dbt-project-evaluator¶

Tested version: 1.2.4 | Integration tested: Yes (Lakehouse only)

dbt-project-evaluator audits your dbt project against best practices: model naming, documentation coverage, test coverage, DAG structure, modeling conventions, and more.

Compute engine support¶

Compute engine	Status
Lakehouse (FabricSpark)	Tested
Data Warehouse (Fabric)	Not compatible — upstream PR dbt-labs/dbt-project-evaluator#576 adds Fabric DW support

Dispatch configuration¶

dispatch:
  - macro_namespace: dbt_project_evaluator
    search_order: ['your_project_name', 'dbt', 'dbt_project_evaluator']
  - macro_namespace: dbt_utils
    search_order: ['your_project_name', 'dbt', 'dbt_utils']

Macro compatibility¶

All dbt-project-evaluator macros work on Lakehouse without adapter-specific overrides — the package's logic relies on dbt's graph context and standard SQL operations that Spark SQL handles natively.

Notes¶

Depends on dbt-utils. Include the dbt-utils dispatch configuration alongside the project-evaluator one.
If your project DAG depth exceeds the default, override max_depth_dag in your dbt_project.yml vars. The integration tests set it to 9:

vars:
  max_depth_dag: 9

- The package's integration_tests subdirectory has an internal local dependency (exclude_package/) that cannot be resolved when installed as a git subdirectory package. This only affects running the package's own integration tests, not normal use of the package against your project.