multiAI Summary Pending

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.

231 stars

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/dbt-transformation-patterns/SKILL.md --create-dirs "https://raw.githubusercontent.com/aiskillstore/marketplace/main/skills/sickn33/dbt-transformation-patterns/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/dbt-transformation-patterns/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How dbt-transformation-patterns Compares

Feature / Agentdbt-transformation-patternsStandard Approach
Platform SupportmultiLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/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 implementing analytics engineering best practices.

Which AI agents support this skill?

This skill is compatible with multi.

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.