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dbt-unit-testing

Validate dbt models with mock inputs and expected outputs.

8|Updated Feb 23, 2026
Search Tags:#unit test#data validation#dbt#sql#transformation#model testing
One-click install
npx skills add https://github.com/rittmananalytics/wire-plugin --skill dbt-unit-testing-rittmananalytics
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: dbt-unit-testing
Source: https://github.com/rittmananalytics/wire-plugin/tree/main/skills/dbt-unit-testing
Command: npx skills add https://github.com/rittmananalytics/wire-plugin --skill dbt-unit-testing-rittmananalytics

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill facilitates the creation and execution of unit tests for dbt models, enabling developers to verify transformation logic in isolation before deployment.

Core Features & Use Cases

  • Mock Data Simulation: Enables defining mock input and expected output data for dbt models using various formats.
  • Automated Testing Workflow: Automates testing of complex transformation behaviors, such as regex extraction, window functions, and conditional logic.
  • Use Case: Suppose you have a dbt model with complex date calculations. Use this Skill to generate specific mock inputs and verify the output matches expectations, ensuring correctness before deployment.

Quick Start

Use the dbt unit testing skill to define a test that mocks model inputs and verifies output for a formula involving window functions.

Frequently Asked Questions about dbt-unit-testing

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

FAQPage Schema
How do I unit test dbt models with complex SQL transformations?▼

To unit test dbt models with complex SQL transformations, define mock inputs and expected outputs to verify logic in isolation. This ensures model correctness and automates regression checks before deployment.

What is the best way to mock input data for dbt model testing?▼

Mocking input data for dbt model testing involves specifying expected input and output datasets in various formats. This isolates transformation logic, like regex extraction or window functions, for automated validation.

Can I use automated unit testing for dbt models with ephemeral dependencies?▼

Yes, automated unit testing supports dbt models with ephemeral dependencies. It validates complex SQL logic and data transformations by mocking inputs to ensure regression checks pass correctly.

How do you write dbt unit tests for window functions and conditional logic?▼

Writing dbt unit tests for window functions involves generating specific mock inputs and verifying the output matches expectations. This validates complex transformation behaviors and conditional logic before deployment.

Does dbt unit testing require a specific dbt project setup?▼

Yes, dbt unit testing requires a dbt dependency. It operates within dbt projects to automate testing of complex transformation behaviors, ensuring model correctness through defined mock inputs and expected outputs.

What are the limitations of dbt unit testing for data validation?▼

dbt unit testing focuses on verifying transformation logic in isolation using mock data. It does not replace schema or data quality testing on actual production data, but ensures model correctness before deployment.

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