feat(phase-2.5): mutate_prompt_llm operator + weighted dispatcher + GA wiring

Implementazione completa Phase 2.5 (LLM prompt mutator) seguendo il piano in
docs/superpowers/plans/2026-05-11-mutate-prompt-llm-phase-2-5.md.

Nuovo modulo src/multi_swarm/genome/mutation_prompt_llm.py:
- 6 mutation instructions (tighten_threshold, swap_comparator, add_condition,
  remove_condition, change_timeframe, add_temporal_gate)
- mutate_prompt_llm(g, llm, rng, mutator_tier=ModelTier.B): clona genome con
  tier B per la call mutator, costruisce system+user prompt con istruzione
  scelta random, estrae prompt da tag <prompt>...</prompt>, valida
- is_valid_prompt(): 3 check (lunghezza >= 50, keyword tecnica, diff > 5%
  Levenshtein-like via difflib.SequenceMatcher)
- Fallback random_mutate su qualsiasi validation fail O LLM exception

Esteso src/multi_swarm/genome/mutation.py con weighted_random_mutate dispatcher:
con probabilità prompt_mutation_weight invoca mutate_prompt_llm, altrimenti
random_mutate. Backward compat: llm=None oppure weight=0 → solo scalare.

Integrazione GA loop + RunConfig:
- GAConfig.prompt_mutation_weight: float = 0.0 (default off)
- next_generation(llm=...) propagato all'invocazione mutator
- RunConfig.prompt_mutation_weight con stesso default
- run_phase1: passa llm a next_generation solo se weight > 0
- scripts/run_phase1.py: flag CLI --prompt-mutation-weight

Tests (+18, 175 totale):
- tests/unit/test_mutation_prompt_llm.py (12): extract_prompt, is_valid_prompt
  3 check, operator success + fallback su 3 modi (invalid/identical/exception),
  tier B per LLM call, istruzione scelta dal pool
- tests/unit/test_mutation_dispatcher.py (4): weight 0/1/None + distribuzione
  30/70 su 1000 estrazioni con tolleranza ±5%
- tests/integration/test_ga_loop_with_prompt_mutator.py (2): loop con
  weight=1.0 produce prompt evoluti; backward compat weight=0 invariato

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

scripts/run_phase1.py

@@ -31,6 +31,12 @@ def parse_args() -> argparse.Namespace:
     p.add_argument("--end", default="2026-01-01T00:00:00+00:00")
     p.add_argument("--fees-bp", type=float, default=5.0)
     p.add_argument("--n-trials-dsr", type=int, default=50)
+    p.add_argument(
+        "--prompt-mutation-weight",
+        type=float,
+        default=0.0,
+        help="Phase 2.5: probabilità (0-1) che la mutazione invochi LLM mutator tier B",
+    )
     return p.parse_args()
 
 
@@ -84,6 +90,7 @@ def main() -> None:
         fees_bp=args.fees_bp,
         n_trials_dsr=args.n_trials_dsr,
         db_path=settings.db_path,
+        prompt_mutation_weight=args.prompt_mutation_weight,
     )
 
     run_id = run_phase1(cfg, ohlcv=ohlcv, llm=llm)