dbt Testing

SkillFiles & storage

Adds schema tests and data quality validation to dbt models. Use when working with dbt tests for: (1) Adding or modifying tests in schema.yml files (2) Task mentions "test", "validate", "data quality", "unique", "not_null", or "accepted_values" (3) Ensuring data integrity - primary keys, foreign keys, relationships (4) Debugging test failures or understanding why dbt test failed Matches existing project test patterns and YAML style before adding new tests.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the dbt Testing skill

What this skill tells your AI

The instructions your AI receives, as published by altimateai/data-engineering-skills in skills/dbt/testing-dbt-models/SKILL.md and read by ahel’s review.

Every model deserves at least one test. Primary keys need unique + not_null.

Workflow

1. Study Existing Test Patterns

CRITICAL: Match the project's existing testing style before adding new tests.

# Find all schema.yml files with tests
find . -name "schema.yml" -exec grep -l "tests:" {} \;

# Read existing tests to learn patterns
cat models/staging/schema.yml | head -100
cat models/marts/schema.yml | head -100

# Check for custom tests or dbt packages
ls tests/
cat packages.yml 2>/dev/null

Extract from existing tests:

  • YAML formatting style (indentation, spacing)
  • Test coverage depth (all columns vs key columns only)
  • Use of custom tests (dbt_utils, dbt_expectations, custom macros)
  • Description style (brief vs detailed)
  • Severity levels used (warn vs error)

2. Read Model SQL

cat models/<path>/<model_name>.sql

Identify: primary keys, foreign keys, categorical columns, date columns, business-critical fields.

3. Check Existing Tests for This Model

cat models/<path>/schema.yml | grep -A 50 "<model_name>"
# or
find . -name "schema.yml" -exec grep -l "<model_name>" {} \;

4. Identify Testable Columns

Column TypeRecommended Tests
Primary keyunique, not_null
Foreign keynot_null, relationships
Categoricalaccepted_values (ask user for valid values)
Required fieldnot_null
Date/timestampnot_null
Booleanaccepted_values: [true, false]

5. Write Tests in schema.yml

Match the existing style from step 1. Example format (adapt to project):

version: 2

models:
  - name: model_name
    description: "Brief description of what this model contains"
    columns:
      - name: primary_key_column
        description: "Unique identifier for this record"
        tests:
          - unique
          - not_null

      - name: foreign_key_column
        description: "Reference to related_model"
        tests:
          - not_null
          - relationships:
              to: ref('related_model')
              field: related_key_column

      - name: status
        description: "Current status of the record"
        tests:
          - not_null
          - accepted_values:
              values: ['pending', 'active', 'completed', 'cancelled']

      - name: created_at
        description: "Timestamp when record was created"
        tests:
          - not_null

6. Run Tests

# Test specific model
dbt test --select <model_name>

# Test with upstream
dbt test --select +<model_name>

7. Fix Failing Tests

Common failures and fixes:

FailureLikely CauseFix
unique failsDuplicate recordsAdd deduplication in model
not_null failsNULL values in sourceAdd COALESCE or filter
relationships failsOrphan recordsAdd WHERE clause or fix upstream
accepted_values failsNew/unexpected valuesUpdate accepted values list

Test Types Reference

Generic Tests (built-in)

tests:
  - unique
  - not_null
  - accepted_values:
      values: ['a', 'b', 'c']
  - relationships:
      to: ref('other_model')
      field: id

Custom Generic Tests

tests:
  - dbt_utils.expression_is_true:
      expression: "amount >= 0"
  - dbt_utils.recency:
      datepart: day
      field: created_at
      interval: 1

Singular Tests

Create tests/<test_name>.sql:

-- tests/assert_positive_revenue.sql
select *
from {{ ref('orders') }}
where revenue < 0

Anti-Patterns

  • Adding tests without checking existing project patterns first
  • Using different YAML formatting style than existing tests
  • Models without any tests
  • Primary keys without both unique AND not_null
  • Testing only obvious columns, ignoring business-critical ones
  • Hardcoding accepted_values without confirming with stakeholders
  • Adding dbt_utils tests when project doesn't use that package

Signals

GitHub stars
122
Forks
10
Last commit
Jul 2026
Advanced
Catalog kind
skill
Gateway key
testing-dbt-models
Source
github.com/altimateai/data-engineering-skills