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 ...
Best use case
dbt-transformation-patterns is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
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 ...
Teams using dbt-transformation-patterns should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/dbt-transformation-patterns/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How dbt-transformation-patterns Compares
| Feature / Agent | dbt-transformation-patterns | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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 ...
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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.
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