fix(learning-harness): the round-4 review findings

Three defects, two of them the same shape as ones already rejected once:

- The meta-agent proposer still could not propose. `MetaAgent(inner_model=)`
  takes a ModelConfig; it was handed a model name, a `# type: ignore` hid
  that from mypy, and a bare `except Exception` turned the resulting
  AttributeError into `meta_agent_failed` -- which reads exactly like the
  model declining. The composition is now a seam a test can pin, and a
  construction error is re-raised rather than reported as a quiet round.
- `ousast pairs --hunter` crashed in its documented form: the K floor landed
  with `--k-runs` still defaulting to 1. The covering test always passed
  `--k-runs 4`, which is why nothing noticed.
- 28 rows (12% of the corpus) resolved a span on the vulnerable side and
  none on the fixed side, so every fixed-side finding read as outside the
  labeled function and the pair scored as silence whatever the detector
  said. `fix_function` now reaches the catalog and the scorer, and the
  generator derives it from the fixed excerpt for the 25 trap rows that
  never declared one. Measured after: 0 rows.

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

src/openultrasast/cli.py

@@ -189,7 +189,9 @@ def main(argv: list[str] | None = None) -> int:
     )
     pairs.add_argument("--loo-out", type=Path, default=None, help="where to write loo.json (default: reports/loo.json)")
     pairs.add_argument("--json", action="store_true", help="print the pair scoreboard as JSON")
-    pairs.add_argument("--k-runs", type=int, default=1, help="runs per pair on the hunter path; the family scorer needs at least three")
+    pairs.add_argument(
+        "--k-runs", type=int, default=None, help="runs per pair on the hunter path; never fewer than three, and three by default"
+    )
 
     subparsers.add_parser("mcp", help="run the narrow MCP server over stdio for OpenCode integration")
     mechanisms = subparsers.add_parser("mechanisms", help="maintainer: mechanism memory seeded from trusted pairs")
@@ -982,7 +984,10 @@ def _pairs(
             from .learning.families import load_families
 
             scan = make_hunter_scan(client, model, taxonomy=load_families())
-    result = evaluate_catalog(cases, hunter=scan, pointers=True if pointers else None, k_runs=k_runs)
+    try:
+        result = evaluate_catalog(cases, hunter=scan, pointers=True if pointers else None, k_runs=k_runs)
+    except ValueError as exc:
+        raise SystemExit(f"--k-runs: {exc}") from exc
     if json_out:
         print(json.dumps(result_payload(result), indent=2, sort_keys=True))
         return 0