How does this help with SQL injection protection?

By using the Drizzle ORM query builder for all measure and dimension definitions, the skill ensures that all generated SQL is safely parameterized.

Does this skill support many-to-many relationships?

Yes, it provides specific patterns for 'belongsToMany' joins using junction tables and specialized security filters for those relationships.

What is Drizzle Cube?

Drizzle Cube is a semantic layer for Drizzle ORM that allows you to define structured data models (cubes) for analytical queries with built-in SQL generation.

Why is the security context mandatory in this skill?

Security context filters ensure that every analytical query is automatically isolated by tenant (e.g., organizationId), preventing unauthorized data access.

Which databases are supported?

Drizzle Cube and this skill work identically across PostgreSQL, MySQL, and SQLite, with the database type auto-detected from your Drizzle instance.

Drizzle Cube Definition

Name: Drizzle Cube Definition
Author: cliftonc

bycliftonc

데이터베이스 관리

Simplifies the creation of secure, type-safe semantic layer cube definitions for Drizzle ORM-based applications.

소개

The dc-cube-definition skill empowers developers to architect sophisticated semantic layers within Drizzle Cube environments. It provides standardized patterns for defining measures, dimensions, and complex relationships while enforcing critical security context filters for multi-tenant data isolation. By leveraging Drizzle ORM's type safety, this skill ensures that analytical queries are validated at compile-time and protected against SQL injection, making it an essential tool for building robust business intelligence and data reporting features within a modern TypeScript stack.

주요 기능

Pre-configured measure types including count, sum, average, and filtered aggregations
0 GitHub stars
Automated generation of Drizzle-first cube definitions with full type safety
Standardized dimension mapping for string, number, boolean, and time-based data
Mandatory security context implementation for secure multi-tenant data isolation
Support for complex join relationships including Star Schema and Many-to-Many patterns

사용 사례

Mapping Drizzle ORM schemas to an analytical model for automated SQL generation
Defining a semantic layer for complex business intelligence reporting
Building a multi-tenant analytics dashboard for a SaaS application

소개

주요 기능

Pre-configured measure types including count, sum, average, and filtered aggregations
0 GitHub stars
Automated generation of Drizzle-first cube definitions with full type safety
Standardized dimension mapping for string, number, boolean, and time-based data
Mandatory security context implementation for secure multi-tenant data isolation
Support for complex join relationships including Star Schema and Many-to-Many patterns

사용 사례

Mapping Drizzle ORM schemas to an analytical model for automated SQL generation
Defining a semantic layer for complex business intelligence reporting
Building a multi-tenant analytics dashboard for a SaaS application