diff --git a/src/chat/heart_flow/heartFC_chat.py b/src/chat/heart_flow/heartFC_chat.py
index a7d37e77..707c44bd 100644
--- a/src/chat/heart_flow/heartFC_chat.py
+++ b/src/chat/heart_flow/heartFC_chat.py
@@ -332,7 +332,8 @@ class HeartFChatting:
             self.questioned = False
             # 重置连续 no_reply 计数
             self.consecutive_no_reply_count = 0
-            reason = "有人提到了你，进行回复"
+            reason = ""
+            
 
             await database_api.store_action_info(
                 chat_stream=self.chat_stream,
diff --git a/src/chat/replyer/group_generator.py b/src/chat/replyer/group_generator.py
index e98cf8a7..3019ca0d 100644
--- a/src/chat/replyer/group_generator.py
+++ b/src/chat/replyer/group_generator.py
@@ -56,7 +56,6 @@ class DefaultReplyer:
         self.chat_stream = chat_stream
         self.is_group_chat, self.chat_target_info = get_chat_type_and_target_info(self.chat_stream.stream_id)
         self.heart_fc_sender = UniversalMessageSender()
-        # self.memory_activator = MemoryActivator()
 
         from src.plugin_system.core.tool_use import ToolExecutor  # 延迟导入ToolExecutor，不然会循环依赖
 
@@ -848,7 +847,7 @@ class DefaultReplyer:
 
         # 从 chosen_actions 中提取 planner 的整体思考理由
         planner_reasoning = ""
-        if reply_reason:
+        if global_config.chat.include_planner_reasoning and reply_reason:
             # 如果没有 chosen_actions，使用 reply_reason 作为备选
             planner_reasoning = f"你的想法是：{reply_reason}"
 
diff --git a/src/chat/replyer/private_generator.py b/src/chat/replyer/private_generator.py
index d8438308..76eedf8c 100644
--- a/src/chat/replyer/private_generator.py
+++ b/src/chat/replyer/private_generator.py
@@ -768,7 +768,7 @@ class PrivateReplyer:
 
         # 从 chosen_actions 中提取 planner 的整体思考理由
         planner_reasoning = ""
-        if reply_reason:
+        if global_config.chat.include_planner_reasoning and reply_reason:
             # 如果没有 chosen_actions，使用 reply_reason 作为备选
             planner_reasoning = f"你的想法是：{reply_reason}"
 
diff --git a/src/config/official_configs.py b/src/config/official_configs.py
index abbd73d2..795b38cb 100644
--- a/src/config/official_configs.py
+++ b/src/config/official_configs.py
@@ -117,6 +117,9 @@ class ChatConfig(ConfigBase):
     时间区间支持跨夜，例如 "23:00-02:00"。
     """
 
+    include_planner_reasoning: bool = False
+    """是否将planner推理加入replyer，默认关闭（不加入）"""
+
     def _parse_stream_config_to_chat_id(self, stream_config_str: str) -> Optional[str]:
         """与 ChatStream.get_stream_id 一致地从 "platform:id:type" 生成 chat_id。"""
         try:
diff --git a/src/express/expression_selector.py b/src/express/expression_selector.py
index 32bee81e..031cc714 100644
--- a/src/express/expression_selector.py
+++ b/src/express/expression_selector.py
@@ -16,11 +16,10 @@ logger = get_logger("expression_selector")
 
 
 def init_prompt():
-    expression_evaluation_prompt = """
-以下是正在进行的聊天内容：
-{chat_observe_info}
+    expression_evaluation_prompt = """{chat_observe_info}
 
 你的名字是{bot_name}{target_message}
+{reply_reason_block}
 
 以下是可选的表达情境：
 {all_situations}
@@ -31,7 +30,6 @@ def init_prompt():
 2.话题类型（日常、技术、游戏、情感等）
 3.情境与当前语境的匹配度
 {target_message_extra_block}
-{reply_reason_block}
 
 请以JSON格式输出，只需要输出选中的情境编号：
 例如：
@@ -234,22 +232,25 @@ class ExpressionSelector:
             all_situations_str = "\n".join(all_situations)
 
             if target_message:
-                target_message_str = f"，现在你想要对上面的这条消息进行恢复：“{target_message}”"
+                target_message_str = f"，现在你想要对这条消息进行回复：“{target_message}”"
                 target_message_extra_block = "4.考虑你要回复的目标消息"
             else:
                 target_message_str = ""
                 target_message_extra_block = ""
-
+                
+            chat_context = f"以下是正在进行的聊天内容：{chat_info}"
+    
             # 构建reply_reason块
             if reply_reason:
-                reply_reason_block = f"5.考虑你的回复理由：{reply_reason}"
+                reply_reason_block = f"你的回复理由是：{reply_reason}"
+                chat_context = ""
             else:
                 reply_reason_block = ""
 
             # 3. 构建prompt（只包含情境，不包含完整的表达方式）
             prompt = (await global_prompt_manager.get_prompt_async("expression_evaluation_prompt")).format(
                 bot_name=global_config.bot.nickname,
-                chat_observe_info=chat_info,
+                chat_observe_info=chat_context,
                 all_situations=all_situations_str,
                 max_num=max_num,
                 target_message=target_message_str,
@@ -261,7 +262,7 @@ class ExpressionSelector:
             content, (reasoning_content, model_name, _) = await self.llm_model.generate_response_async(prompt=prompt)
 
             
-            print(prompt)
+            # print(prompt)
             
             if not content:
                 logger.warning("LLM返回空结果")
diff --git a/template/bot_config_template.toml b/template/bot_config_template.toml
index 45d97c30..cc540e6a 100644
--- a/template/bot_config_template.toml
+++ b/template/bot_config_template.toml
@@ -1,5 +1,5 @@
 [inner]
-version = "6.21.3"
+version = "6.21.4"
 
 #----以下是给开发人员阅读的，如果你只是部署了麦麦，不需要阅读----
 #如果你想要修改配置文件，请递增version的值
@@ -101,6 +101,8 @@ talk_value_rules = [
     { target = "qq:114514:private", time = "00:00-23:59", value = 0.3 },
 ]
 
+include_planner_reasoning = false # 是否将planner推理加入replyer，默认关闭（不加入）
+
 [memory]
 max_agent_iterations = 5 # 记忆思考深度（最低为1（不深入思考））