Does it support vector databases for AI?

Yes, it provides guidance on using the pgvector extension and vector types for similarity search embeddings.

How does it handle performance for large tables?

It recommends declarative partitioning (Range, List, or Hash) and specialized indexes like BRIN for very large, naturally ordered datasets.

Does it help with database security?

Yes, it provides implementation patterns for Row-Level Security (RLS) policies to control data access at the row level.

What primary key type does this skill recommend?

It prefers BIGINT GENERATED ALWAYS AS IDENTITY for standard tables and UUID v7 for distributed or opaque identifiers.

Why does it suggest TEXT over VARCHAR(n)?

In PostgreSQL, there is no performance difference between the two; using TEXT with CHECK constraints is more flexible than hardcoded length limits.

PostgreSQL Table Design

Name: PostgreSQL Table Design
Author: HermeticOrmus

byHermeticOrmus

0•

Database Management

Architects high-performance, production-ready PostgreSQL schemas using modern best practices and advanced indexing patterns.

The PostgreSQL Table Design skill provides comprehensive guidance for creating robust database schemas tailored specifically for PostgreSQL's unique architecture. It enforces modern standards like 3NF normalization, identity columns over legacy serial types, and precise data type selection—such as TIMESTAMPTZ for global consistency and NUMERIC for exact decimals. Beyond basic modeling, the skill offers expert-level insights into indexing strategies (B-tree, GIN, GiST), MVCC-aware performance tuning, Row-Level Security, and advanced features like partitioning and vector search. It is an essential tool for developers building scalable backends who need to ensure data integrity and query efficiency from day one.

Key Features

01Optimized data type selection including JSONB, Vector, and Range types

020 GitHub stars

03Performance-tuned patterns for insert-heavy and update-heavy workloads

04Comprehensive indexing strategies including Partial, Covering, and Expression indexes

05Declarative partitioning and schema evolution best practices

06Implementation of Row-Level Security (RLS) and advanced constraints

Use Cases

01Architecting a scalable multi-tenant SaaS database with Row-Level Security

02Migrating legacy database schemas to modern PostgreSQL standards

03Optimizing high-traffic tables to handle MVCC bloat and index maintenance

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add hermeticormus/after-the-third-cup postgresql

For use in Claude.ai and ChatGPT

Download Skill