migrate-etl-package

Generates seed data, schema checks, and assertions for Snowflake & Jira project migrations.

1|1|Updated Apr 15, 2026

Search Tags:#automation #testing #database #migration #dbt #snowflake

Ready to run

npx skills add https://github.com/Snowflake-Labs/cortex-code-migrations --skill migrate-etl-package

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: migrate-etl-package
Source: https://github.com/Snowflake-Labs/cortex-code-migrations/tree/main/plugin/skills/migration/migrate-objects/actions/migrate-etl-package/dbt-test-gen
Command: npx skills add https://github.com/Snowflake-Labs/cortex-code-migrations --skill migrate-etl-package

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill helps automate the generation and execution of comprehensive database migration tests, reducing manual effort and increasing reliability.

Core Features & Use Cases

Test Automation: Generate seed data, schema validations, and detailed assertions for ETL processes.
End-to-End Validation: Ensure data integrity and transformation correctness before production deployment.
Use Case: Suppose you’re migrating multiple databases to Snowflake; use this Skill to create tests that verify data consistency, schema correctness, and transformation logic for each source.

Quick Start

Use the migrate-etl-package to generate testing artifacts for your Snowflake migration project, then deploy and run the tests in your environment.

Frequently Asked Questions about migrate-etl-package

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I automate database migration testing for Snowflake and dbt projects?▼

Database migration testing for Snowflake and dbt projects is automated by generating seed data, schema checks, and assertions aligned with source ETL logic. This validates data fidelity and transformation correctness before production deployment.

How do I validate ETL logic and data integrity during a database migration?▼

ETL logic and data integrity are validated during a database migration by generating detailed assertions and schema validations. This ensures data consistency and transformation correctness across your source databases.

What is AI-assisted database migration testing and how does it work?▼

AI-assisted database migration testing works by automating the creation of comprehensive testing artifacts, including seed data and schema checks. It reduces manual effort while increasing reliability for complex database migrations.

Do I need an existing dbt project to validate Snowflake database migrations?▼

Yes, validating Snowflake database migrations requires integration with an existing dbt project and Snowflake environment. This setup allows the automation to generate tests aligned with your source ETL logic.

What is the best way to ensure data consistency when migrating multiple databases to Snowflake?▼

The best way to ensure data consistency when migrating multiple databases to Snowflake is deploying automated tests that verify schema correctness and transformation logic for each source. This end-to-end validation catches discrepancies early.

What are the limitations of automating database migration tests with dbt?▼

Automating database migration tests with dbt is limited by its dependency on Snowflake integration and existing dbt projects. It is designed specifically for validating data fidelity and transformation correctness rather than general database administration.