dbt-transformation-patterns
FeaturedMaster dbt (data build tool) for analytics engineering with model organization, testing, documentation, and incremental strategies. Use when building data transformations, creating data models, or implementing analytics engineering best practices.
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Quality Score: 93/100
Skill Content
Details
- Author
- wshobson
- Repository
- wshobson/agents
- Created
- 1 years ago
- Last Updated
- 4 days ago
- Language
- Python
- License
- MIT
Integrates with
Similar Skills
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dbt-transformation-patterns
Master dbt (data build tool) for analytics engineering with model organization, testing, documentation, and incremental strategies. Use when building data transformations, creating data models, or implementing analytics engineering best practices.
dbt-patterns
dbt model design, ref chains, sources, tests, macros, incremental strategies, materializations, and documentation best practices. Use this skill whenever the user is writing or reviewing dbt models, configuring dbt tests, designing model layers (staging/intermediate/marts), asking about incremental models, choosing materializations, writing macros, setting up sources.yml, or troubleshooting dbt run/test failures. Also trigger when the user mentions dbt refs, lineage graphs, model dependencies, dbt Cloud, the dbt CLI, or when they want to transform data already in the warehouse using SQL. If the project uses dbt at all, this skill should be active for any transformation questions.
building-dbt-models
Build well-structured dbt models — staging/intermediate/marts layers, ref() and source(), materializations, and incremental models with the right strategy. Use when creating or refactoring dbt models, choosing table vs view vs incremental, structuring a dbt project, or writing incremental logic.