How does it handle security and data access?

It includes implementation patterns for Row-Level Security (RLS), allowing you to define fine-grained access control policies directly at the database level.

Does it address common PostgreSQL 'gotchas'?

Yes, it warns about common issues such as case-sensitivity in identifiers, the lack of automatic foreign key indexing, and how MVCC handles row updates.

What is the preferred primary key type recommended by this skill?

The skill recommends using BIGINT GENERATED ALWAYS AS IDENTITY for most reference tables, suggesting UUIDs only when global uniqueness or opacity is specifically required.

Does it provide guidance on specialized data types like JSON or Vectors?

Absolutely. It covers the optimal use of JSONB for semi-structured data, GIN indexing for search, and vector types for AI-driven similarity searches.

Does this skill help with performance for large datasets?

Yes, it provides detailed strategies for table partitioning (Range, List, Hash) and the use of BRIN indexes for very large, naturally ordered data like time-series logs.

PostgreSQL Table Design

Name: PostgreSQL Table Design
Author: linehaul-ai

bylinehaul-ai

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Database Management

Designs high-performance, production-ready PostgreSQL schemas following industry best practices and modern database patterns.

This skill provides comprehensive guidance for architecting PostgreSQL databases, focusing on schema normalization, optimal data type selection, and advanced indexing strategies. It helps developers avoid common pitfalls like silent coercions and unindexed foreign keys while leveraging powerful features such as Row-Level Security (RLS), partitioning for large datasets, and specialized types for JSONB, vectors, and full-text search. Whether building a new application or optimizing an existing database, this skill ensures your PostgreSQL implementation is scalable, maintainable, and performance-optimized.

Key Features

01Advanced schema normalization and 3NF design patterns

02Optimal data type selection including JSONB, UUID, and pgvector

03Comprehensive indexing strategies using B-tree, GIN, GiST, and BRIN

04Performance tuning for insert-heavy and update-heavy workloads

05Implementation of Row-Level Security (RLS) and declarative partitioning

061 GitHub stars

Use Cases

01Architecting a new SaaS backend with scalable and normalized table structures

02Optimizing slow queries through advanced indexing and table partitioning

03Implementing secure multi-tenant data access using Row-Level Security policies

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add linehaul-ai/linehaulai-claude-marketplace postgres

For use in Claude.ai and ChatGPT

Download Skill