feat(phase-2.5): Task 6 cost_kind attribution + fees_eat_alpha threshold CLI

Task 6 del piano Phase 2.5 (deferito → ora completato):
- CostRecord: nuovo campo call_kind (default "hypothesis")
- CostTracker.record: accetta call_kind opzionale, summary include
  by_call_kind breakdown (hypothesis vs mutation)
- Schema cost_records: aggiunta colonna call_kind TEXT NOT NULL DEFAULT
  'hypothesis' + migration soft via ALTER TABLE in init_schema (silently
  catched per DB pre-Task 6)
- Repository.save_cost_record: nuova arg call_kind opzionale
- mutate_prompt_llm: accetta cost_tracker/repo/run_id opzionali e logga
  la call mutator con call_kind="mutation" quando sink presente
- weighted_random_mutate, next_generation: propagano cost sink
- orchestrator.run_phase1: passa cost_tracker+repo+run_id a
  next_generation solo se prompt_mutation_weight > 0

Esposto fees_eat_alpha_threshold come parametro AdversarialAgent
(default 0.5 = comportamento Phase 1.5 invariato), propagato via
RunConfig.fees_eat_alpha_threshold e flag CLI
--fees-eat-alpha-threshold. Abilita ablation con soglia 0.7-0.8 senza
modificare codice — adversarial finding dominante in tutti i run
Phase 2/2.5 (50+ HIGH per run).

Tests (+4 → 186 totale):
- test_cost_tracker: default call_kind="hypothesis"; breakdown
  by_call_kind con hypothesis+mutation
- test_mutation_prompt_llm: logging mutation cost con sink completo;
  backward compat senza sink (no errore)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

tests/unit/test_cost_tracker.py

@@ -61,3 +61,28 @@ def test_tracker_summary_contains_all_five_tiers():
     for tier_letter in ("S", "A", "B", "C", "D"):
         assert tier_letter in summary["by_tier"]
         assert summary["by_tier"][tier_letter]["calls"] == 1
+
+
+def test_tracker_default_call_kind_is_hypothesis():
+    t = CostTracker()
+    rec = t.record(input_tokens=10, output_tokens=10, tier=ModelTier.C, run_id="r", agent_id="a")
+    assert rec.call_kind == "hypothesis"
+    summary = t.summary()
+    assert "hypothesis" in summary["by_call_kind"]
+    assert summary["by_call_kind"]["hypothesis"]["calls"] == 1
+    assert "mutation" not in summary["by_call_kind"]
+
+
+def test_tracker_by_call_kind_breakdown():
+    t = CostTracker()
+    t.record(input_tokens=100, output_tokens=200, tier=ModelTier.C, run_id="r", agent_id="a")
+    t.record(input_tokens=100, output_tokens=200, tier=ModelTier.C, run_id="r", agent_id="a")
+    t.record(
+        input_tokens=50, output_tokens=80, tier=ModelTier.B,
+        run_id="r", agent_id="parent-x", call_kind="mutation",
+    )
+    summary = t.summary()
+    assert summary["by_call_kind"]["hypothesis"]["calls"] == 2
+    assert summary["by_call_kind"]["mutation"]["calls"] == 1
+    assert summary["by_call_kind"]["mutation"]["input_tokens"] == 50
+    assert summary["by_call_kind"]["mutation"]["output_tokens"] == 80

tests/unit/test_mutation_prompt_llm.py

@@ -161,6 +161,69 @@ def test_mutate_prompt_llm_falls_back_on_llm_exception() -> None:
     assert child.generation == parent.generation + 1
 
 
+def test_mutate_prompt_llm_logs_mutation_cost_when_sink_provided() -> None:
+    """Quando cost_tracker+repo+run_id sono forniti, la call mutator viene loggata
+    con call_kind='mutation' sia in memoria sia nel repo."""
+    mutated = (
+        "Strategia RSI 1h evolved. Entry long quando RSI(14) < 28 e close > "
+        "SMA(50). Exit short quando RSI(14) > 72."
+    )
+
+    class _R:
+        text = f"<prompt>{mutated}</prompt>"
+        input_tokens = 350
+        output_tokens = 140
+
+    class _FakeLLMCosted:
+        def complete(self, genome, system, user, max_tokens=2000):
+            return _R()
+
+    tracker_calls = []
+    repo_calls = []
+
+    class _FakeTracker:
+        def record(self, **kw):
+            tracker_calls.append(kw)
+            from types import SimpleNamespace
+            return SimpleNamespace(cost_usd=0.0042)
+
+    class _FakeRepo:
+        def save_cost_record(self, **kw):
+            repo_calls.append(kw)
+
+    parent = _make_genome()
+    child = mutate_prompt_llm(
+        parent, _FakeLLMCosted(), random.Random(0),
+        cost_tracker=_FakeTracker(), repo=_FakeRepo(), run_id="run-xyz",
+    )
+    assert child.system_prompt == mutated
+    assert len(tracker_calls) == 1
+    assert tracker_calls[0]["call_kind"] == "mutation"
+    assert tracker_calls[0]["tier"] == ModelTier.B
+    assert tracker_calls[0]["run_id"] == "run-xyz"
+    assert tracker_calls[0]["agent_id"] == parent.id
+    assert tracker_calls[0]["input_tokens"] == 350
+    assert tracker_calls[0]["output_tokens"] == 140
+
+    assert len(repo_calls) == 1
+    assert repo_calls[0]["call_kind"] == "mutation"
+    assert repo_calls[0]["tier"] == "B"
+    assert repo_calls[0]["cost_usd"] == 0.0042
+
+
+def test_mutate_prompt_llm_no_logging_without_sink() -> None:
+    """Senza cost_tracker+repo+run_id → niente logging cost (backward compat)."""
+    mutated = (
+        "Strategia RSI 1h evoluta. Entry long quando RSI(14) < 25 e close > "
+        "SMA(60). Exit short quando RSI(14) > 75 e ATR rising."
+    )
+    llm = _FakeLLM(response_text=f"<prompt>{mutated}</prompt>")
+    parent = _make_genome()
+    # Non solleva (anche se 0 sink forniti)
+    child = mutate_prompt_llm(parent, llm, random.Random(0))
+    assert child.system_prompt == mutated
+
+
 def test_mutate_prompt_llm_picks_one_of_six_instructions() -> None:
     """Verifica che il system message dell'LLM includa una delle 6 istruzioni."""
     mutated = (