Round 3, iteration 1 of the fold optimization loop
(docs/research/optimization-loop-2026-07-30.md).
The foundation audit found gold scoring machinery (26 oracle files in
bench/gold/, fold_eval/scoring.py, gold_threshold_failures gates)
fully implemented but wired into zero project manifests — the eval
measured finding drift, never precision/recall.
New gold standards anchored on the reviewed dispositions:
- bench/gold/fold_self_gold.json: 9 cases (5 SafetyObserver stub
clones, 1 detector-internal clone, 1 loop_inventory clone, 2
sql-injection sites reviewed false-positive-but-intentionally-
reported)
- bench/gold/yams_self_gold.json: 7 cases (3 clone, 4 high-complexity)
Both manifests now enforce gold_thresholds precision 1.0 / recall 1.0:
any detector drift that loses a reviewed finding (recall drop) or
emits a new unmatched finding (precision drop) fails the evaluation.
Proof runs: fold TP=9/FP=0/FN=0, yams TP=7/FP=0/FN=0, precision 1.0,
recall 1.0, fingerprints exactly preserved (0fec78e5.../247523c5...),
full suite 137/137. Gold files live in bench/gold/ alongside the
existing oracles (the tests/benchmarks schema-test glob correctly does
not sweep that directory).
Add negative_cases_from_universe to expand an explicit file-by-rule universe
into labeled negatives (enabling TP/FP/TN/FN, not just TP/FP), plus project-eval
harness updates in run_project_eval and the score/score_fp/quality-gate helpers.
