testing-dbt-models
SolidAdds 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.
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Quality Score: 82/100
Skill Content
Details
- Author
- AltimateAI
- Repository
- AltimateAI/data-engineering-skills
- Created
- 7 months ago
- Last Updated
- 1 months ago
- Language
- N/A
- License
- MIT
Bundled in these plugins
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data-quality
Use when adding or reviewing data quality tests for dbt models in warehouse-backed analytics projects. Covers dbt generic tests, singular tests (assert_*.sql), accepted-values macros, dbt_utils patterns, cross-system consistency tests, and warehouse-oriented validation. Use when writing data tests, creating assert_*.sql files, testing business logic, or validating referential integrity.
data-quality
Write systematic data quality checks — validation rules, Great Expectations suites, dbt tests, anomaly detection, null/type/range/referential integrity assertions, and monitoring patterns for production pipelines. Use this skill whenever the user is dealing with bad data in a pipeline, setting up validation before or after a load step, adding tests to dbt models, writing Great Expectations expectations, or trying to detect when upstream data has changed shape. Also trigger when stakeholders keep finding incorrect numbers, when a pipeline silently loads garbage, or when the user asks "how do I make sure my data is correct". Prevention is cheaper than debugging.
creating-dbt-models
Creates dbt models following project conventions. Use when working with dbt models for: (1) Creating new models (any layer - discovers project's naming conventions first) (2) Task mentions "create", "build", "add", "write", "new", or "implement" with model, table, or SQL (3) Modifying existing model logic, columns, joins, or transformations (4) Implementing a model from schema.yml specs or expected output requirements Discovers project conventions before writing. Runs dbt build (not just compile) to verify.