diff --git a/.gitignore b/.gitignore
index 0612e1e3..de10c0b7 100644
--- a/.gitignore
+++ b/.gitignore
@@ -32,7 +32,6 @@ plugins/banwords/lib/__pycache__
 !plugins/role
 !plugins/keyword
 !plugins/linkai
-!plugins/agent
 !plugins/cow_cli
 client_config.json
 ref/
diff --git a/plugins/agent/README.md b/plugins/agent/README.md
deleted file mode 100644
index 744a3d61..00000000
--- a/plugins/agent/README.md
+++ /dev/null
@@ -1,66 +0,0 @@
-# Agent插件
-
-## 插件说明
-
-基于 [AgentMesh](https://github.com/MinimalFuture/AgentMesh) 多智能体框架实现的Agent插件，可以让机器人快速获得Agent能力，通过自然语言对话来访问 **终端、浏览器、文件系统、搜索引擎** 等各类工具。
-同时还支持通过 **多智能体协作** 来完成复杂任务，例如多智能体任务分发、多智能体问题讨论、协同处理等。
-
-AgentMesh项目地址：https://github.com/MinimalFuture/AgentMesh
-
-## 安装
-
-1. 确保已安装依赖：
-
-```bash
-pip install agentmesh-sdk>=0.1.3
-```
-
-2. 如需使用浏览器工具，还需安装：
-
-```bash
-pip install browser-use>=0.1.40
-playwright install
-```
-
-## 配置
-
-插件配置文件是 `plugins/agent`目录下的 `config.yaml`，包含智能体团队的配置以及工具的配置，可以从模板文件 `config-template.yaml`中复制：
-
-```bash
-cp config-template.yaml config.yaml
-```
-
-说明：
-
- - `team`配置是默认选中的 agent team
- - `teams` 下是Agent团队配置，团队的model默认为`gpt-4.1-mini`，可根据需要进行修改，模型对应的 `api_key` 需要在项目根目录的 `config.json` 全局配置中进行配置。例如openai模型需要配置 `open_ai_api_key`
- - 支持为 `agents` 下面的每个agent添加model字段来设置不同的模型
-
-
-## 使用方法
-
-在对机器人发送的消息中使用 `$agent` 前缀来触发插件，支持以下命令：
-
-- `$agent [task]`: 使用默认团队执行任务 (默认团队可通 config.yaml 中的team配置修改)
-- `$agent teams`: 列出可用的团队
-- `$agent use [team_name] [task]`: 使用指定的团队执行任务
-
-
-### 示例
-
-```bash
-$agent 帮我查看当前目录下有哪些文件夹
-$agent teams
-$agent use software_team 帮我写一个产品预约体验的表单页面
-```
-
-## 工具支持
-
-目前支持多种内置工具，包括但不限于：
-
-- `calculator`: 数学计算工具
-- `current_time`: 获取当前时间
-- `browser`: 浏览器操作工具，注意需安装`browser-use`依赖
-- `google_search`: 搜索引擎，注意需在`config.yaml`中配置 `api_key`
-- `file_save`: 文件保存工具，开启后智能体输出的内容将保存在 `workspace` 目录下
-- `terminal`: 终端命令执行工具
diff --git a/plugins/agent/__init__.py b/plugins/agent/__init__.py
deleted file mode 100644
index 75642e00..00000000
--- a/plugins/agent/__init__.py
+++ /dev/null
@@ -1,3 +0,0 @@
-from .agent import AgentPlugin
-
-__all__ = ["AgentPlugin"]
\ No newline at end of file
diff --git a/plugins/agent/agent.py b/plugins/agent/agent.py
deleted file mode 100644
index 700f134e..00000000
--- a/plugins/agent/agent.py
+++ /dev/null
@@ -1,282 +0,0 @@
-import os
-import yaml
-from typing import Dict, List, Optional
-
-from agentmesh import AgentTeam, Agent, LLMModel
-from agentmesh.models import ClaudeModel
-from agentmesh.tools import ToolManager
-from config import conf
-
-import plugins
-from plugins import Plugin, Event, EventContext, EventAction
-from bridge.context import ContextType
-from bridge.reply import Reply, ReplyType
-from common.log import logger
-
-
-@plugins.register(
-    name="agent",
-    desc="Use AgentMesh framework to process tasks with multi-agent teams",
-    version="0.1.0",
-    author="Saboteur7",
-    desire_priority=1,
-)
-class AgentPlugin(Plugin):
-    """Plugin for integrating AgentMesh framework."""
