orm

Detect and fix N+1 queries and transaction misuse across ORMs.

26|8|Updated Mar 19, 2026
One-click install
npx skills add https://github.com/arbazkhan971/godmode --skill orm
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: orm
Source: https://github.com/arbazkhan971/godmode/tree/main/skills/orm
Command: npx skills add https://github.com/arbazkhan971/godmode --skill orm

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Solve ORM data access inefficiencies by identifying and eliminating N+1 query patterns, improper transaction usage, and suboptimal pooling configurations.

Core Features & Use Cases

  • Detect N+1 queries and replace them with efficient eager loading strategies across Prisma, SQLAlchemy, Django ORM, and GORM.
  • Enforce safe transaction boundaries, proper connection pooling, and predictable performance under load.
  • Use case: A medium-sized service migrates from lazy-loading loops to joined queries, reducing latency and database load.

Quick Start

Audit your codebase to identify N+1 patterns and apply recommended ORM optimizations in one go.

Frequently Asked Questions about orm

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I fix N+1 query problems in my ORM?

Fix N+1 queries by detecting lazy-loading loops and replacing them with efficient eager loading strategies across ORMs like Prisma, SQLAlchemy, Django ORM, and GORM. This reduces database load and latency.

What is the best way to enforce safe transaction boundaries with SQLAlchemy or TypeORM?

Enforce safe transaction boundaries by auditing your codebase for improper transaction usage and applying guidelines for transactional safety. This ensures predictable performance under load.

Does this ORM optimization approach work with Python and Go stacks?

This ORM optimization approach works with multi-language stacks including TypeScript, JavaScript, Python, Go, and Ruby. It applies guidelines across PostgreSQL, MySQL, and SQLite databases.

How do I optimize connection pooling for a Prisma or GORM application?

Optimize connection pooling by identifying suboptimal pooling configurations and applying guidelines for proper connection management. This ensures production readiness and predictable performance.

Why does my Django ORM service have high latency under load?

High latency under load often results from N+1 query patterns, improper transaction usage, and suboptimal pooling configurations. Auditing your codebase identifies these specific data access inefficiencies.

When should I not use eager loading to fix ORM performance issues?

Eager loading may not be appropriate when it unnecessarily fetches large datasets that are rarely accessed, increasing memory overhead. Audit query patterns to balance joined queries against actual data requirements.