DAG Authoring Skill

This skill guides you through creating and validating Airflow DAGs using best practices and the VS Code extension tools.

For testing and debugging DAGs, see the testing-dags skill.

Critical Warning: Use Extension Tools

Use the Airflow VS Code extension tools for all Airflow operations. Avoid running Airflow CLI commands for listing DAGs, checking logs, or inspecting runs.

Workflow Overview

1. Discover
2. Plan
3. Implement
4. Validate
5. Test (with user consent)
6. Iterate

Phase 1: Discover

Explore the codebase

Use file tools to find existing patterns:

• Search for existing DAGs in the repo
• Read similar DAGs for conventions
• Check requirements and providers in use

Query Airflow via extension tools

Use these tools to understand the environment:

• list_active_dags and list_paused_dags for naming conventions
• get_running_dags for current activity
• get_dag_history to see run cadence
• go_to_connections_view and go_to_variables_view for configuration
• go_to_providers_view and go_to_plugins_view for installed components
• go_to_server_health_view for health checks

Phase 2: Plan

Propose:

1. DAG structure (tasks, dependencies, schedule)
2. Operators to use
3. Connections and variables needed
4. Package changes if required

Get user approval before implementing.

Phase 3: Implement

1. Create or update the DAG file
2. Update dependencies if needed
3. Save the file

Phase 4: Validate

After the DAG is deployed to Airflow, validate via tools:

• Confirm the DAG appears in list_active_dags or list_paused_dags
• Use get_dag_source_code to verify the deployed source
• Review run history with get_dag_history

Phase 5: Test

Follow the testing-dags skill:

1. Ask for consent
2. Trigger with trigger_dag_run
3. Review results with get_dag_runs and analyse_dag_latest_run

Notes

• Avoid CLI checks like airflow dags list or astro dev run for operational status.
• Use the extension tools for runtime investigation and logs.