Is this skill suitable for schema design?

While it offers some model relationship insights, it is primarily focused on query efficiency; for deep architectural reviews, it is best used alongside the 'schema-reviewer' skill.

Does it provide actual code fixes?

Yes, it generates framework-specific code snippets that demonstrate how to refactor inefficient queries or implement proper transaction handling.

Can it detect missing database transactions?

Yes, it reviews related create, update, or delete operations to ensure they are wrapped in atomic transactions to maintain data integrity.

How does it help prevent N+1 queries?

The skill analyzes your data fetching patterns within loops and recommends appropriate 'include', 'selectinload', or 'prefetch_related' calls based on your specific framework.

Which ORMs does this skill support?

ORM Reviewer supports a wide range of popular frameworks including Prisma, TypeORM, SQLAlchemy, Django ORM, and GORM.

ORM Reviewer

Name: ORM Reviewer
Author: physics91

byphysics91

Gestión de Bases de Datos

Reviews and optimizes ORM code for efficiency, transaction handling, and N+1 query prevention.

Acerca de

The ORM Reviewer skill is a specialized tool for Claude Code designed to audit Object-Relational Mapping code for performance bottlenecks and architectural flaws. It automatically detects patterns in popular frameworks like Prisma, TypeORM, SQLAlchemy, Django ORM, and GORM to identify common issues such as N+1 queries, inefficient loading strategies, and missing transactions. By providing actionable feedback and framework-specific code examples, it helps developers ensure their database interactions are scalable, performant, and reliable.

Características Principales

Automatic N+1 query detection and prevention strategies
Interactive transaction safety and atomic operation analysis
0 GitHub stars
Framework-specific pattern recognition (Prisma, TypeORM, SQLAlchemy, etc.)
Detailed reporting with status levels and recommended code fixes
Review of Eager vs. Lazy loading strategies across frameworks

Casos de Uso

Auditing existing codebases for database performance bottlenecks
Automating the review of database-heavy pull requests
Onboarding new developers to project-specific ORM best practices

Acerca de

Características Principales

Automatic N+1 query detection and prevention strategies
Interactive transaction safety and atomic operation analysis
0 GitHub stars
Framework-specific pattern recognition (Prisma, TypeORM, SQLAlchemy, etc.)
Detailed reporting with status levels and recommended code fixes
Review of Eager vs. Lazy loading strategies across frameworks

Casos de Uso

Auditing existing codebases for database performance bottlenecks
Automating the review of database-heavy pull requests
Onboarding new developers to project-specific ORM best practices