Can it fix all dbt errors automatically?

It uses dbt-autofix for common deprecations, but for complex issues, it strictly follows official dbt Labs documentation to suggest manual resolutions or stops to prevent incorrect changes.

What version of dbt Core is required for this migration?

This skill is specifically designed for projects running dbt Core v1.10 or higher.

How does the skill handle features not yet supported in Fusion?

For unsupported features like Python models or materialized views, the skill will flag them and offer to disable them using Jinja config blocks so the rest of the project can compile.

Does this skill provide a record of changes made to my code?

Yes, it creates a changes_made.md file that documents every error encountered, the specific fix applied, and the reasoning behind each change.

What is the final validation step for the migration?

The migration is considered successful only when the 'dbtf compile' command finishes with zero errors in the terminal.

dbt Fusion Migration

Name: dbt Fusion Migration
Author: dbt-labs

bydbt-labs

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Database Management

Migrates dbt Core projects to the dbt Fusion engine by resolving compatibility errors, deprecations, and unsupported configurations.

About

This skill provides a structured workflow for transitioning dbt projects from dbt Core v1.10+ to the next-generation dbt Fusion engine. It automates the detection of parsing errors, applies bulk fixes using dbt-autofix, and provides expert guidance for manual adjustments based on dbt Labs' official resources. By systematically handling unsupported features like Python models and custom configurations, this skill ensures projects achieve successful compilation on the Fusion engine while maintaining a detailed audit log of all modifications in a changes_made.md file.

Key Features

13 GitHub stars
Automated compatibility scanning using dbtf parse and debug
Detailed change logging and documentation of migration steps
Intelligent handling of unsupported features like Python models and materialized views
Validation of migration success through end-to-end project compilation
Bulk resolution of project deprecations via dbt-autofix integration

Use Cases

Upgrading a legacy dbt Core project to utilize the high-performance Fusion engine
Refactoring large dbt codebases to align with dbt Fusion's next-generation authoring layer
Auditing dbt projects for deprecated syntax and unsupported data platform configurations

About

Key Features

13 GitHub stars
Automated compatibility scanning using dbtf parse and debug
Detailed change logging and documentation of migration steps
Intelligent handling of unsupported features like Python models and materialized views
Validation of migration success through end-to-end project compilation
Bulk resolution of project deprecations via dbt-autofix integration

Use Cases

Upgrading a legacy dbt Core project to utilize the high-performance Fusion engine
Refactoring large dbt codebases to align with dbt Fusion's next-generation authoring layer
Auditing dbt projects for deprecated syntax and unsupported data platform configurations