feat: key management and scheduled task tools

agent/prompt/builder.py

@@ -242,6 +242,8 @@ def _build_tooling_section(tools: List[Any], language: str) -> List[str]:
         "- 每次工具调用后，评估是否已获得足够信息来推进或完成任务",
         "- 避免重复调用相同的工具和相同参数获取相同的信息，除非用户明确要求",
         "",
+        "**安全提醒**: 回复中涉及密钥、令牌、密码等敏感信息时，必须脱敏处理，禁止直接显示完整内容。",
+        "",
     ])
     
     return lines

agent/skills/config.py

@@ -70,33 +70,27 @@ def should_include_skill(
     entry: SkillEntry,
     config: Optional[Dict] = None,
     current_platform: Optional[str] = None,
-    lenient: bool = True,
 ) -> bool:
     """
     Determine if a skill should be included based on requirements.
     
-    Similar to clawdbot's shouldIncludeSkill logic, but with lenient mode:
+    Simple rule: Skills are auto-enabled if their requirements are met.
-    - In lenient mode (default): Only check explicit disable and platform, ignore missing requirements
+    - Has required API keys → enabled
-    - In strict mode: Check all requirements (binary, env vars, config)
+    - Missing API keys → disabled
+    - Wrong keys → enabled but will fail at runtime (LLM will handle error)
     
     :param entry: SkillEntry to check
-    :param config: Configuration dictionary
+    :param config: Configuration dictionary (currently unused, reserved for future)
     :param current_platform: Current platform (default: auto-detect)
-    :param lenient: If True, ignore missing requirements and load all skills (default: True)
     :return: True if skill should be included
     """
     metadata = entry.metadata
-    skill_name = entry.skill.name
-    skill_config = get_skill_config(config, skill_name)
-    
-    # Always check if skill is explicitly disabled in config
-    if skill_config and skill_config.get('enabled') is False:
-        return False
     
+    # No metadata = always include (no requirements)
     if not metadata:
         return True
     
-    # Always check platform requirements (can't work on wrong platform)
+    # Check platform requirements (can't work on wrong platform)
     if metadata.os:
         platform_name = current_platform or resolve_runtime_platform()
         # Map common platform names
@@ -114,12 +108,7 @@ def should_include_skill(
     if metadata.always:
         return True
     
-    # In lenient mode, skip requirement checks and load all skills
+    # Check requirements
-    # Skills will fail gracefully at runtime if requirements are missing
-    if lenient:
-        return True
-    
-    # Strict mode: Check all requirements
     if metadata.requires:
         # Check required binaries (all must be present)
         required_bins = metadata.requires.get('bins', [])
@@ -133,29 +122,13 @@ def should_include_skill(
             if not has_any_binary(any_bins):
                 return False
         
-        # Check environment variables (with config fallback)
+        # Check environment variables (API keys)
+        # Simple rule: All required env vars must be set
         required_env = metadata.requires.get('env', [])
         if required_env:
             for env_name in required_env:
-                # Check in order: 1) env var, 2) skill config env, 3) skill config apiKey (if primaryEnv)
+                if not has_env_var(env_name):
-                if has_env_var(env_name):
+                    # Missing required API key → disable skill
-                    continue
-                if skill_config:
-                    # Check skill config env dict
-                    skill_env = skill_config.get('env', {})
-                    if isinstance(skill_env, dict) and env_name in skill_env:
-                        continue
-                    # Check skill config apiKey (if this is the primaryEnv)
-                    if metadata.primary_env == env_name and skill_config.get('apiKey'):
-                        continue
-                # Requirement not satisfied
-                return False
-        
-        # Check config paths
-        required_config = metadata.requires.get('config', [])
-        if required_config and config:
-            for config_path in required_config:
-                if not is_config_path_truthy(config, config_path):
                     return False
     
     return True

agent/skills/formatter.py

@@ -34,6 +34,7 @@ def format_skills_for_prompt(skills: List[Skill]) -> str:
         lines.append(f"    <name>{_escape_xml(skill.name)}</name>")
         lines.append(f"    <description>{_escape_xml(skill.description)}</description>")
         lines.append(f"    <location>{_escape_xml(skill.file_path)}</location>")
+        lines.append(f"    <base_dir>{_escape_xml(skill.base_dir)}</base_dir>")
         lines.append("  </skill>")
     
     lines.append("</available_skills>")

agent/skills/frontmatter.py

@@ -23,7 +23,22 @@ def parse_frontmatter(content: str) -> Dict[str, Any]:
     
     frontmatter_text = match.group(1)
     
