chore: create Multica handoff checkpoint

app/backend/features/mentor/service.py

@@ -129,9 +129,10 @@ class MentorServiceMixin:
 
         def generate():
             answer_parts: list[str] = []
+            follow_ups: list[str] = []
             events = self.llm_gateway.stream(
                 "mentor",
-                f"mentor-skill-v1:{skill.skill_id}",
+                f"mentor-skill-v2:{skill.skill_id}",
                 lambda profile: stream_with_mentor(
                     skill,
                     context,
@@ -140,6 +141,7 @@ class MentorServiceMixin:
                     profile.api_key,
                     profile.base_url,
                     profile.model,
+                    follow_ups=follow_ups,
                 ),
                 (MentorAgentError,),
             )
@@ -160,6 +162,7 @@ class MentorServiceMixin:
                     yield {
                         "type": "meta",
                         "data_trade_date": context["data_trade_date"],
+                        "follow_ups": follow_ups or self._mentor_follow_up_fallback(question),
                         "notice": "智能解读已自动切换可用服务。"
                         if event.role == "fallback"
                         else "",
@@ -167,6 +170,27 @@ class MentorServiceMixin:
 
         return generate()
 
+    @staticmethod
+    def _mentor_follow_up_fallback(question: str) -> list[str]:
+        normalized = question.strip()
+        if any(keyword in normalized for keyword in ("风险", "亏损", "回撤", "止损")):
+            return [
+                "这些风险最早会从哪些信号中暴露？",
+                "哪些变化会让当前风险判断失效？",
+                "如果风险继续扩大，仓位预案应如何调整？",
+            ]
+        if any(keyword in normalized for keyword in ("股票", "个股", "代码", "怎么看")):
+            return [
+                "这个判断最关键的确认信号是什么？",
+                "哪些变化会让当前结论失效？",
+                "明日盘中应该优先观察哪些数据？",
+            ]
+        return [
+            "这个判断最关键的确认依据是什么？",
+            "哪些变化会让当前结论失效？",
+            "下一步应该优先观察什么？",
+        ]
+
     def mentor_messages(self, mentor_id: str, trade_date: str) -> list[dict[str, Any]]:
         mentor_id = validate_text(mentor_id, "问师角色", 100, required=True)
         trade_date = normalize_date(trade_date)