What common PostgreSQL 'gotchas' does this skill address?

It warns against common pitfalls like silent identifier lowercasing, the lack of auto-indexed foreign keys, and the behavior of NULLs in unique constraints.

Can this skill help with database security?

Yes, it includes detailed instructions and policies for implementing Row-Level Security (RLS), ensuring that users can only access the data they are authorized to see.

Does it support advanced PostgreSQL features like JSONB?

Yes, it provides specific guidance on when to use JSONB for semi-structured data and how to index it using GIN indexes for maximum search efficiency.

How does this skill improve database performance?

It guides the user to use appropriate index types (B-tree, GIN, GiST), optimizes data types to reduce storage bloat, and provides patterns for efficient table partitioning.

Why does it prefer BIGINT over UUID for primary keys?

While UUIDs offer global uniqueness, BIGINT identity columns are generally more performant for indexing, sorting, and join operations within a standard relational database.

PostgreSQL Table Design

Name: PostgreSQL Table Design
Author: HermeticOrmus

byHermeticOrmus

Database Management

Architects high-performance PostgreSQL schemas using industry best practices for data integrity, indexing, and advanced features.

About

The PostgreSQL Table Design skill empowers Claude to act as a senior database architect, providing domain-specific guidance for creating robust relational schemas. It enforces critical best practices such as Third Normal Form (3NF) normalization, precise data type selection (preferring TIMESTAMPTZ and BIGINT), and sophisticated indexing strategies like B-tree, GIN, and GiST. Beyond basic table structure, it offers deep expertise in performance patterns for update-heavy workloads, Row-Level Security (RLS), and declarative partitioning for large-scale datasets. This skill ensures that your database layer is built on a solid 'Gold Hat' foundation—prioritizing efficiency, maintainability, and empowerment over technical debt.

Key Features

Scalability strategies including RANGE, LIST, and HASH partitioning for large tables.
Optimized data type selection including JSONB, TIMESTAMPTZ, and identity columns.
Implementation patterns for Row-Level Security (RLS) and complex constraints.
Advanced indexing guidance for B-tree, GIN, GiST, and partial indexes.
0 GitHub stars
Automated schema normalization (3NF) to eliminate redundancy and update anomalies.

Use Cases

Implementing complex multi-tenant security policies directly at the database layer.
Refactoring existing schemas to improve query performance and data integrity.
Designing a scalable relational database for a modern web application.

About

Key Features

Scalability strategies including RANGE, LIST, and HASH partitioning for large tables.
Optimized data type selection including JSONB, TIMESTAMPTZ, and identity columns.
Implementation patterns for Row-Level Security (RLS) and complex constraints.
Advanced indexing guidance for B-tree, GIN, GiST, and partial indexes.
0 GitHub stars
Automated schema normalization (3NF) to eliminate redundancy and update anomalies.

Use Cases

Implementing complex multi-tenant security policies directly at the database layer.
Refactoring existing schemas to improve query performance and data integrity.
Designing a scalable relational database for a modern web application.