Drop variant B, adopt Black-belt Exam defender, add one-sidedness metrics

- Remove variant B (Brown cap, +1 for higher beating lower) from rules,
  engine, bots and simulator; a higher belt beating a lower one gains 0.
- Final Exam: the defender fights as a Black belt (RULES.md v0.7). Ties to
  the defender and best-of-3 stay as simulator switches (`--exam`).
- Report stripe income per source as gains and losses.
- Add ten one-sidedness measures sampled at turn ends (lead gap, winner
  margin and lead share, halfway leader, last lead change, contention,
  rank swaps, leader Kumite losses, Exam challengers, winner pace).
- Plan: decisions D28-D33 and the detailed Phase 6.

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

tests/test_bots.py

@@ -14,10 +14,11 @@ from dojo.bots import (
     HeuristicAgent,
     Profile,
     RandomAgent,
+    series_probability,
     win_probability,
 )
 from dojo.engine import Agent, FightView, Game, RandomSource
-from dojo.rules import VARIANT_A, VARIANT_B, Card, RulesConfig
+from dojo.rules import DEFAULT_RULES, Card, RulesConfig
 
 ALLENAMENTO = Pos(0, 5)
 FATICA = Pos(3, 6)
@@ -30,6 +31,22 @@ def test_win_probability_counts_senshu_and_bonuses() -> None:
     assert win_probability(0, 0) == pytest.approx(21 / 36)
     assert win_probability(2, 0) == pytest.approx(30 / 36)
     assert win_probability(0, 2) == pytest.approx(10 / 36)
+    assert win_probability(0, 0, senshu=False) == pytest.approx(15 / 36)
+
+
+def test_series_probability_is_a_best_of_n() -> None:
+    assert series_probability(0.3, 1) == pytest.approx(0.3)
+    assert series_probability(0.5, 3) == pytest.approx(0.5)
+    assert series_probability(0.6, 3) == pytest.approx(0.6**2 * (3 - 2 * 0.6))
+
+
+def test_kiai_that_only_ties_the_exam_is_kept_when_ties_go_to_the_defender() -> None:
+    game, _, _ = make_game(config=RulesConfig(exam_ties_to_defender=True))
+    game.players[0].tecnica = Card.KIAI
+    exam = FightView(0, 1, True, 3, 5, played=())
+
+    assert not HeuristicAgent().play_tecnica(game.view(0), exam)
+    assert HeuristicAgent().play_tecnica(game.view(0), fight(3, 5))
 
 
 def test_heuristic_prefers_allenamento_to_fatica() -> None:
@@ -100,7 +117,13 @@ def play(board: Board, config: RulesConfig, seed: int) -> Game:
     return game
 
 
-@pytest.mark.parametrize("config", [VARIANT_A, VARIANT_B])
+@pytest.mark.parametrize(
+    "config",
+    [
+        DEFAULT_RULES,
+        RulesConfig(exam_ties_to_defender=True, exam_defender_black=True, exam_rounds=3),
+    ],
+)
 def test_bots_play_full_games_reproducibly(board: Board, config: RulesConfig) -> None:
     first, again = play(board, config, seed=7), play(board, config, seed=7)