-    # Simple YAML-like parsing (supports key: value format)
+    # Try to use PyYAML for proper YAML parsing
+    try:
+        import yaml
+        frontmatter = yaml.safe_load(frontmatter_text)
+        if not isinstance(frontmatter, dict):
+            frontmatter = {}
+        return frontmatter
+    except ImportError:
+        # Fallback to simple parsing if PyYAML not available
+        pass
+    except Exception:
+        # If YAML parsing fails, fall back to simple parsing
+        pass
+    
+    # Simple YAML-like parsing (supports key: value format only)
+    # This is a fallback for when PyYAML is not available
     for line in frontmatter_text.split('\n'):
         line = line.strip()
         if not line or line.startswith('#'):
@@ -72,10 +87,8 @@ def parse_metadata(frontmatter: Dict[str, Any]) -> Optional[SkillMetadata]:
     if not isinstance(metadata_raw, dict):
         return None
     
-    # Support both 'moltbot' and 'cow' keys for compatibility
+    # Use metadata_raw directly (COW format)
-    meta_obj = metadata_raw.get('moltbot') or metadata_raw.get('cow')
+    meta_obj = metadata_raw
-    if not meta_obj or not isinstance(meta_obj, dict):
-        return None
     
     # Parse install specs
     install_specs = []

agent/skills/manager.py

@@ -82,32 +82,24 @@ class SkillManager:
         self,
         skill_filter: Optional[List[str]] = None,
         include_disabled: bool = False,
-        check_requirements: bool = False,  # Changed default to False for lenient loading
-        lenient: bool = True,  # New parameter for lenient mode
     ) -> List[SkillEntry]:
         """
         Filter skills based on criteria.
         
-        By default (lenient=True), all skills are loaded regardless of missing requirements.
+        Simple rule: Skills are auto-enabled if requirements are met.
-        Skills will fail gracefully at runtime if requirements are not met.
+        - Has required API keys → included
+        - Missing API keys → excluded
         
         :param skill_filter: List of skill names to include (None = all)
         :param include_disabled: Whether to include skills with disable_model_invocation=True
-        :param check_requirements: Whether to check skill requirements (default: False)
-        :param lenient: If True, ignore missing requirements (default: True)
         :return: Filtered list of skill entries
         """
         from agent.skills.config import should_include_skill
         
         entries = list(self.skills.values())
         
-        # Check requirements (platform, explicit disable, etc.)
+        # Check requirements (platform, binaries, env vars)
-        # In lenient mode, only checks platform and explicit disable
+        entries = [e for e in entries if should_include_skill(e, self.config)]
-        if check_requirements or not lenient:
-            entries = [e for e in entries if should_include_skill(e, self.config, lenient=lenient)]
-        else:
-            # Lenient mode: only check explicit disable and platform
-            entries = [e for e in entries if should_include_skill(e, self.config, lenient=True)]
         
         # Apply skill filter
         if skill_filter is not None:

agent/tools/__init__.py

@@ -13,11 +13,21 @@ from agent.tools.ls.ls import Ls
 from agent.tools.memory.memory_search import MemorySearchTool
 from agent.tools.memory.memory_get import MemoryGetTool
 
+# Import env config tool
+from agent.tools.env_config.env_config import EnvConfig
+
 # Import tools with optional dependencies
 def _import_optional_tools():
     """Import tools that have optional dependencies"""
     tools = {}
     
+    # Scheduler Tool (requires croniter)
+    try:
+        from agent.tools.scheduler.scheduler_tool import SchedulerTool
+        tools['SchedulerTool'] = SchedulerTool
+    except ImportError:
+        pass
+    
     # Google Search (requires requests)
     try:
         from agent.tools.google_search.google_search import GoogleSearch
@@ -43,6 +53,7 @@ def _import_optional_tools():
 
