feat(runtime): add planner reflection history with rationale and thinking

- ToolCallDecision captures thinking blocks and pre-tool text output
- AnthropicToolCallingClient supports optional extended thinking (budget_tokens + beta header)
- PlannedStep carries rationale and thinking from each LLM decision
- WorldEvent replaces scene_summary with rationale/thinking/page fields (backward-compatible)
- AI planner system prompt instructs reflection before each tool call
- _history_summary() emits compact {page, rationale, action, success} dicts
- Cloud DB migration 0011 adds nullable rationale/thinking columns to planner_decision_log
- OpenAI client extracts reasoning_content into thinking field

world/models.py

@@ -12,16 +12,24 @@ from world.config import DEFAULT_HISTORY_SIZE
 
 @dataclass(frozen=True)
 class WorldEvent:
-    scene_summary: SemanticScene | Scene
     action: str
     success: bool
+    # Optional for backward compatibility; new entries created by AIPlanner
+    # paths leave this as None and use rationale/thinking instead.
+    scene_summary: SemanticScene | Scene | None = None
+    rationale: str | None = None
+    thinking: str | None = None
+    page: str | None = None
     timestamp: datetime = field(default_factory=utc_now)
 
     def to_dict(self) -> dict[str, Any]:
         return {
-            "scene_summary": self.scene_summary.to_dict(),
+            "scene_summary": self.scene_summary.to_dict() if self.scene_summary is not None else None,
             "action": self.action,
             "success": self.success,
+            "rationale": self.rationale,
+            "thinking": self.thinking,
+            "page": self.page,
             "timestamp": self.timestamp.isoformat(),
         }