What databases does this skill support?

While focused on Supabase, the best practices and performance optimizations apply to any modern PostgreSQL database implementation.

How does it improve query performance?

It analyzes query patterns, suggests missing or partial indexes, and provides optimized SQL examples based on Postgres execution plans and metrics.

Does this cover database connection management?

Yes, it provides critical rules for connection pooling, managing active connections, and preventing common throughput bottlenecks.

Can this skill help with Row-Level Security (RLS)?

Yes, it includes specific guidelines and implementation patterns for securing your data using Postgres RLS and Supabase Auth integration.

Supabase Postgres Best Practices

Name: Supabase Postgres Best Practices
Author: guaderrama

byguaderrama

0•

データベース管理

Optimizes Postgres database performance, schema design, and security configurations specifically for Supabase environments.

This Claude Code skill provides a comprehensive performance optimization framework for Postgres databases, specifically tailored for the Supabase ecosystem. It offers automated guidance across eight critical categories, ranging from query performance and connection management to Row-Level Security (RLS) and advanced schema design. By providing detailed 'incorrect vs. correct' SQL examples and query plan analysis, it helps developers build scalable, secure, and high-performing database architectures while adhering to production-ready standards.

主な機能

01Comprehensive Row-Level Security (RLS) implementation patterns

020 GitHub stars

03Advanced schema design and concurrency locking strategies

04Automated SQL query optimization and indexing recommendations

05Efficient database connection and pooling management guidance

06Detailed performance metrics and query plan analysis

ユースケース

01Refactoring slow SQL queries for better execution times and lower resource usage

02Troubleshooting database bottlenecks and connection pooling issues in production

03Designing secure database schemas with robust Row-Level Security policies

主な機能

01Comprehensive Row-Level Security (RLS) implementation patterns

020 GitHub stars

03Advanced schema design and concurrency locking strategies

04Automated SQL query optimization and indexing recommendations

05Efficient database connection and pooling management guidance

06Detailed performance metrics and query plan analysis

ユースケース

01Refactoring slow SQL queries for better execution times and lower resource usage

02Troubleshooting database bottlenecks and connection pooling issues in production

03Designing secure database schemas with robust Row-Level Security policies