Airflow ETL DAG Generator

## Overview Writing Airflow DAGs by hand is tedious and error-prone. This crystal accepts a natural-language description of your data sources, transformation requirements, and target storage, then produces a fully structured Python DAG file that follows Airflow 2.x best practices — ready to drop into your dags/ folder. ## What Gets Generated - Complete Python DAG file with a sensible `default_args` configuration - Extract, Transform, and Load tasks clearly separated into three stages - Retry policies, task-level timeouts, and failure alerting hooks - A pytest unit-test scaffold covering the core transformation logic ## Tech Stack Apache Airflow 2.6+, Python 3.10+. Optional integrations with dbt for transformation and Great Expectations for data quality checks are supported via configuration flags.