Airflow DAG Authoring
Streamlines the creation, planning, and validation of Apache Airflow DAGs using industry best practices and structured MCP tools.
The Airflow DAG Authoring skill provides a comprehensive framework for developing robust data pipelines within Claude Code. It guides users through a structured six-phase workflow—Discovery, Planning, Implementation, Validation, Testing, and Iteration—ensuring that every DAG is built according to modern standards like the TaskFlow API. By leveraging Model Context Protocol (MCP) tools instead of fragile CLI commands, this skill provides real-time feedback on import errors, environment constraints, and configuration warnings, making it an essential tool for data engineers seeking to build production-grade workflows efficiently.