 # Load optional tools
 _optional_tools = _import_optional_tools()
+SchedulerTool = _optional_tools.get('SchedulerTool')
 GoogleSearch = _optional_tools.get('GoogleSearch')
 FileSave = _optional_tools.get('FileSave') 
 Terminal = _optional_tools.get('Terminal')
@@ -79,6 +90,8 @@ __all__ = [
     'Ls',
     'MemorySearchTool',
     'MemoryGetTool',
+    'EnvConfig',
+    'SchedulerTool',
     # Optional tools (may be None if dependencies not available)
     'GoogleSearch',
     'FileSave',

agent/tools/env_config/__init__.py

@@ -0,0 +1,3 @@
+from agent.tools.env_config.env_config import EnvConfig
+
+__all__ = ['EnvConfig']

agent/tools/env_config/env_config.py

@@ -0,0 +1,283 @@
+"""
+Environment Configuration Tool - Manage API keys and environment variables
+"""
+
+import os
+import re
+from typing import Dict, Any
+from pathlib import Path
+
+from agent.tools.base_tool import BaseTool, ToolResult
+from common.log import logger
+
+
+# API Key 知识库：常见的环境变量及其描述
+API_KEY_REGISTRY = {
+    # AI 模型服务
+    "OPENAI_API_KEY": "OpenAI API 密钥 (用于GPT模型、Embedding模型)",
+    "GEMINI_API_KEY": "Google Gemini API 密钥",
+    "CLAUDE_API_KEY": "Claude API 密钥 (用于Claude模型)",
+    "LINKAI_API_KEY": "LinkAI智能体平台 API 密钥，支持多种模型切换",
+    # 搜索服务
+    "BOCHA_API_KEY": "博查 AI 搜索 API 密钥 ",
+}
+
+class EnvConfig(BaseTool):
+    """Tool for managing environment variables (API keys, etc.)"""
+    
+    name: str = "env_config"
+    description: str = (
+        "Manage API keys and skill configurations stored in the workspace .env file. "
+        "Use this tool when user wants to configure API keys (like BOCHA_API_KEY, OPENAI_API_KEY), "
+        "view configured keys, or manage skill settings. "
+        "Actions: 'set' (add/update key), 'get' (view specific key), 'list' (show all configured keys), 'delete' (remove key). "
+        "Values are automatically masked for security. Changes take effect immediately via hot reload."
+    )
+    
+    params: dict = {
+        "type": "object",
+        "properties": {
+            "action": {
+                "type": "string",
+                "description": "Action to perform: 'set', 'get', 'list', 'delete'",
+                "enum": ["set", "get", "list", "delete"]
+            },
+            "key": {
+                "type": "string",
+                "description": (
+                    "Environment variable key name. Common keys:\n"
+                    "- OPENAI_API_KEY: OpenAI API (GPT models)\n"
+                    "- OPENAI_API_BASE: OpenAI API base URL\n"
+                    "- CLAUDE_API_KEY: Anthropic Claude API\n"
+                    "- GEMINI_API_KEY: Google Gemini API\n"
+                    "- LINKAI_API_KEY: LinkAI platform\n"
+                    "- BOCHA_API_KEY: Bocha AI search (博查搜索)\n"
+                    "Use exact key names (case-sensitive, all uppercase with underscores)"
+                )
+            },
+            "value": {
+                "type": "string",
+                "description": "Value to set for the environment variable (for 'set' action)"
+            }
+        },
+        "required": ["action"]
+    }
+    
+    def __init__(self, config: dict = None):
+        self.config = config or {}
+        self.workspace_dir = self.config.get("workspace_dir", os.path.expanduser("~/cow"))
+        self.env_path = os.path.join(self.workspace_dir, '.env')
+        self.agent_bridge = self.config.get("agent_bridge")  # Reference to AgentBridge for hot reload
+        # Don't create .env file in __init__ to avoid issues during tool discovery
+        # It will be created on first use in execute()
+    
+    def _ensure_env_file(self):
+        """Ensure the .env file exists"""
+        # Create workspace directory if it doesn't exist
+        os.makedirs(self.workspace_dir, exist_ok=True)
+        
+        if not os.path.exists(self.env_path):
+            Path(self.env_path).touch()
+            logger.info(f"[EnvConfig] Created .env file at {self.env_path}")
+    
+    def _mask_value(self, value: str) -> str:
+        """Mask sensitive parts of a value for logging"""
+        if not value or len(value) <= 10:
+            return "***"
+        return f"{value[:6]}***{value[-4:]}"
+    
+    def _read_env_file(self) -> Dict[str, str]:
+        """Read all key-value pairs from .env file"""
+        env_vars = {}
+        if os.path.exists(self.env_path):
+            with open(self.env_path, 'r', encoding='utf-8') as f:
+                for line in f:
+                    line = line.strip()
+                    # Skip empty lines and comments
+                    if not line or line.startswith('#'):
+                        continue
+                    # Parse KEY=VALUE
+                    match = re.match(r'^([^=]+)=(.*)$', line)
+                    if match:
+                        key, value = match.groups()
+                        env_vars[key.strip()] = value.strip()
+        return env_vars
+    
+    def _write_env_file(self, env_vars: Dict[str, str]):
+        """Write all key-value pairs to .env file"""
+        with open(self.env_path, 'w', encoding='utf-8') as f:
+            f.write("# Environment variables for agent skills\n")
+            f.write("# Auto-managed by env_config tool\n\n")
+            for key, value in sorted(env_vars.items()):
+                f.write(f"{key}={value}\n")
+    
+    def _reload_env(self):
+        """Reload environment variables from .env file"""
+        env_vars = self._read_env_file()
+        for key, value in env_vars.items():
+            os.environ[key] = value
+        logger.debug(f"[EnvConfig] Reloaded {len(env_vars)} environment variables")
+    
+    def _refresh_skills(self):
+        """Refresh skills after environment variable changes"""
+        if self.agent_bridge:
+            try:
+                # Reload .env file
+                self._reload_env()
+                
+                # Refresh skills in all agent instances
+                refreshed = self.agent_bridge.refresh_all_skills()
+                logger.info(f"[EnvConfig] Refreshed skills in {refreshed} agent instance(s)")
+                return True
+            except Exception as e:
