Car Wash Operations
A filthy operational dataset — ghost records, orphaned orders, typo'd customers, raw enum variants. Tests judgment under messy real-world data: what gets fixed, quarantined, or wrongly promoted.
51legacy 67
Interesting but UnreliableGPT-5.4 showed better file-level rigor than Opus on SVC-007 and duplicate-customer conflict evidence, but strict scoring centers migration safety. Ghost/test records survived as canonical data, Terrence Blackwood was promoted to a customer, status/payment values remained raw enough for magic/case variants to survive, and the canonical customer count ballooned. The output is a review scaffold, not a trustworthy migration.
OverlayDownload radar
1Claude Opus 4.886
2GPT-5.555
3Gemini 3.5 Flash (High) Fast51
4GPT-5.451
5Opus 4.748
What it nailed
- Completed the required artifact set.
- Accounted for the full file corpus in the cross-review analysis.
- Parsed deshawn_services.tsv and surfaced the SVC-007 conflict.
- Preserved useful conflict evidence for some duplicate customer cases.
Where it slipped
- Promoted Mickey Mouse, Test Customer, and Asdf Asdf into canonical data.
- Promoted Terrence Blackwood to a canonical customer.
- Left status and payment methods raw enough that case variants and magic survived.
- Over-expanded the canonical customer table.
Misses Three Or More Primary CanariesPromotes Ghost RecordsPromotes Orphan Order