Works with the AI tools you already use
DB Query Optimizer
Detects and fixes N+1 queries, missing indexes, and ORM performance bottlenecks in SQL, Prisma, Django, and more.
Free
See it in action
You say
Why is this Prisma call slow? It fetches all posts, and then for each post, my UI displays the author name and the count of comments. It works fine locally but hangs in production.
Your agent does
This is a classic N+1 query. You are fetching N posts, then triggering 2 additional queries per post for the author and comments. In production with 100 posts, this is 201 queries.
Fix: Update your Prisma findMany to include: include: { author: true, _count: { select: { comments: true } } }
About this skill
The problem
Database performance issues often stay hidden during development because ORM code looks clean despite executing inefficiently. N+1 queries and missing indexes only reveal themselves as catastrophic slowdowns or connection pool exhaustion once your data volume grows in production.
What it does
- Identifies N+1 query patterns in ORM code and provides the exact eager-loading or batching syntax for your specific framework.
- Analyzes
EXPLAINandEXPLAIN ANALYZEoutput to detect sequential scans and inefficient query plans. - Flags missing indexes on foreign keys,
WHEREclauses, andORDER BYstatements, accounting for composite index column order. - Detects application-level filtering and pagination bugs that should be handled at the database layer.
- Diagnoses connection pool exhaustion caused by high query volume per request.
Frameworks & tools
Supports Prisma, Sequelize, TypeORM, Django ORM, ActiveRecord, SQLAlchemy, and Eloquent. Works with PostgreSQL, MySQL, and SQLite.
Why this beats prompting it yourself
General LLMs often suggest generic fixes or hallucinate ORM methods that do not exist. This skill uses framework-specific reference patterns to ensure the suggested fix is syntactically correct and actually addresses the underlying execution plan rather than just making the code look better.
Use cases
- Auditing an API endpoint that has become progressively slower as the database grows.
- Refactoring legacy ORM code to eliminate N+1 queries in serializers and view layers.
- Optimizing database performance by analyzing slow query logs and execution plans.
- Troubleshooting intermittent database timeouts and connection pool errors under load.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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