Audits a synthetic dataset (SDG output) for downstream-task utility against the real source data via the TSTR / TRTS / TRTR triangle — Train on Synthetic, Test on Real vs Train on Real, Test on Real vs Train on Real, Test on Synthetic. Reports per-metric utility ratio (synth / real), per-marginal KS / Wasserstein distance, pairwise-correlation Frobenius gap, and a downstream-task fidelity verdict (use-as-real / use-with-caveats / reject). Triggers whenever the user has generated tabular synthetic data via SDV / CTGAN / TVAE / Synthpop / Gretel / Mostly AI / private-DP-synth and is about to train or evaluate a model on it. Refuses to certify utility without a held-out REAL…
