refactoring-dbt-models

What problem does it solve?

Refactoring dbt models can silently break downstream transformations when columns, types, logic, or dependencies change, causing incorrect results or failing builds.

Core Features & Use Cases

• Downstream dependency discovery: Finds all dependent models (including transitive impacts) before any change.
• Refactoring strategy planning: Chooses an approach such as extracting CTEs to intermediate models, creating macros, or splitting join logic.
• Safer incremental execution: Refactors one change at a time, then validates with compile/build and output sampling to confirm behavior matches the original.
• Use case: You want to reorganize a complex model that currently feeds multiple downstream analytics models, and you must ensure renames/type changes don’t break consumers.

Quick Start

Ask the AI to refactor your dbt model while first enumerating all downstream models and validating output after each single refactoring step.