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testing-dbt-models

Add schema tests and validate data integrity in dbt models.

Updated Jun 10, 2026
Search Tags:#data integrity#dbt#ETL/ELT#data testing#dbt testing
One-click install
npx skills add https://github.com/AltimateAI/altimate-opencode-plugin --skill testing-dbt-models-altimateai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: testing-dbt-models
Source: https://github.com/AltimateAI/altimate-opencode-plugin/tree/main/skills/dbt/testing-dbt-models
Command: npx skills add https://github.com/AltimateAI/altimate-opencode-plugin --skill testing-dbt-models-altimateai

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill addresses the challenge of maintaining and validating the integrity of dbt models through schema tests and data quality checks.

Core Features & Use Cases

  • Schema Tests: Adds and modifies tests in schema.yml files to ensure the correctness of data structures.
  • Data Quality Validation: Validates data integrity including primary keys, foreign keys, and relationships.
  • Debugging: Assists in identifying and resolving test failures or understanding test outcomes.
  • Use Case: When you need to ensure that your dbt models are functioning correctly and that the data within them adheres to defined rules and standards.

Quick Start

Run the testing-dbt-models skill to add schema tests and perform data quality checks for your dbt model.

Frequently Asked Questions about testing-dbt-models

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

FAQPage Schema
How do I add schema tests to my dbt models?▼

To add schema tests to dbt models, you configure test definitions in your schema.yml files to validate data structures, primary keys, and foreign key relationships. This ensures your ETL/ELT data transformation workflows maintain strict data integrity.

Why do my dbt data tests fail during an ETL pipeline run?▼

dbt data tests fail during an ETL pipeline run when model data violates defined schema rules or relationship constraints. You can debug these test failures by examining the test outcomes to identify and resolve the underlying data integrity issues within your dbt models.

What is the best way to validate data quality in dbt transformations?▼

Validating data quality in dbt transformations is best achieved by applying schema tests to verify primary keys, foreign keys, and relationships within your models. This approach ensures data correctness and adherence to defined rules across ETL/ELT pipelines.

Do I need standard dbt model definitions to run data testing?▼

Yes, you need standard dbt model definitions to run data testing. The testing process relies on dbt's native testing capabilities and requires existing schema.yml files to properly apply schema tests and validate data integrity within your transformation workflows.

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