Which ORMs does this skill support?

This skill provides specific patterns for popular TypeScript/JavaScript ORMs including Prisma, Drizzle, TypeORM, and Sequelize.

Does it help with connection management?

Yes, it detects issues like creating new connections inside functions and slow external API calls inside database transactions.

Does it provide automated fixes?

It provides standardized 'Fix Patterns' that Claude can use as templates to refactor inefficient code into batched queries or parallelized executions.

Can it help with PostgreSQL performance specifically?

Yes, it includes specialized SQL diagnostic queries for PostgreSQL to find slow queries and identify columns that require indexing based on scan patterns.

How does it detect N+1 queries?

It utilizes domain-specific grep patterns to identify database calls made inside iterative loops like .map(), .forEach(), or for-of loops.

Database Anti-Pattern Detection

Name: Database Anti-Pattern Detection
Author: antoineschaller

byantoineschaller

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数据库管理

Identifies and resolves common database performance bottlenecks and inefficient query patterns in modern ORMs.

关于

The Database Anti-Patterns skill equips Claude with specialized knowledge to audit your codebase for performance-draining database behaviors. It provides automated detection strategies for common issues like N+1 queries, unbounded fetches, and sequential execution patterns across popular ORMs like Prisma, Drizzle, and TypeORM. Beyond simple detection, it offers production-ready refactoring templates to optimize query parallelization, implement cursor-based pagination, and manage connection pools effectively, ensuring your backend remains scalable and responsive.

主要功能

Best practices for connection pool and transaction management
N+1 query detection for major TypeScript ORMs
Parallelization patterns for sequential database calls
Unbounded fetch identification for large dataset safety
1 GitHub stars
SQL diagnostic queries for finding missing indexes

使用场景

Auditing legacy codebases for hidden performance bottlenecks
Automating code reviews for database query efficiency
Optimizing backend API response times and database load

关于

主要功能

Best practices for connection pool and transaction management
N+1 query detection for major TypeScript ORMs
Parallelization patterns for sequential database calls
Unbounded fetch identification for large dataset safety
1 GitHub stars
SQL diagnostic queries for finding missing indexes

使用场景

Auditing legacy codebases for hidden performance bottlenecks
Automating code reviews for database query efficiency
Optimizing backend API response times and database load