メニュー
Generates dbt tests including schema tests, data quality tests, and freshness checks. Use when adding tests to dbt models or implementing data quality validation.
| name | test-generator |
| description | Generates dbt tests including schema tests, data quality tests, and freshness checks. Use when adding tests to dbt models or implementing data quality validation. |
Generate comprehensive tests for dbt models including schema tests, data quality tests, and freshness checks.
# models/schema.yml
version: 2
models:
- name: stg_orders
description: Staging orders table
columns:
- name: order_id
description: Unique order identifier
tests:
- unique
- not_null
- name: customer_id
description: Customer reference
tests:
- not_null
- relationships:
to: ref('stg_customers')
field: customer_id
- name: order_status
description: Order status
tests:
- accepted_values:
values: ['pending', 'processing', 'shipped', 'delivered', 'cancelled']
- name: order_total
description: Total order amount
tests:
- not_null
- dbt_utils.accepted_range:
min_value: 0
-- tests/assert_positive_revenue.sql
select
order_id,
order_total
from {{ ref('fct_orders') }}
where order_total < 0
# models/sources.yml
version: 2
sources:
- name: raw
database: analytics
schema: raw_data
tables:
- name: orders
description: Raw orders data
freshness:
warn_after: {count: 12, period: hour}
error_after: {count: 24, period: hour}
loaded_at_field: created_at
# Run all tests
dbt test
# Run tests for specific model
dbt test --select stg_orders
# Run specific test type
dbt test --select test_type:unique
dbt test --select test_type:not_null
Schema tests:
dbt_utils tests:
Custom tests:
Creates and validates Azure Resource Manager (ARM) templates for infrastructure deployment. Use when creating ARM templates, deploying Azure infrastructure as code, or validating Azure templates.
Analyzes Azure costs and provides optimization recommendations including reserved instances, rightsizing, and unused resources. Use when optimizing Azure spending or analyzing Azure costs.
Creates dbt models with proper layering (staging, marts), incremental strategies, and documentation. Use when creating dbt models, organizing data transformations, or implementing incremental models.
Configures Google Cloud Build pipelines with caching, parallel builds, and optimization. Use when setting up Cloud Build, optimizing build performance, or configuring CI/CD pipelines.
Analyzes GCP costs and provides optimization recommendations including committed use discounts, rightsizing, and unused resources. Use when optimizing GCP spending or analyzing GCP costs.
Create custom GitHub Actions (composite, Docker, or JavaScript). Use when building reusable actions, creating custom workflow steps, or packaging logic for distribution. Trigger words include "create action", "custom action", "build action", "composite action", "Docker action".