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

runtime/ai_planner.py

@@ -60,6 +60,8 @@ class AIPlanner(Planner):
                 description=f"AI planner: {decision.tool_name}({decision.arguments})",
                 args=dict(decision.arguments),
                 prompt=decision.user_prompt or user_prompt,
+                rationale=decision.text_output,
+                thinking=decision.thinking,
             )
         ]
 
@@ -72,4 +74,12 @@ class AIPlanner(Planner):
 def _history_summary(world: "WorldState | None") -> list[dict[str, Any]]:
     if world is None:
         return []
-    return [event.to_dict() for event in world.history]
+    return [
+        {
+            "page": event.page,
+            "action": event.action,
+            "rationale": event.rationale,
+            "success": event.success,
+        }
+        for event in world.history
+    ]