Agent skill · data analytics · rmyndharis
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.
Why this skill is useful
Provides specific patterns and strategies for dbt that enhance data transformation processes beyond generic SQL knowledge.
What it needs
About 1k tokens when loaded. Last updated 2026-08-02. 1,255 stars on the source repository.
What this skill does
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.
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills rmyndharis/dbt-transformation-patterns