How does it handle SQL formatting?

It enforces a standardized structure requiring all refs at the top in CTEs, descriptive CTE naming, 4-space indentation, and explicit join qualifiers.

Does it support staging, integration, and warehouse layers?

Absolutely. It has specific rules for stg_, int_, _dim, and _fct prefixes, including directory structure and materialization requirements for each layer.

Does it help with dbt testing and documentation?

Yes, it validates that every model has a schema.yml entry, primary keys have unique/not_null tests, and models are 100% documented.

When does the dbt Development skill activate?

The skill is proactive; it triggers whenever you are about to create or modify a .sql file within the models/ directory of a dbt project.

Can I use my team's specific dbt coding standards?

Yes, the skill prioritizes project-specific files like .dbt-conventions.md or dbt_coding_conventions.md in your project root before falling back to defaults.

dbt Development

Name: dbt Development
Author: rittmananalytics

byrittmananalytics

데이터베이스 관리

Enforces standardized dbt coding conventions and validates model structures across staging, integration, and warehouse layers.

소개

The dbt Development skill provides a proactive framework for data engineers to maintain high-quality dbt projects. It automatically activates before SQL is written to ensure adherence to strict naming conventions, SQL structure patterns (like CTE-first designs), and field ordering rules. By validating models against project-specific or industry-standard conventions, it helps teams avoid technical debt, ensures consistent documentation, and mandates rigorous testing coverage for every model from staging to final facts and dimensions.

주요 기능

Support for project-specific convention overrides via local markdown files
Proactive validation triggered before writing dbt SQL models
Automated testing and documentation coverage validation
0 GitHub stars
Standardized SQL structure enforcement using CTE patterns and best practices
Layer-specific naming conventions for staging, integration, and warehouse models

사용 사례

Auditing existing dbt projects for missing tests and documentation
Creating new staging models with standardized prefixes and primary key patterns
Refactoring complex integration logic into clean, readable CTE-based SQL

소개

주요 기능

Support for project-specific convention overrides via local markdown files
Proactive validation triggered before writing dbt SQL models
Automated testing and documentation coverage validation
0 GitHub stars
Standardized SQL structure enforcement using CTE patterns and best practices
Layer-specific naming conventions for staging, integration, and warehouse models

사용 사례

Auditing existing dbt projects for missing tests and documentation
Creating new staging models with standardized prefixes and primary key patterns
Refactoring complex integration logic into clean, readable CTE-based SQL