diff --git a/src/plugins/chat/__init__.py b/src/plugins/chat/__init__.py
index 8bbb16bf5..55b83e889 100644
--- a/src/plugins/chat/__init__.py
+++ b/src/plugins/chat/__init__.py
@@ -84,7 +84,11 @@ async def start_background_tasks():
 @driver.on_startup
 async def init_schedule():
     """在 NoneBot2 启动时初始化日程系统"""
-    bot_schedule.initialize(name=global_config.BOT_NICKNAME, personality=global_config.PROMPT_PERSONALITY, behavior=global_config.PROMPT_SCHEDULE_GEN, interval=global_config.SCHEDULE_DOING_UPDATE_INTERVAL)
+    bot_schedule.initialize(
+        name=global_config.BOT_NICKNAME, 
+        personality=global_config.PROMPT_PERSONALITY, 
+        behavior=global_config.PROMPT_SCHEDULE_GEN, 
+        interval=global_config.SCHEDULE_DOING_UPDATE_INTERVAL)
     asyncio.create_task(bot_schedule.mai_schedule_start())
 
 @driver.on_startup
diff --git a/src/plugins/chat/prompt_builder.py b/src/plugins/chat/prompt_builder.py
index 283ea0eae..dc2e5930e 100644
--- a/src/plugins/chat/prompt_builder.py
+++ b/src/plugins/chat/prompt_builder.py
@@ -57,7 +57,7 @@ class PromptBuilder:
         mood_prompt = mood_manager.get_prompt()
 
         # 日程构建
-        schedule_prompt = f'''你现在正在做的事情是：{bot_schedule.get_current_num_task(num = 1,time_info = False)}'''
+        # schedule_prompt = f'''你现在正在做的事情是：{bot_schedule.get_current_num_task(num = 1,time_info = False)}'''
 
         # 获取聊天上下文
         chat_in_group = True
diff --git a/src/plugins/schedule/offline_llm.py b/src/plugins/schedule/offline_llm.py
index f274740fa..5276f3802 100644
--- a/src/plugins/schedule/offline_llm.py
+++ b/src/plugins/schedule/offline_llm.py
@@ -1,10 +1,7 @@
 import asyncio
 import os
-import time
-from typing import Tuple, Union
 
 import aiohttp
-import requests
 from src.common.logger import get_module_logger
 
 logger = get_module_logger("offline_llm")
diff --git a/src/plugins/schedule/schedule_generator.py b/src/plugins/schedule/schedule_generator.py
index b14ebd1ba..41cf187e1 100644
--- a/src/plugins/schedule/schedule_generator.py
+++ b/src/plugins/schedule/schedule_generator.py
@@ -24,7 +24,7 @@ logger = get_module_logger("scheduler", config=schedule_config)
 class ScheduleGenerator:
     # enable_output: bool = True
 
-    def __init__(self, ):
+    def __init__(self):
         # 使用离线LLM模型
         self.llm_scheduler_all = LLM_request(
             model= global_config.llm_reasoning, temperature=0.9, max_tokens=7000,request_type="schedule")
@@ -45,7 +45,11 @@ class ScheduleGenerator:
         
         self.schedule_doing_update_interval = 300 #最好大于60
     
-    def initialize(self,name: str = "bot_name", personality: str = "你是一个爱国爱党的新时代青年", behavior: str = "你非常外向，喜欢尝试新事物和人交流",interval: int = 60):
+    def initialize(
+        self,name: str = "bot_name", 
+        personality: str = "你是一个爱国爱党的新时代青年", 
+        behavior: str = "你非常外向，喜欢尝试新事物和人交流",
+        interval: int = 60):
         """初始化日程系统"""
         self.name = name
         self.behavior = behavior
@@ -117,7 +121,7 @@ class ScheduleGenerator:
         prompt =  f"你是{self.name}，{self.personality}，{self.behavior}"
         prompt += f"你昨天的日程是：{self.yesterday_schedule_text}\n"
         prompt += f"请为你生成{date_str}（{weekday}）的日程安排，结合你的个人特点和行为习惯\n"
-        prompt += "推测你的日程安排，包括你一天都在做什么，从起床到睡眠，有什么发现和思考，具体一些，详细一些，需要1500字以上，精确到每半个小时，记得写明时间\n"
+        prompt += "推测你的日程安排，包括你一天都在做什么，从起床到睡眠，有什么发现和思考，具体一些，详细一些，需要1500字以上，精确到每半个小时，记得写明时间\n" #noqa: E501
         prompt += "直接返回你的日程，从起床到睡觉，不要输出其他内容："
         return prompt
     
