Workflow and best practices for writing Apache Airflow DAGs. Use when the user wants to create a new DAG, write pipeline code, or asks about DAG patterns and…
Guided workflow for creating Apache Airflow DAGs with validation and testing integration. Structured six-phase approach: discover environment and existing patterns, plan DAG structure, implement following best practices, validate with af CLI commands, test with user consent, and iterate on fixes CLI commands for discovery (af config connections, af config providers, af dags list) and validation (af dags errors, af dags get, af dags explore) provide immediate feedback on DAG correctness Integrates with testing-dags skill for comprehensive test-debug-fix-retest workflows and supports Astro-specific features like astro dev parse and DAG-only deploys References external best practices documentation covering correct patterns, anti-patterns, and Airflow 3-specific behavior DAG Authoring Skill This skill guides you through creating and validating Airflow DAGs using best practices and af CLI commands. For testing and debugging DAGs, see the testing-dags skill which covers the full test -> debug -> fix -> retest workflow. Running the CLI These commands assume af is on PATH. Run via astro otto to get it automatically, or install standalone with uv tool install astro-airflow-mcp. Workflow Overview
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by @sickn33