Does this skill install dbt-expectations automatically?

The skill provides the necessary YAML configuration for your packages.yml and uses tool calls to run dbt deps, ensuring the environment is ready for advanced testing.

Does it modify my existing schema.yml files?

Yes, it uses file-editing tools to intelligently append or update test definitions within your existing dbt schema configurations without overwriting other data.

What types of tests can it generate?

It generates a wide range of tests including uniqueness, null checks, regex matching for emails/URLs, value ranges for metrics, and set membership for status codes.

Can it handle large dbt projects with many models?

Yes, it is designed with performance constraints in mind, using batch processing for columns and recommending model-specific updates for projects exceeding 50 models.

How does it verify that the generated rules work?

After writing the rules, the skill can execute dbt test commands for the specific models updated to ensure the new quality rules are passing correctly.

DBT Data Quality Rule Definer

Name: DBT Data Quality Rule Definer
Author: nerver111

bynerver111

0•

Database Management

Automates the definition and configuration of dbt data quality rules using dbt-expectations and intelligent schema analysis.

The DBT Data Quality Rule Definer is a specialized tool for data engineers that automates the implementation of robust testing frameworks within dbt projects. By leveraging the power of the dbt-expectations package, this skill intelligently analyzes model fields to suggest and write complex assertions—such as regex-based email validation, value range checks, and multi-column uniqueness—directly into your schema.yml files. It is optimized for performance, handling batch processing and automated validation to ensure data integrity across large-scale analytics projects without the manual overhead of YAML configuration.

Key Features

01Batch processing of schema updates to maintain high performance

02Integrated validation using dbt test to verify rule accuracy

03Automated dbt-expectations integration and package management

04Support for advanced validations including regex, sets, and ranges

05Intelligent field analysis for context-aware quality test generation

060 GitHub stars

Use Cases

01Enforcing standardized formatting rules for PII like emails and phone numbers

02Automating the migration from basic dbt tests to advanced dbt-expectations assertions

03Bootstrapping comprehensive data quality tests for new dbt staging models

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add nerver111/git-skill-test dbt-quality-rule-definer

For use in Claude.ai and ChatGPT

Key Features

01Batch processing of schema updates to maintain high performance

02Integrated validation using dbt test to verify rule accuracy

03Automated dbt-expectations integration and package management

04Support for advanced validations including regex, sets, and ranges

05Intelligent field analysis for context-aware quality test generation

060 GitHub stars

Use Cases

01Enforcing standardized formatting rules for PII like emails and phone numbers

02Automating the migration from basic dbt tests to advanced dbt-expectations assertions

03Bootstrapping comprehensive data quality tests for new dbt staging models

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add nerver111/git-skill-test dbt-quality-rule-definer

For use in Claude.ai and ChatGPT