Apache Airflow DAG Patterns
Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.
Production-ready patterns for dbt (data build tool) including model organization, testing strategies, documentation, and incremental processing.
--- name: dbt-transformation-patterns description: "Production-ready patterns for dbt (data build tool) including model organization, testing strategies, documentation, and incremental processing." risk: none source: community date_added: "2026-02-27" --- # 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. ## 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.--- name: dbt-transformation-patterns description: "Production-ready patterns for dbt (data build tool) including model organization, testing strategies, documentation, and incremental processing." risk: none source: community date_added: "2026-02-27" --- # 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. ## 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.
Imported SKILL.md format for Claude Code, Codex and Cursor. Review the complete instructions and required tools before use. Package integrity checked; individual agent behavior has not been tested.