@@ -132,7 +136,7 @@ class ScheduleGenerator:
         
         prompt = f"你是{self.name}，{self.personality}，{self.behavior}"
         prompt += f"你今天的日程是：{self.today_schedule_text}\n"
-        prompt += f"你之前做了的事情是：{previous_doings}，从之前到现在已经过去了{self.schedule_doing_update_interval/60}分钟了\n"
+        prompt += f"你之前做了的事情是：{previous_doings}，从之前到现在已经过去了{self.schedule_doing_update_interval/60}分钟了\n" #noqa: E501
         if mind_thinking:
             prompt += f"你脑子里在想：{mind_thinking}\n"
         prompt += f"现在是{now_time}，结合你的个人特点和行为习惯,"
@@ -284,7 +288,11 @@ class ScheduleGenerator:
 async def main():
     # 使用示例
     scheduler = ScheduleGenerator()
-    scheduler.initialize(name="麦麦", personality="你叫麦麦，你19岁，是一个大二的女大学生，你有一头黑色短发，你会刷贴吧，你现在在学习心理学", behavior="你比较内向，一般熬夜比较晚，然后第二天早上10点起床吃早午饭",interval=60)
+    scheduler.initialize(
+        name="麦麦", 
+        personality="你叫麦麦，你19岁，是一个大二的女大学生，你有一头黑色短发，你会刷贴吧，你现在在学习心理学", 
+        behavior="你比较内向，一般熬夜比较晚，然后第二天早上10点起床吃早午饭",
+        interval=60)
     await scheduler.mai_schedule_start()
     
 
diff --git a/配置文件错误排查.py b/配置文件错误排查.py
index 114171135..d277ceb4a 100644
--- a/配置文件错误排查.py
+++ b/配置文件错误排查.py
@@ -1,8 +1,7 @@
 import tomli
 import sys
-import re
 from pathlib import Path
-from typing import Dict, Any, List, Set, Tuple
+from typing import Dict, Any, List, Tuple
 
 def load_toml_file(file_path: str) -> Dict[str, Any]:
     """加载TOML文件"""
@@ -184,10 +183,15 @@ def check_model_configurations(config: Dict[str, Any], env_vars: Dict[str, str])
                 provider = model_config["provider"].upper()
                 
                 # 检查拼写错误
-                for known_provider, correct_provider in reverse_mapping.items():
+                for known_provider, _correct_provider in reverse_mapping.items():
                     # 使用模糊匹配检测拼写错误
-                    if provider != known_provider and _similar_strings(provider, known_provider) and provider not in reverse_mapping:
-                        errors.append(f"[model.{model_name}]的provider '{model_config['provider']}' 可能拼写错误，应为 '{known_provider}'")
+                    if (provider != known_provider and 
+                        _similar_strings(provider, known_provider) and 
+                        provider not in reverse_mapping):
+                        errors.append(
+                            f"[model.{model_name}]的provider '{model_config['provider']}' "
+                            f"可能拼写错误，应为 '{known_provider}'"
+                        )
                         break
     
     return errors
@@ -223,7 +227,7 @@ def check_api_providers(config: Dict[str, Any], env_vars: Dict[str, str]) -> Lis
     
     # 检查配置文件中使用的所有提供商
     used_providers = set()
-    for model_category, model_config in config["model"].items():
+    for _model_category, model_config in config["model"].items():
         if "provider" in model_config:
             provider = model_config["provider"]
             used_providers.add(provider)
@@ -247,7 +251,7 @@ def check_api_providers(config: Dict[str, Any], env_vars: Dict[str, str]) -> Lis
     # 特别检查常见的拼写错误
     for provider in used_providers:
         if provider.upper() == "SILICONFOLW":
-            errors.append(f"提供商 'SILICONFOLW' 存在拼写错误，应为 'SILICONFLOW'")
+            errors.append("提供商 'SILICONFOLW' 存在拼写错误，应为 'SILICONFLOW'")
     
     return errors
 
@@ -272,7 +276,7 @@ def check_groups_configuration(config: Dict[str, Any]) -> List[str]:
                 "main": "groups.talk_allowed中存在默认示例值'123'，请修改为真实的群号",
                 "details": [
                     f"  当前值: {groups['talk_allowed']}",
-                    f"  '123'为示例值，需要替换为真实群号"
+                    "  '123'为示例值，需要替换为真实群号"
                 ]
             })
         