+                logger.warning(f"[EnvConfig] Failed to refresh skills: {e}")
+                return False
+        return False
+    
+    def execute(self, args: Dict[str, Any]) -> ToolResult:
+        """
+        Execute environment configuration operation
+        
+        :param args: Contains action, key, and value parameters
+        :return: Result of the operation
+        """
+        # Ensure .env file exists on first use
+        self._ensure_env_file()
+        
+        action = args.get("action")
+        key = args.get("key")
+        value = args.get("value")
+        
+        try:
+            if action == "set":
+                if not key or not value:
+                    return ToolResult.fail("Error: 'key' and 'value' are required for 'set' action.")
+                
+                # Read current env vars
+                env_vars = self._read_env_file()
+                
+                # Update the key
+                env_vars[key] = value
+                
+                # Write back to file
+                self._write_env_file(env_vars)
+                
+                # Update current process env
+                os.environ[key] = value
+                
+                logger.info(f"[EnvConfig] Set {key}={self._mask_value(value)}")
+                
+                # Try to refresh skills immediately
+                refreshed = self._refresh_skills()
+                
+                result = {
+                    "message": f"Successfully set {key}",
+                    "key": key,
+                    "value": self._mask_value(value),
+                }
+                
+                if refreshed:
+                    result["note"] = "✅ Skills refreshed automatically - changes are now active"
+                else:
+                    result["note"] = "⚠️ Skills not refreshed - restart agent to load new skills"
+                
+                return ToolResult.success(result)
+            
+            elif action == "get":
+                if not key:
+                    return ToolResult.fail("Error: 'key' is required for 'get' action.")
+                
+                # Check in file first, then in current env
+                env_vars = self._read_env_file()
+                value = env_vars.get(key) or os.getenv(key)
+                
+                # Get description from registry
+                description = API_KEY_REGISTRY.get(key, "未知用途的环境变量")
+                
+                if value is not None:
+                    logger.info(f"[EnvConfig] Got {key}={self._mask_value(value)}")
+                    return ToolResult.success({
+                        "key": key,
+                        "value": self._mask_value(value),
+                        "description": description,
+                        "exists": True
+                    })
+                else:
+                    return ToolResult.success({
+                        "key": key,
+                        "description": description,
+                        "exists": False,
+                        "message": f"Environment variable '{key}' is not set"
+                    })
+            
+            elif action == "list":
+                env_vars = self._read_env_file()
+                
+                # Build detailed variable list with descriptions
+                variables_with_info = {}
+                for key, value in env_vars.items():
+                    variables_with_info[key] = {
+                        "value": self._mask_value(value),
+                        "description": API_KEY_REGISTRY.get(key, "未知用途的环境变量")
+                    }
+                
+                logger.info(f"[EnvConfig] Listed {len(env_vars)} environment variables")
+                
+                if not env_vars:
+                    return ToolResult.success({
+                        "message": "No environment variables configured",
+                        "variables": {},
+                        "note": "常用的 API 密钥可以通过 env_config(action='set', key='KEY_NAME', value='your-key') 来配置"
+                    })
+                
+                return ToolResult.success({
+                    "message": f"Found {len(env_vars)} environment variable(s)",
+                    "variables": variables_with_info
+                })
+            
+            elif action == "delete":
+                if not key:
+                    return ToolResult.fail("Error: 'key' is required for 'delete' action.")
+                
+                # Read current env vars
+                env_vars = self._read_env_file()
+                
+                if key not in env_vars:
+                    return ToolResult.success({
+                        "message": f"Environment variable '{key}' was not set",
+                        "key": key
+                    })
+                
+                # Remove the key
+                del env_vars[key]
+                
+                # Write back to file
+                self._write_env_file(env_vars)
+                
+                # Remove from current process env
+                if key in os.environ:
+                    del os.environ[key]
+                
+                logger.info(f"[EnvConfig] Deleted {key}")
+                
+                # Try to refresh skills immediately
+                refreshed = self._refresh_skills()
+                
+                result = {
+                    "message": f"Successfully deleted {key}",
+                    "key": key,
+                }
+                
+                if refreshed:
+                    result["note"] = "✅ Skills refreshed automatically - changes are now active"
+                else:
+                    result["note"] = "⚠️ Skills not refreshed - restart agent to apply changes"
+                
+                return ToolResult.success(result)
+            
+            else:
+                return ToolResult.fail(f"Error: Unknown action '{action}'. Use 'set', 'get', 'list', or 'delete'.")
+        
+        except Exception as e:
+            logger.error(f"[EnvConfig] Error: {e}", exc_info=True)
+            return ToolResult.fail(f"EnvConfig tool error: {str(e)}")

