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Use dbt-transformation-patterns to design a dbt model-layer and naming convention for [source schemas], including data-quality tests, documentation, freshness checks, and an incremental strategy where appropriate.
Required inputs
[source schemas]
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SKILL.md
name: dbt-transformation-patternsdescription: Production-ready patterns for dbt (data build tool) including model organization, testing strategies, documentation, and incremental processing.metadata: aas-risk: none aas-source: community aas-date-added: '2026-02-27'
dbt Transformation Patterns
Production-ready patterns for dbt (data build tool) including model organization, testing strategies, documentation, and incremental processing.
Use this skill when
Building data transformation pipelines with dbt
Organizing models into staging, intermediate, and marts layers
Implementing data quality tests and documentation
Creating incremental models for large datasets
Setting up dbt project structure and conventions
Do not use this skill when
The project is not using dbt or a warehouse-backed workflow
You only need ad-hoc SQL queries
There is no access to source data or schemas
Instructions
Define model layers, naming, and ownership.
Implement tests, documentation, and freshness checks.
Choose materializations and incremental strategies.
Optimize runs with selectors and CI workflows.
If detailed patterns are required, open resources/implementation-playbook.md.
Resources
resources/implementation-playbook.md for detailed dbt patterns and examples.
Limitations
Use this skill only when the task clearly matches the scope described above.
Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.