fix(learning-harness): the run reads the meter it publishes

The chat client meters itself and nothing passed the meter to the baseline
or the round, so every published cost would have been 0.00 -- and the
round's cost cap, which reads the same meter, could never have fired.

Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG

src/openultrasast/cli.py

@@ -1272,6 +1272,10 @@ def _learning_run(args: argparse.Namespace, cases: Sequence[PairCase], taxonomy:
     if resolved is None:
         print("learning: learning_endpoint_unavailable; scoring what can be scored without a detector")
     client = resolved[0] if resolved else None
+    # The client meters itself; a run that never reads the meter publishes a cost of zero and can never trip its
+    # own cap (Req 8.3, 9.8).
+    meter = getattr(client, "cost_usd", None)
+    spent: Callable[[], float] | None = meter if callable(meter) else None
     configs = load_family_configs(configs_dir, taxonomy)  # type: ignore[arg-type]
 
     def factory(family_config: object) -> Callable[[Path], list[StaticFinding]]:
@@ -1323,7 +1327,9 @@ def _learning_run(args: argparse.Namespace, cases: Sequence[PairCase], taxonomy:
             # `--slice` already chose the rows; without this the baseline's own default filters them out again and
             # a run over the memory-safety slice reports nothing at all (Req 8.4).
             slices=(args.slice,) if args.slice != "all" else DEFAULT_SLICES,
+            spent_usd=spent,
         )
+        print(f"learning baseline cost: ${report.cost_usd:.4f}")
         print(f"learning baseline {model}: {len(report.floors)} families, k={report.k_runs} -> {out / 'baseline'}")
         return 0
     journal = LearningJournal(out / "journal.jsonl")
@@ -1342,11 +1348,12 @@ def _learning_run(args: argparse.Namespace, cases: Sequence[PairCase], taxonomy:
         cost_cap_usd=args.cost_cap_usd or config.learning.round_cost_cap_usd,
         minibatch=config.learning.minibatch,
         k_runs=k_runs,
+        spent_usd=spent,
         # Every other family the corpus actually carries, so a change that reaches beyond its own directory is
         # measured rather than assumed impossible (Req 9.5).
         sweep_families=tuple(sorted({_label(case, taxonomy) for case in cases} & set(configs) - {args.family})),
     )
-    print(f"learning round {record.round} {record.family}: {record.outcome} ({record.reason})")
+    print(f"learning round {record.round} {record.family}: {record.outcome} ({record.reason}) cost ${record.cost_usd:.4f}")
     return 0