feat: send live flow context to AI Assist for full editor awareness

The AI panel now sends the current tree structure (troubleshooting) or
steps + intake form (procedural/maintenance) with each message. This
gives the AI full visibility into node details, questions, descriptions,
options, and intake form fields — not just the node ID.

- Backend: add flow_context param to schema, endpoint, and service
- Frontend: add getFlowContext callback to useEditorAI hook
- TreeEditorPage: passes treeStructure as flow context
- ProceduralEditorPage: passes steps + intakeForm as flow context

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

backend/app/api/endpoints/ai_chat.py

@@ -172,6 +172,7 @@ async def post_message(
             session, data.content, db,
             action_type=data.action_type or "open_chat",
             focal_node_id=data.focal_node_id,
+            flow_context=data.flow_context,
         )
     except Exception as e:
         logger.exception("AI chat message failed: %s", e)

backend/app/core/ai_chat_service.py

@@ -533,13 +533,33 @@ async def send_message(
     db: AsyncSession,
     action_type: str = "open_chat",
     focal_node_id: str | None = None,
+    flow_context: dict | None = None,
 ) -> tuple[str, Optional[dict], Optional[str], Optional[dict]]:
     """Send a user message and get AI response.
 
+    Args:
+        flow_context: Live flow structure from the editor. Contains the current
+            tree_structure (troubleshooting) or steps + intake_form (procedural).
+            This gives the AI full awareness of the flow being edited.
+
     Returns (ai_content, working_tree_update, new_phase, metadata_update).
     """
     system_prompt = _build_system_prompt(session.flow_type)
 
+    # Inject live flow context so the AI can see current editor state
+    if flow_context:
+        context_json = json.dumps(flow_context, indent=2)
+        system_prompt += (
+            f"\n\nCURRENT FLOW STATE (live from editor):\n{context_json}"
+        )
+        if focal_node_id:
+            focal_node = _find_node_by_id(flow_context, focal_node_id)
+            if focal_node:
+                system_prompt += (
+                    f"\n\nFOCAL NODE/STEP (the item being acted on):\n"
+                    f"{json.dumps(focal_node, indent=2)}"
+                )
+
     # Build messages array from conversation history
     now_iso = datetime.now(timezone.utc).isoformat()
     history = list(session.conversation_history)

backend/app/schemas/ai_chat.py

@@ -43,6 +43,10 @@ class AIChatMessageRequest(BaseModel):
         default=None,
         description="ID of the node/step being acted on",
     )
+    flow_context: Optional[dict[str, Any]] = Field(
+        default=None,
+        description="Live flow structure from the editor (tree structure, steps, intake form)",
+    )
 
 
 class AIChatImportRequest(BaseModel):