@@ -371,7 +375,8 @@ def check_memory_config(config: Dict[str, Any]) -> List[str]:
     if "memory_compress_rate" in memory and (memory["memory_compress_rate"] <= 0 or memory["memory_compress_rate"] > 1):
         errors.append(f"memory.memory_compress_rate值无效: {memory['memory_compress_rate']}, 应在0-1之间")
     
-    if "memory_forget_percentage" in memory and (memory["memory_forget_percentage"] <= 0 or memory["memory_forget_percentage"] > 1):
+    if ("memory_forget_percentage" in memory 
+    and (memory["memory_forget_percentage"] <= 0 or memory["memory_forget_percentage"] > 1)):
         errors.append(f"memory.memory_forget_percentage值无效: {memory['memory_forget_percentage']}, 应在0-1之间")
     
     return errors
@@ -393,7 +398,10 @@ def check_personality_config(config: Dict[str, Any]) -> List[str]:
     else:
         # 检查数组长度
         if len(personality["prompt_personality"]) < 1:
-            errors.append(f"personality.prompt_personality数组长度不足，当前长度: {len(personality['prompt_personality'])}, 需要至少1项")
+            errors.append(
+                f"personality.prompt_personality至少需要1项，"
+                f"当前长度: {len(personality['prompt_personality'])}"
+            )
         else:
             # 模板默认值
             template_values = [
@@ -452,10 +460,13 @@ def check_bot_config(config: Dict[str, Any]) -> List[str]:
 
 def format_results(all_errors):
     """格式化检查结果"""
-    sections_errors, prob_sum_errors, prob_range_errors, model_errors, api_errors, groups_errors, kr_errors, willing_errors, memory_errors, personality_errors, bot_results = all_errors
+    sections_errors, prob_sum_errors, prob_range_errors, model_errors, api_errors, groups_errors, kr_errors, willing_errors, memory_errors, personality_errors, bot_results = all_errors  # noqa: E501, F821
     bot_errors, bot_infos = bot_results
     
-    if not any([sections_errors, prob_sum_errors, prob_range_errors, model_errors, api_errors, groups_errors, kr_errors, willing_errors, memory_errors, personality_errors, bot_errors]):
+    if not any([
+        sections_errors, prob_sum_errors, 
+        prob_range_errors, model_errors, api_errors, groups_errors, 
+        kr_errors, willing_errors, memory_errors, personality_errors, bot_errors]):
         result = "✅ 配置文件检查通过，未发现问题。"
         
         # 添加机器人信息
@@ -574,7 +585,10 @@ def main():
     bot_results = check_bot_config(config)
     
     # 格式化并打印结果
-    all_errors = (sections_errors, prob_sum_errors, prob_range_errors, model_errors, api_errors, groups_errors, kr_errors, willing_errors, memory_errors, personality_errors, bot_results)
+    all_errors = (
+        sections_errors, prob_sum_errors, 
+        prob_range_errors, model_errors, api_errors, groups_errors, 
+        kr_errors, willing_errors, memory_errors, personality_errors, bot_results)
     result = format_results(all_errors)
     print("📋 机器人配置检查结果:")
     print(result)
@@ -586,7 +600,9 @@ def main():
     bot_errors, _ = bot_results
     
     # 计算普通错误列表的长度
-    for errors in [sections_errors, model_errors, api_errors, groups_errors, kr_errors, willing_errors, memory_errors, bot_errors]:
+    for errors in [
+        sections_errors, model_errors, api_errors,
+        groups_errors, kr_errors, willing_errors, memory_errors, bot_errors]:
         total_errors += len(errors)
     
     # 计算元组列表的长度（概率相关错误）