diff --git a/src/chat/focus_chat/info_processors/relationship_processor.py b/src/chat/focus_chat/info_processors/relationship_processor.py
index 3fa662ee0..8db062493 100644
--- a/src/chat/focus_chat/info_processors/relationship_processor.py
+++ b/src/chat/focus_chat/info_processors/relationship_processor.py
@@ -26,6 +26,7 @@ from src.chat.utils.chat_message_builder import (
 )
 import os
 import pickle
+import random
 
 
 # 消息段清理配置
@@ -36,9 +37,55 @@ SEGMENT_CLEANUP_CONFIG = {
     "cleanup_interval_hours": 1,  # 清理间隔（小时）
 }
 
+# 用于随机生成prompt示例的资源池
+USER_EXAMPLE_KEYS = ["用户A", "小明", "Alice", "陈皮", "老王", "Bob", "张三", "李四"]
+USER_EXAMPLE_VALUES = [
+    "ta的昵称", "ta对你的态度", "你对ta的印象", "ta最近心情如何", 
+    "你们的关系", "ta的身份", "ta的兴趣爱好", "ta和你的共同点", "ta的习惯","你们最近做的事","你对ta的语气","你们的互动方式","给你的第一印象","你们最近聊过什么"
+]
+BOT_EXAMPLE_VALUES = ["身份", "性格", "你的原则", "你的知识", "你的目标", "你的爱好", "你最近在做什么","头像","年龄","性别","职业","兴趣爱好","习惯","目标","原则","知识","爱好"]
+
+
 logger = get_logger("processor")
 
 
+def _generate_random_prompt_example() -> str:
+    """动态生成一个随机的、符合规则的JSON示例字符串"""
+    
+    bot_nickname = global_config.bot.nickname
+    bot_aliases = list(global_config.bot.alias_names)
+    
+    # 确定示例数量
+    num_user_examples = random.randint(1, 2)
+    num_bot_examples = random.randint(1, 2)
+
+    example_dict = {}
+
+    # 1. 生成用户提取示例
+    user_keys = random.sample(USER_EXAMPLE_KEYS, min(num_user_examples, len(USER_EXAMPLE_KEYS)))
+    user_values = random.sample(USER_EXAMPLE_VALUES, min(num_user_examples, len(USER_EXAMPLE_VALUES)))
+    for i in range(len(user_keys)):
+        example_dict[user_keys[i]] = user_values[i]
+
+    # 2. 生成bot自身示例 (使用昵称和别名避免key重复)
+    bot_name_pool = [bot_nickname] + bot_aliases
+    random.shuffle(bot_name_pool)
+    bot_values = random.sample(BOT_EXAMPLE_VALUES, min(num_bot_examples, len(BOT_EXAMPLE_VALUES)))
+    
+    for i in range(min(num_bot_examples, len(bot_name_pool), len(bot_values))):
+        example_dict[bot_name_pool[i]] = bot_values[i]
+
+    # 3. 添加固定示例
+    example_dict["person_name"] = "其他信息"
+
+    # 随机化顺序并格式化为JSON字符串
+    items = list(example_dict.items())
+    random.shuffle(items)
+    shuffled_dict = dict(items)
+    
+    return json.dumps(shuffled_dict, ensure_ascii=False, indent=4)
+
+
 def init_prompt():
     relationship_prompt = """
 <聊天记录>
@@ -57,13 +104,7 @@ def init_prompt():
 
 请以json格式输出，例如：
 
-{{
-    "用户A": "ta的昵称",
-    "用户B": "ta对你的态度",
-    "用户D": "你对ta的印象",
-    "{bot_name}": "身份",
-    "person_name": "其他信息",
-}}
+{example_json}
 
 请严格按照json输出格式，不要输出多余内容，可以同时查询多个人的信息：
 
@@ -561,12 +602,15 @@ class RelationshipProcessor(BaseProcessor):
                     f"你已经调取了[{info_fetching['person_name']}]的[{info_fetching['info_type']}]信息\n"
                 )
 
+        example_json = _generate_random_prompt_example()
+
         prompt = (await global_prompt_manager.get_prompt_async("relationship_prompt")).format(
             name_block=name_block,
             bot_name=global_config.bot.nickname,
             time_now=time.strftime("%Y-%m-%d %H:%M:%S", time.localtime()),
             chat_observe_info=chat_observe_info,
             info_cache_block=info_cache_block,
+            example_json=example_json,
         )
 
         try:
diff --git a/src/individuality/individuality.py b/src/individuality/individuality.py
index beb7422cb..9ccfea0ed 100644
--- a/src/individuality/individuality.py
+++ b/src/individuality/individuality.py
@@ -6,13 +6,7 @@ import random
 import json
 import os
 import hashlib
-import traceback
 from rich.traceback import install
-from json_repair import repair_json
-from src.chat.utils.prompt_builder import Prompt, global_prompt_manager
-from src.manager.async_task_manager import AsyncTask
-from src.llm_models.utils_model import LLMRequest
-from src.config.config import global_config
 from src.common.logger import get_logger
 from src.person_info.person_info import get_person_info_manager
 
@@ -85,7 +79,7 @@ class Individuality:
                 "nickname": self.name,
             }
             await person_info_manager.update_one_field(self.bot_person_id, "impression", impression_text, data=update_data)
-            logger.info(f"已将完整人设更新到bot的impression中")
+            logger.info("已将完整人设更新到bot的impression中")
 
         await self.express_style.extract_and_store_personality_expressions()
 
diff --git a/src/plugins/built_in/core_actions/plugin.py b/src/plugins/built_in/core_actions/plugin.py
index 8ff8c3c8d..d0b73e09e 100644
--- a/src/plugins/built_in/core_actions/plugin.py
+++ b/src/plugins/built_in/core_actions/plugin.py
@@ -38,7 +38,8 @@ class ReplyAction(BaseAction):
     action_description = "参与聊天回复，发送文本进行表达"
 
     # 动作参数定义
-    action_parameters = {"reply_to": "你要回复的对方的发言内容，格式：（用户名:发言内容），可以为none"}
+    action_parameters = {"reply_to": "你要回复的对方的发言内容，格式：（用户名:发言内容），可以为none",
+                         "reason": "回复的原因"}
 
     # 动作使用场景
     action_require = ["你想要闲聊或者随便附和", "有人提到你", "如果你刚刚进行了回复，不要对同一个话题重复回应"]
@@ -106,8 +107,8 @@ class ReplyAction(BaseAction):
 class NoReplyAction(BaseAction):
     """不回复动作，继承时会等待新消息或超时"""
 
-    # focus_activation_type = ActionActivationType.ALWAYS
-    focus_activation_type = ActionActivationType.RANDOM
+    focus_activation_type = ActionActivationType.ALWAYS
+    # focus_activation_type = ActionActivationType.RANDOM
     normal_activation_type = ActionActivationType.NEVER
     mode_enable = ChatMode.FOCUS
     parallel_action = False
@@ -122,7 +123,7 @@ class NoReplyAction(BaseAction):
     # 连续no_reply计数器
     _consecutive_count = 0
 
-    random_activation_probability = 0.2
+    # random_activation_probability = 0.2
 
     # 分级等待时间
     _waiting_stages = [10, 60, 600]  # 第1、2、3次的等待时间