mongodb-query-optimizer

What problem does it solve?

This Skill helps diagnose slow MongoDB queries and reduce resource usage by identifying inefficient query shapes, missing or suboptimal indexes, and aggregation pipeline anti-patterns so teams can improve latency and throughput.

Core Features & Use Cases

• Explain plan analysis: Run explain() to detect COLLSCANs, in-memory sorts, and examine keys/documents examined versus returned.
• Index recommendations: Propose compound indexes following equality→sort→range (ERS) rules and identify opportunities for covered queries.
• Atlas and MCP integration: Use Atlas Performance Advisor and slow query logs when Atlas API or MCP connection is available; fall back to query-shape advice when not.
• Aggregation and update guidance: Load aggregation-optimization and update-query references for pipeline-specific or oplog-efficient update suggestions.

Quick Start

Ask "Why is this query slow?" and provide the query, database name, collection name, and optionally a MongoDB connection string or Atlas project/cluster identifiers so the skill can run explain and suggest indexes.