How does it handle performance optimization?

It recommends B-tree indexes for filter columns and utilizes initPlan caching by wrapping JWT functions like auth.uid() in subqueries.

How does it manage database migrations?

It mandates a migration-first workflow where all RLS changes are tracked in isolated SQL files with clearly defined rollback procedures.

What is the main benefit of using this Supabase RLS skill?

It ensures your Supabase RLS policies are both ultra-secure and highly optimized for performance by following industry-standard best practices.

Does it distinguish between application-level and database-level security?

Yes, it emphasizes that while application-level filters improve intent and performance, the RLS policy remains the final and absolute security boundary.

Why is SECURITY DEFINER safety emphasized?

Improperly configured SECURITY DEFINER functions can lead to privilege escalation; this skill enforces search_path settings and schema qualification to mitigate these risks.

Supabase RLS Optimizer

Name: Supabase RLS Optimizer
Author: shoma-endo

byshoma-endo

데이터베이스 관리

Implements high-performance and secure Row Level Security (RLS) policies and functions for Supabase projects.

소개

This skill provides a standardized framework for implementing Supabase Row Level Security (RLS) with a focus on performance and security. It enforces best practices such as B-tree indexing on filter columns, leveraging initPlan caching via auth.uid() wrapping, and securing SECURITY DEFINER functions through schema qualification and search_path definitions. By following these guidelines, developers can ensure that security boundaries are strictly maintained at the database level while optimizing query execution plans and migration workflows.

주요 기능

Secure SECURITY DEFINER function patterns with schema qualification
Standardized error handling logic using RETURN false versus RAISE EXCEPTION
Migration-based workflow for RLS policy management and rollbacks
0 GitHub stars
Performance optimization through B-tree indexing and JWT function caching
Enforcement of security boundaries within the database layer

사용 사례

Scaling Supabase applications with complex multi-tenant security requirements
Hardening database security through robust Row Level Security implementations
Optimizing RLS query performance for high-traffic PostgreSQL databases

소개

주요 기능

Secure SECURITY DEFINER function patterns with schema qualification
Standardized error handling logic using RETURN false versus RAISE EXCEPTION
Migration-based workflow for RLS policy management and rollbacks
0 GitHub stars
Performance optimization through B-tree indexing and JWT function caching
Enforcement of security boundaries within the database layer

사용 사례

Scaling Supabase applications with complex multi-tenant security requirements
Hardening database security through robust Row Level Security implementations
Optimizing RLS query performance for high-traffic PostgreSQL databases