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>

src/multi_swarm/genome/mutation_prompt_llm.py

@@ -130,6 +130,9 @@ def mutate_prompt_llm(
     rng: random.Random,
     mutator_tier: ModelTier = ModelTier.B,
     max_tokens: int = 2000,
+    cost_tracker: Any | None = None,
+    repo: Any | None = None,
+    run_id: str | None = None,
 ) -> HypothesisAgentGenome:
     """Operatore di mutazione prompt-level via LLM mutator.
 
@@ -137,6 +140,9 @@ def mutate_prompt_llm(
     LLM tier B per ottenere il prompt mutato, valida l'output. Su validation
     fail (output troppo corto, non-strategia, troppo simile al parent),
     fallback silenzioso a ``random_mutate``.
+
+    Se ``cost_tracker``, ``repo`` e ``run_id`` sono forniti, la chiamata mutator
+    viene registrata con ``call_kind="mutation"`` per audit budget.
     """
     instruction_key = rng.choice(list(MUTATION_INSTRUCTIONS))
     instruction = MUTATION_INSTRUCTIONS[instruction_key]
@@ -160,6 +166,28 @@ def mutate_prompt_llm(
     except Exception:
         return random_mutate(g, rng)
 
+    # Cost tracking call_kind="mutation" se sink fornito.
+    if cost_tracker is not None and repo is not None and run_id is not None:
+        in_tok = getattr(result, "input_tokens", 0)
+        out_tok = getattr(result, "output_tokens", 0)
+        cr = cost_tracker.record(
+            input_tokens=in_tok,
+            output_tokens=out_tok,
+            tier=mutator_tier,
+            run_id=run_id,
+            agent_id=g.id,
+            call_kind="mutation",
+        )
+        repo.save_cost_record(
+            run_id=run_id,
+            agent_id=g.id,
+            tier=mutator_tier.value,
+            input_tokens=in_tok,
+            output_tokens=out_tok,
+            cost_usd=cr.cost_usd,
+            call_kind="mutation",
+        )
+
     new_prompt = _extract_prompt(getattr(result, "text", ""))
     if not is_valid_prompt(new_prompt, g.system_prompt):
         return random_mutate(g, rng)