Add schema-level YAML tests to dbt models and validate with dbt test.
npx skills add https://github.com/miptah21/skills --skill testing-dbt-models
Please help me install this Agent Skill. Skill: testing-dbt-models Source: https://github.com/miptah21/skills/tree/main/.agents/skills/testing-dbt-models Command: npx skills add https://github.com/miptah21/skills --skill testing-dbt-models
dbt models can silently degrade as sources change, breaking downstream analytics and pipelines without early warning, so you need reliable schema tests that match your project’s existing conventions.
Ask the agent to review the model SQL and existing schema.yml patterns, then propose the exact YAML tests to add for primary keys, foreign keys, required fields, and accepted categorical values before running dbt test for the selected model.
High-intent search queries and answers about installing and using this skill.
To add dbt schema tests, you update your schema.yml file with built-in test types like unique and relationships. This ensures primary key uniqueness and validates foreign key referential integrity to prevent broken analytics.
For categorical fields and required columns, use accepted_values and not_null schema tests in dbt. These tests enforce allowed categorical inputs and validate required fields, catching silent data degradation before it breaks downstream pipelines.
When updating schema.yml, you must match the repository's existing YAML formatting, test coverage depth, custom test usage, and severity conventions. This maintains consistency and prevents regressions across your dbt models.
dbt pipelines break when source data changes silently, but schema tests provide early warning. By applying data-integrity invariants in schema.yml, you catch issues like duplicate keys or invalid values before they impact analytics.
Yes, you validate dbt schema tests by running the dbt test command on your selected target model. This executes the configured uniqueness, relationships, and accepted_values checks to confirm data integrity.
schema.yml tests are limited to predefined checks like uniqueness, not_null, accepted_values, and relationships. Complex custom logic requires custom test macros, and severe test failures will halt pipelines if severity conventions are set to error.
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