indexes, aggregation pipelines, transactions, change streams, Atlas, security, backups, performance, and Node.js application integration. Use when building, reviewing, or debugging MongoDB-backed applications. source: HsinPu/Autoverse-Ai-Agent-Skills license: Apache-2.0

MongoDB Development

Use this skill when building, reviewing, tuning, or debugging applications backed by MongoDB or MongoDB Atlas.

Core Scope

• Document schema design, embedding vs referencing, collection boundaries, and data growth
• Indexes, query patterns, aggregation pipelines, Atlas Search, and performance diagnostics
• Transactions, change streams, retryable writes, and consistency tradeoffs
• Atlas configuration, backups, security, network access, credentials, and observability
• Node.js and TypeScript integration with official drivers or ODMs such as Mongoose

Workflow

1. Identify access patterns before modeling collections.
2. Decide embedding vs referencing based on read/write shape, document growth, and consistency needs.
3. Create indexes that support actual filters, sorts, and joins-like lookups.
4. Use aggregation pipelines for server-side transformations and reporting.
5. Use transactions only when schema design cannot keep related updates in one document boundary.
6. Review Atlas/network/IAM settings before production access.
7. Monitor slow queries, index usage, connection pools, document size, and storage growth.

Schema Design

• Embed data that is read and written together and stays bounded.
• Reference data when arrays can grow without bound or entities have independent lifecycle.
• Avoid unbounded arrays inside hot documents.
• Store denormalized fields intentionally and define update strategy.
• Keep document validation and application validation aligned.

Index And Query Checks

• Create compound indexes that match query predicates and sort order.
• Watch for collection scans in explain plans.
• Avoid indexes that add write overhead without serving real queries.
• Use projection to avoid transferring large documents unnecessarily.
• Review aggregation memory and $lookup costs on large collections.

Operational Checks

• Use least-privilege database users.
• Restrict Atlas network access and rotate credentials when exposed.
• Verify backups and point-in-time restore where supported.
• Use change streams for event-driven reactions, not as a substitute for durable business transactions.
• Track retry behavior and duplicate handling in consumers.

Handoff

• Use database-design for broader data modeling decisions.
• Use javascript-development or typescript-development for app integration.
• Use nodejs-adjacent local project patterns when present; do not force an ODM if the repo uses the official driver.
• Use security-code-review for access control and secret exposure review.

References

• MongoDB Schema Design: https://www.mongodb.com/docs/manual/data-modeling/schema-design-process/
• MongoDB Indexes: https://www.mongodb.com/docs/manual/indexes/
• MongoDB Aggregation Pipeline: https://www.mongodb.com/docs/manual/core/aggregation-pipeline/
• MongoDB Change Streams: https://www.mongodb.com/docs/manual/changestreams/