Add Monte Carlo simulator, game metrics and sim CLI (Phase 5)

`dojo sim` plays seeded games over a scenario matrix (variant, players,
Kiai bonus, start position, bot lineup) in parallel, prints a summary per
scenario and optionally writes one CSV row per game. Metrics are replayed
from the event log. Plan updated with the Phase 5 baseline.

Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>

tests/test_cli.py

@@ -56,3 +56,28 @@ def test_legend_next_to_the_quadrant_is_used_by_default(
 
     assert main(["board", "validate", "--quadrant", str(quadrant)]) == EXIT_FORMAT_ERRORS
     assert "legend links tunnel '9'" in capsys.readouterr().err
+
+
+def test_sim_prints_a_summary_per_scenario_and_writes_games(
+    tmp_path: Path, capsys: pytest.CaptureFixture[str]
+) -> None:
+    games = tmp_path / "games.csv"
+    argv = ["sim", "--games", "2", "--variant", "A", "B", "--players", "3", "--jobs", "1"]
+
+    assert main([*argv, "--csv", str(games)]) == EXIT_OK
+
+    output = capsys.readouterr().out
+    assert "== A p3 kiai+2 start0 balanced,farmer,aggressive  (2 games" in output
+    assert "== B p3 kiai+2 start0" in output
+    rows = games.read_text(encoding="utf-8").splitlines()
+    assert rows[0].startswith("scenario,seed,lineup,winner_seat")
+    assert len(rows) == 1 + 4
+
+
+@pytest.mark.parametrize("bad", [["--lineup", "balanced,cheater"], ["--games", "0"]])
+def test_sim_rejects_bad_arguments(bad: list[str], capsys: pytest.CaptureFixture[str]) -> None:
+    with pytest.raises(SystemExit) as exit_info:
+        main(["sim", *bad])
+
+    assert exit_info.value.code == 2
+    assert "error:" in capsys.readouterr().err