refactor(protocol): swap S-expression grammar for strict JSON Schema

Sostituisce la grammatica S-expression con uno schema JSON stretto. La
grammatica S-expression falliva il parsing nel 64% delle generazioni del
modello Qwen3-235B sul run reale; JSON e' nativo per gli LLM moderni e
si parsa con json.loads.

Cambiamenti principali:
- grammar.py: costanti rinominate LOGICAL_OPS / COMPARATOR_OPS /
  CROSSOVER_OPS / ACTION_VALUES / KIND_VALUES.
- parser.py: nuovo AST a dataclass tipizzato (OpNode, IndicatorNode,
  FeatureNode, LiteralNode, Rule, Strategy); parse_strategy ora consuma
  JSON tramite json.loads.
- validator.py: walk dispatchato per tipo (isinstance) invece di
  pattern-matching su 'kind'; arity check su operatori e indicator.
- compiler.py: traversal del nuovo AST tipizzato, dispatch per
  isinstance; logica indicator/feature/literal invariata.
- hypothesis.py: prompt SYSTEM riscritto con esempi JSON e vincoli
  espliciti su no-nesting; estrazione via fence ```json``` + fallback
  brace-balanced.
- __init__.py: re-export pubblico delle entita' del protocollo.
- Tutti i test (parser, validator, compiler, hypothesis_agent,
  falsification, adversarial, e2e, smoke_run) migrati a JSON.
- Rimossa dipendenza sexpdata da pyproject.toml + uv.lock.

Test: 135 passed (era 122; aggiunti casi parser/validator).
ruff + mypy strict clean. Smoke run end-to-end OK.

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

scripts/smoke_run.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import json
 from pathlib import Path
 
 import numpy as np
@@ -9,19 +10,40 @@ from multi_swarm.genome.hypothesis import HypothesisAgentGenome, ModelTier
 from multi_swarm.llm.client import CompletionResult
 from multi_swarm.orchestrator.run import RunConfig, run_phase1
 
+_MOCK_STRATEGY = json.dumps(
+    {
+        "rules": [
+            {
+                "condition": {
+                    "op": "gt",
+                    "args": [
+                        {"kind": "indicator", "name": "rsi", "params": [14]},
+                        {"kind": "literal", "value": 70.0},
+                    ],
+                },
+                "action": "entry-short",
+            },
+            {
+                "condition": {
+                    "op": "lt",
+                    "args": [
+                        {"kind": "indicator", "name": "rsi", "params": [14]},
+                        {"kind": "literal", "value": 30.0},
+                    ],
+                },
+                "action": "entry-long",
+            },
+        ]
+    }
+)
+
 
 class MockLLMClient:
     def complete(
         self, genome: HypothesisAgentGenome, system: str, user: str,
         max_tokens: int = 2000,
     ) -> CompletionResult:
-        text = (
-            "```lisp\n"
-            "(strategy"
-            " (when (gt (indicator rsi 14) 70.0) (entry-short))"
-            " (when (lt (indicator rsi 14) 30.0) (entry-long)))\n"
-            "```"
-        )
+        text = "```json\n" + _MOCK_STRATEGY + "\n```"
         return CompletionResult(
             text=text, input_tokens=120, output_tokens=60,
             tier=genome.model_tier, model="mock",