postgres-patterns

PostgreSQL query optimization involves evaluating predicates, data types, and execution plans to choose efficient indexes and query shapes for filters, joins, and pagination. This Skill reviews your SQL to identify causes of slow reporting queries and applies production-safe tuning patterns.

Schema design for PostgreSQL requires selecting database types and constraints that improve correctness, performance, and maintainability. This Skill guides you in picking the right data types and constraints during migration design to prevent poor indexing and ensure production readiness.

Row level security in PostgreSQL applies access policies to restrict data visibility based on user context. This Skill provides row level security patterns and evaluates access policies to produce deterministic, production-safe security configurations for your database.

Index selection in PostgreSQL should target common filters, joins, pagination, and queue processing workloads. This Skill evaluates your predicates and execution plans to recommend efficient index choices that improve database performance without introducing anti-patterns.

Yes, PostgreSQL connection settings and monitoring checks are covered as part of security and operations guidance. This Skill applies connection pooling configurations and anti-pattern detection to ensure production readiness in backend environments.

PostgreSQL migrations can introduce poor indexing when schema changes ignore predicate evaluation and data type selection. This Skill reviews your migration design to detect anti-patterns and suggests safer indexing and schema patterns for production backends.