Can I use these patterns for standard PostgreSQL databases?

While these patterns are optimized for InsForge's PostgREST backend, the SQL logic and indexing strategies follow standard PostgreSQL best practices and are applicable to most SQL environments.

What kind of application features are covered?

The skill covers essential modern app features including social following systems, 'like' mechanics, nested comment threads, and organization-based multi-tenancy.

Does this skill include security best practices?

Yes, every pattern includes Row Level Security (RLS) policies to ensure that users can only access the data they are authorized to see, preventing data leaks at the database level.

What is InsForge and how does this skill help?

InsForge is a backend platform that uses PostgREST to serve a RESTful API from PostgreSQL. This skill provides the specific SQL patterns and SDK queries required to build secure, high-performance apps on that stack.

InsForge Database Patterns

Name: InsForge Database Patterns
Author: Microck

byMicrock

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Database Management

Provides optimized PostgreSQL schema patterns and Row Level Security (RLS) policies specifically for InsForge and PostgREST applications.

About

This skill equips Claude with specialized knowledge for designing robust database architectures within the InsForge ecosystem. It offers standardized implementation patterns for common application features like social follows, junction tables for likes, nested commenting systems, and complex multi-tenant SaaS structures. By using this skill, developers can ensure their generated schemas follow industry best practices for indexing, foreign key constraints, and granular security through PostgreSQL Row Level Security (RLS), while also receiving compatible InsForge SDK query examples.

Key Features

81 GitHub stars
Optimized indexing and foreign key strategies for PostgREST performance
Self-referential schema patterns for nested comments and threaded discussions
Granular Row Level Security (RLS) policy configurations for data isolation
Production-ready SQL templates for social graphs and many-to-many relationships
Multi-tenant organization scoping for SaaS application architectures

Use Cases

Implementing hierarchical data structures like nested comment threads or file systems
Developing a multi-tenant SaaS application with strict organization-level data privacy
Building a social media platform with follower/following mechanics and content likes

About

Key Features

81 GitHub stars
Optimized indexing and foreign key strategies for PostgREST performance
Self-referential schema patterns for nested comments and threaded discussions
Granular Row Level Security (RLS) policy configurations for data isolation
Production-ready SQL templates for social graphs and many-to-many relationships
Multi-tenant organization scoping for SaaS application architectures

Use Cases

Implementing hierarchical data structures like nested comment threads or file systems
Developing a multi-tenant SaaS application with strict organization-level data privacy
Building a social media platform with follower/following mechanics and content likes