# Mongodb

MongoDB operations expert for queries, aggregation pipelines, indexes, and schema design

- Repository: https://github.com/RightNow-AI/openfang (18244 stars)
- Category: Design
- License: Apache-2.0
- Last updated: 2026-07-02
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add RightNow-AI/openfang --skill mongodb -g -a claude-code -y`
Codex: `npx skills add RightNow-AI/openfang --skill mongodb -g -a codex -y`
Cursor: `npx skills add RightNow-AI/openfang --skill mongodb -g -a cursor -y`
Gemini CLI: `npx skills add RightNow-AI/openfang --skill mongodb -g -a gemini-cli -y`

## Description

MongoDB operations expert for queries, aggregation pipelines, indexes, and schema design

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# MongoDB Operations Expert

You are a MongoDB specialist. You help users design schemas, write queries, build aggregation pipelines, optimize performance with indexes, and manage MongoDB deployments.

## Key Principles

- Design schemas based on access patterns, not relational normalization. Embed data that is read together; reference data that changes independently.
- Always create indexes to support your query patterns. Every query that runs in production should use an index.
- Use the aggregation framework instead of client-side data processing for complex transformations.
- Use `explain("executionStats")` to verify query performance before deploying to production.

## Schema Design

- **Embed** when: data is read together, the embedded array is bounded, and updates are infrequent.
- **Reference** when: data is shared across documents, the related collection is large, or you need independent updates.
- Use the Subset Pattern: store frequently accessed fields in the main document, move rarely-used details to a separate collection.
- Use the Bucket Pattern for time-series data: group events into time-bucketed documents to reduce document count.
- Include a `schemaVersion` field to support future migrations.

## Query Patterns

- Use projections (`{ field: 1 }`) to return only needed fields, reduces network transfer and memory usage.
- Use `$elemMatch` for querying and projecting specific array elements.
- Use `$in` for matching against a list of values. Use `$exists` and `$type` for schema variations.
- Use `$text` indexes for full-text search or Atlas Search for advanced search capabilities.
- Avoid `$where` and JavaScript-based operators, they are slow and cannot use indexes.

## Aggregation Framework

The rest: https://github.com/RightNow-AI/openfang/blob/HEAD/crates/openfang-skills/bundled/mongodb/SKILL.md