Skill · Data
Dbt transformation patterns
Production-ready patterns for dbt (data build tool) including model organization, testing strategies, documentation, and incremental processing.
How to use it
- Start your plan and connect your AI once
- Ask for the task in your own words, or say it directly:
Use the Dbt transformation patterns skill to help me with this.Without a connection: copy the SKILL.md below into your AI's project instructions.
SKILL.md2 files in this skill
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.mdfor 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.