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

tests/test_ai_planner.py

@@ -195,3 +195,62 @@ def test_ai_planner_step_prompt_reflects_scene_changes() -> None:
     assert steps_a[0].prompt != steps_b[0].prompt
     assert "Alpha" in steps_a[0].prompt
     assert "Beta" in steps_b[0].prompt
+
+
+def test_ai_planner_propagates_rationale_and_thinking_to_planned_step() -> None:
+    client = FakeToolCallingClient(
+        ToolCallDecision(
+            tool_name="tap",
+            arguments={"x": 1, "y": 2},
+            text_output="Previous step opened settings. Now tapping account.",
+            thinking="I need to navigate deeper.",
+        )
+    )
+    planner = AIPlanner(client=client)
+
+    steps = planner.plan(goal="open account", scene=_scene(), context=_context())
+
+    assert steps[0].rationale == "Previous step opened settings. Now tapping account."
+    assert steps[0].thinking == "I need to navigate deeper."
+
+
+def test_history_summary_returns_compact_format() -> None:
+    from collections import deque
+    from runtime.ai_planner import _history_summary
+    from world.models import WorldEvent, WorldState
+
+    state = WorldState(
+        history=deque(
+            [
+                WorldEvent(
+                    action="tap",
+                    success=True,
+                    rationale="Opened settings.",
+                    page="Home",
+                ),
+                WorldEvent(
+                    action="swipe",
+                    success=False,
+                    rationale=None,
+                    page="Settings",
+                ),
+            ]
+        )
+    )
+
+    summary = _history_summary(state)
+
+    assert summary == [
+        {"page": "Home", "action": "tap", "rationale": "Opened settings.", "success": True},
+        {"page": "Settings", "action": "swipe", "rationale": None, "success": False},
+    ]
+    # Must not contain scene element data
+    for entry in summary:
+        assert "scene_summary" not in entry
+        assert "elements" not in entry
+
+
+def test_history_summary_returns_empty_for_none_world() -> None:
+    from runtime.ai_planner import _history_summary
+
+    assert _history_summary(None) == []