-    
-    def __init__(self):
-        super().__init__()
-        self.handlers[Event.ON_HANDLE_CONTEXT] = self.on_handle_context
-        self.name = "agent"
-        self.description = "Use AgentMesh framework to process tasks with multi-agent teams"
-        self.config = self._load_config()
-        self.tool_manager = ToolManager()
-        self.tool_manager.load_tools(config_dict=self.config.get("tools"))
-        logger.debug("[agent] inited")
-    
-    def _load_config(self) -> Dict:
-        """Load configuration from config.yaml file."""
-        config_path = os.path.join(self.path, "config.yaml")
-        if not os.path.exists(config_path):
-            logger.debug(f"Config file not found at {config_path}")
-            return {}
-            
-        with open(config_path, 'r', encoding='utf-8') as f:
-            return yaml.safe_load(f)
-    
-    def get_help_text(self, verbose=False, **kwargs):
-        """Return help message for the agent plugin."""
-        help_text = "通过AgentMesh实现对终端、浏览器、文件系统、搜索引擎等工具的执行，并支持多智能体协作。"
-        trigger_prefix = conf().get("plugin_trigger_prefix", "$")
-        
-        if not verbose:
-            return help_text
-            
-        teams = self.get_available_teams()
-        teams_str = ", ".join(teams) if teams else "未配置任何团队"
-        
-        help_text += "\n\n使用说明：\n"
-        help_text += f"{trigger_prefix}agent [task] - 使用默认团队执行任务\n"
-        help_text += f"{trigger_prefix}agent teams - 列出可用的团队\n"
-        help_text += f"{trigger_prefix}agent use [team_name] [task] - 使用特定团队执行任务\n\n"
-        help_text += f"可用团队: \n{teams_str}\n\n"
-        help_text += f"示例:\n"
-        help_text += f"{trigger_prefix}agent 帮我查看当前文件夹路径\n"
-        help_text += f"{trigger_prefix}agent use software_team 帮我写一个产品预约体验的表单页面"
-        return help_text
-    
-    def get_available_teams(self) -> List[str]:
-        """Get list of available teams from configuration."""
-        teams_config = self.config.get("teams", {})
-        return list(teams_config.keys())
-
-
-    def create_team_from_config(self, team_name: str) -> Optional[AgentTeam]:
-        """Create a team from configuration."""
-        # Get teams configuration
-        teams_config = self.config.get("teams", {})
-
-        # Check if the specified team exists
-        if team_name not in teams_config:
-            logger.error(f"Team '{team_name}' not found in configuration.")
-            available_teams = list(teams_config.keys())
-            logger.info(f"Available teams: {', '.join(available_teams)}")
-            return None
-
-        # Get team configuration
-        team_config = teams_config[team_name]
-
-        # Get team's model
-        team_model_name = team_config.get("model", "gpt-4.1-mini")
-        team_model = self.create_llm_model(team_model_name)
-
-        # Get team's max_steps (default to 20 if not specified)
-        team_max_steps = team_config.get("max_steps", 20)
-
-        # Create team with the model
-        team = AgentTeam(
-            name=team_name,
-            description=team_config.get("description", ""),
-            rule=team_config.get("rule", ""),
-            model=team_model,
-            max_steps=team_max_steps
-        )
-
-        # Create and add agents to the team
-        agents_config = team_config.get("agents", [])
-        for agent_config in agents_config:
-            # Check if agent has a specific model
-            if agent_config.get("model"):
-                agent_model = self.create_llm_model(agent_config.get("model"))
-            else:
-                agent_model = team_model
-
-            # Get agent's max_steps
-            agent_max_steps = agent_config.get("max_steps")
-
-            agent = Agent(
-                name=agent_config.get("name", ""),
-                system_prompt=agent_config.get("system_prompt", ""),
-                model=agent_model,  # Use agent's model if specified, otherwise will use team's model
-                description=agent_config.get("description", ""),
-                max_steps=agent_max_steps
-            )
-
-            # Add tools to the agent if specified
-            tool_names = agent_config.get("tools", [])
-            for tool_name in tool_names:
-                tool = self.tool_manager.create_tool(tool_name)
-                if tool:
-                    agent.add_tool(tool)
-                else:
-                    if tool_name == "browser":
-                        logger.warning(
-                            "Tool 'Browser' loaded failed, "
-                            "please install the required dependency with: \n"
-                            "'pip install browser-use>=0.1.40' or 'pip install agentmesh-sdk[full]'\n"
-                        )
-                    else:
-                        logger.warning(f"Tool '{tool_name}' not found for agent '{agent.name}'\n")
-
-            # Add agent to team
-            team.add(agent)
-
-        return team
-    
-    def on_handle_context(self, e_context: EventContext):
-        """Handle the message context."""
