| name | testing-dags |
| description | Complex DAG testing workflows with debugging and fixing cycles. Use for multi-step testing requests like "test this dag and fix it if it fails", "test and debug", "run the pipeline and troubleshoot issues". |
DAG Testing Skill
Use the Airflow VS Code extension tools to test, debug, and fix DAGs in iterative cycles.
First Action: Trigger the DAG
When the user asks to test a DAG, your first action should be:
trigger_dag_run with the provided DAG ID and config
Do not do pre-flight checks unless the user asks for them.
Testing Workflow Overview
- Trigger and monitor
- If success, summarize
- If failed, debug
- Fix and retest
Phase 1: Trigger and Monitor
- Trigger:
trigger_dag_run
- Monitor:
- Use
get_dag_runs to check state
- If a specific run ID is known, use
get_dag_run_detail
Response Interpretation
- Success: summarize duration and outcome
- Failed: move to Phase 2
- Running: ask whether to keep polling
Phase 2: Debug Failures
- Use
analyse_dag_latest_run for a full analysis of the latest run
- If a specific run ID is known, use
get_dag_run_detail
- If task logs are needed, open
go_to_dag_log_view
Phase 3: Fix and Retest
- Apply fixes in the DAG or related systems
- Re-trigger with
trigger_dag_run
- Re-check with
get_dag_runs or get_dag_run_detail
Notes
- Prefer
analyse_dag_latest_run for fast triage
- Use
get_dag_history when comparing across days