优化ai_auto_response回复长度并强化@画像回复

变更项：

1. 收紧回复长度策略：social_short/qa_fast/qa_with_context 全部缩短，减少长句与说明文风格。

2. 强化提示词约束：默认30字内、最多2句且总长不超过55字，禁止大段铺垫。

3. 新增@画像高优先通道：当消息为@或强定向时，构建并注入 at_member_profile_prompt。

4. Dify输入同步注入@画像与 is_at/is_directed 控制字段，保证不同LLM后端行为一致。

plugins/ai_auto_response/context/context_builder.py

@@ -43,6 +43,8 @@ class ContextBuilder:
                 "member_context": member_context or {},
             },
             "speaker_name_clean": self._clean_display_name(sender_name),
+            "is_at": bool(trigger.get("is_at", False)),
+            "is_directed": bool(trigger.get("is_directed", False)),
             "recent_message_items": self._build_recent_message_items(selected_messages),
             "recent_messages": recent_lines,
             "recent_summary": "",
@@ -50,6 +52,12 @@ class ContextBuilder:
             "reply_mode": reply_mode,
             "flow_state": flow_state,
             "memory_prompt": self._build_member_memory_prompt(member_context, member_memory_focus or []),
+            "at_member_profile_prompt": self._build_at_member_profile_prompt(
+                member_context=member_context or {},
+                focus_lines=member_memory_focus or [],
+                is_at=bool(trigger.get("is_at", False)),
+                is_directed=bool(trigger.get("is_directed", False)),
+            ),
             "vector_memory_prompt": self._build_vector_memory_prompt(vector_memories),
             "social_memory_prompt": self._build_social_memory_prompt(social_memory or {}),
             "group_facts_prompt": self._build_group_facts_prompt(group_facts or {}),
@@ -229,6 +237,39 @@ class ContextBuilder:
         ]
         return "\n".join([line for line in lines if line])
 
+    @staticmethod
+    def _build_at_member_profile_prompt(
+        member_context: Dict,
+        focus_lines: List[str] | None = None,
+        is_at: bool = False,
+        is_directed: bool = False,
+    ) -> str:
+        # 只有明确 @ 或强定向时才给“高优先级成员画像”，避免平时过度套人设
+        if not (is_at or is_directed):
+            return ""
+        if not member_context:
+            return "本次是对方点名发起，但暂无稳定画像，按自然群友口吻短回复。"
+
+        meta = member_context.get("meta", {}) or {}
+        summary = str(member_context.get("summary_text", "") or "").strip()
+        interaction_style = str(member_context.get("interaction_style", "") or "").strip()
+        response_hint = str(member_context.get("response_style_hint", "") or "").strip()
+        topics = ContextBuilder._stringify_items(member_context.get("topics_of_interest", []) or [], 4)
+        focus = "；".join((focus_lines or [])[:3]).strip()
+        lines = [
+            "本次为点名互动，优先参考该成员画像后再回复：",
+            f"成员摘要：{summary}" if summary else "",
+            f"互动风格：{interaction_style}" if interaction_style else "",
+            f"偏好回复方式：{response_hint}" if response_hint else "",
+            f"近期相关记忆：{focus}" if focus else "",
+            f"长期兴趣：{topics}" if topics else "",
+            f"禁忌提醒：{ContextBuilder._stringify_items(meta.get('reply_taboos', []), 3)}"
+            if meta.get("reply_taboos")
+            else "",
+            "语气要像熟悉的群友，短句、自然，不要客服腔。",
+        ]
+        return "\n".join([line for line in lines if line])
+
     @staticmethod
     def _stringify_items(items: List | str, limit: int) -> str:
         if isinstance(items, str):