-        if e_context['context'].type != ContextType.TEXT:
-            return
-        content = e_context['context'].content
-        trigger_prefix = conf().get("plugin_trigger_prefix", "$")
-        
-        if not content.startswith(f"{trigger_prefix}agent "):
-            e_context.action = EventAction.CONTINUE
-            return
-
-        if not self.config:
-            reply = Reply()
-            reply.type = ReplyType.ERROR
-            reply.content = "未找到插件配置，请在 plugins/agent 目录下创建 config.yaml 配置文件，可根据 config-template.yml 模板文件复制"
-            e_context['reply'] = reply
-            e_context.action = EventAction.BREAK_PASS
-            return
-
-        # Extract the actual task
-        task = content[len(f"{trigger_prefix}agent "):].strip()
-        
-        # If task is empty, return help message
-        if not task:
-            reply = Reply()
-            reply.type = ReplyType.TEXT
-            reply.content = self.get_help_text(verbose=True)
-            e_context['reply'] = reply
-            e_context.action = EventAction.BREAK_PASS
-            return
-            
-        # Check if task is asking for available teams
-        if task.lower() in ["teams", "list teams", "show teams"]:
-            teams = self.get_available_teams()
-            reply = Reply()
-            reply.type = ReplyType.TEXT
-            
-            if not teams:
-                reply.content = "未配置任何团队。请检查 config.yaml 文件。"
-            else:
-                reply.content = f"可用团队: {', '.join(teams)}"
-                
-            e_context['reply'] = reply
-            e_context.action = EventAction.BREAK_PASS
-            return
-        
-        # Check if task specifies a team
-        team_name = None
-        if task.startswith("use "):
-            parts = task[4:].split(" ", 1)
-            if len(parts) > 0:
-                team_name = parts[0]
-                if len(parts) > 1:
-                    task = parts[1].strip()
-                else:
-                    reply = Reply()
-                    reply.type = ReplyType.TEXT
-                    reply.content = f"已选择团队 '{team_name}'。请输入您想执行的任务。"
-                    e_context['reply'] = reply
-                    e_context.action = EventAction.BREAK_PASS
-                    return
-        if not team_name:
-            team_name = self.config.get("team")
-
-        # If no team specified, use default or first available
-        if not team_name:
-            teams = self.configself.get_available_teams()
-            if not teams:
-                reply = Reply()
-                reply.type = ReplyType.TEXT
-                reply.content = "未配置任何团队。请检查 config.yaml 文件。"
-                e_context['reply'] = reply
-                e_context.action = EventAction.BREAK_PASS
-                return
-            team_name = teams[0]
-            
-        # Create team
-        team = self.create_team_from_config(team_name)
-        if not team:
-            reply = Reply()
-            reply.type = ReplyType.TEXT
-            reply.content = f"创建团队 '{team_name}' 失败。请检查配置。"
-            e_context['reply'] = reply
-            e_context.action = EventAction.BREAK_PASS
-            return
-        
-        # Run the task
-        try:
-            logger.info(f"[agent] Running task '{task}' with team '{team_name}', team_model={team.model.model}")
-            result = team.run_async(task=task)
-            for agent_result in result:
-                res_text = f"🤖 {agent_result.get('agent_name')}\n\n{agent_result.get('final_answer')}"
-                _send_text(e_context, content=res_text)
-            
-            reply = Reply()
-            reply.type = ReplyType.TEXT
-            reply.content = ""
-            e_context['reply'] = reply
-            e_context.action = EventAction.BREAK_PASS
-            
-        except Exception as e:
-            logger.exception(f"Error running task with team '{team_name}'")
-            
-            reply = Reply()
-            reply.type = ReplyType.ERROR
-            reply.content = f"执行任务时出错: {str(e)}"
