Ingest the Python + BigQuery pipeline script.
Identify all BigQuery job triggers and external calls.
Analyze cost exposure, including loops and missing byte limits.
Verify dry-run and execution modes with environment checks.
Check backfill and loop design for date ranges and idempotency.
Assess query safety, partition filters, and join explosion risks.
Evaluate safe writes and idempotency using MERGE or staging tables.
Confirm observability through logging and exception handling.
Generate a final report with PASS/FAIL status, patch list, and cost risks.