-            e_context['reply'] = reply
-            e_context.action = EventAction.BREAK_PASS
-        return
-
-    def create_llm_model(self, model_name) -> LLMModel:
-        if conf().get("use_linkai"):
-            api_base = "https://api.link-ai.tech/v1"
-            api_key = conf().get("linkai_api_key")
-        elif model_name.startswith(("gpt", "text-davinci", "o1", "o3")):
-            api_base = conf().get("open_ai_api_base") or "https://api.openai.com/v1"
-            api_key = conf().get("open_ai_api_key")
-        elif model_name.startswith("claude"):
-            return ClaudeModel(model=model_name, api_key=conf().get("claude_api_key"))
-        elif model_name.startswith("moonshot"):
-            api_base = "https://api.moonshot.cn/v1"
-            api_key = conf().get("moonshot_api_key")
-        elif model_name.startswith("qwen"):
-            api_base = "https://dashscope.aliyuncs.com/compatible-mode/v1"
-            api_key = conf().get("dashscope_api_key")
-        else:
-            api_base = conf().get("open_ai_api_base") or "https://api.openai.com/v1"
-            api_key = conf().get("open_ai_api_key")
-
-        llm_model = LLMModel(model=model_name, api_key=api_key, api_base=api_base)
-        return llm_model
-
-
-def _send_text(e_context: EventContext, content: str):
-    reply = Reply(ReplyType.TEXT, content)
-    channel = e_context["channel"]
-    channel.send(reply, e_context["context"])
diff --git a/plugins/agent/config-template.yaml b/plugins/agent/config-template.yaml
deleted file mode 100644
index db0e69b2..00000000
--- a/plugins/agent/config-template.yaml
+++ /dev/null
@@ -1,52 +0,0 @@
-# 默认选中的Agent Team名称
-team: general_team
-
-tools:
-  google_search:
-    # get your apikey from https://serper.dev/
-    api_key: "YOUR API KEY"
-
-# Agent Team 配置
-teams:
-  # 通用智能体团队
-  general_team:
-    model: "gpt-4.1-mini"        # 团队使用的模型
-    description: "A versatile research and information agent team"
-    max_steps: 5
-    agents:
-      - name: "通用智能助手"
-        description: "Universal assistant specializing in research, information synthesis, and task execution"
-        system_prompt: "You are a versatile assistant who answers questions and completes tasks using available tools. Reply in a clearly structured, attractive and easy to read format."
-        # Agent 支持使用的工具
-        tools:
-          - time
-          - calculator
-          - google_search
-          - browser
-          - terminal
-
-  # 软件开发智能体团队
-  software_team:
-    model: "gpt-4.1-mini"
-    description: "A software development team with product manager, developer and tester."
-    rule: "A normal R&D process should be that Product Manager writes PRD, Developer writes code based on PRD, and Finally, Tester performs testing."
-    max_steps: 10
-    agents:
-      - name: "Product-Manager"
-        description: "Responsible for product requirements and documentation"
-        system_prompt: "You are an experienced product manager who creates concise PRDs, focusing on user needs and feature specifications. You always format your responses in Markdown."
-        tools:
-          - time
-          - file_save
-      - name: "Developer"
-        description: "Implements code based on PRD"
-        system_prompt: "You are a skilled developer. When developing web application, you creates single-page website based on user needs, you deliver HTML files with embedded JavaScript and CSS that are visually appealing, responsive, and user-friendly, featuring a grand layout and beautiful background. The HTML, CSS, and JavaScript code should be well-structured and effectively organized."
-        tools:
-          - file_save
-      - name: "Tester"
-        description: "Tests code and verifies functionality"
-        system_prompt: "You are a tester who validates code against requirements. For HTML applications, use browser tools to test functionality. For Python or other client-side applications, use the terminal tool to run and test. You only need to test a few core cases."
-        tools:
-          - file_save
-          - browser
-          - terminal