agent/tools/scheduler/README.md

@@ -0,0 +1,286 @@
+# 定时任务工具 (Scheduler Tool)
+
+## 功能简介
+
+定时任务工具允许 Agent 创建、管理和执行定时任务，支持：
+
+- ⏰ **定时提醒**: 在指定时间发送消息
+- 🔄 **周期性任务**: 按固定间隔或 cron 表达式重复执行
+- 🔧 **动态工具调用**: 定时执行其他工具并发送结果（如搜索新闻、查询天气等）
+- 📋 **任务管理**: 查询、启用、禁用、删除任务
+
+## 安装依赖
+
+```bash
+pip install croniter>=2.0.0
+```
+
+## 使用方法
+
+### 1. 创建定时任务
+
+Agent 可以通过自然语言创建定时任务，支持两种类型：
+
+#### 1.1 静态消息任务
+
+发送预定义的消息：
+
+**示例对话：**
+```
+用户: 每天早上9点提醒我开会
+Agent: [调用 scheduler 工具]
+      action: create
+      name: 每日开会提醒
+      message: 该开会了！
+      schedule_type: cron
+      schedule_value: 0 9 * * *
+```
+
+#### 1.2 动态工具调用任务
+
+定时执行工具并发送结果：
+
+**示例对话：**
+```
+用户: 每天早上8点帮我搜索一下当前新闻
+Agent: [调用 scheduler 工具]
+      action: create
+      name: 每日新闻
+      tool_call:
+        tool_name: bocha_search
+        tool_params:
+          query: 今日新闻
+        result_prefix: 📰 今日新闻播报
+      schedule_type: cron
+      schedule_value: 0 8 * * *
+```
+
+**工具调用参数说明：**
+- `tool_name`: 要调用的工具名称（如 `bocha_search`、`web_fetch` 等）
+- `tool_params`: 工具的参数（字典格式）
+- `result_prefix`: 可选，在结果前添加的前缀文本
+
+### 2. 支持的调度类型
+
+#### Cron 表达式 (`cron`)
+使用标准 cron 表达式：
+
+```
+0 9 * * *      # 每天 9:00
+0 */2 * * *    # 每 2 小时
+30 8 * * 1-5   # 工作日 8:30
+0 0 1 * *      # 每月 1 号
+```
+
+#### 固定间隔 (`interval`)
+以秒为单位的间隔：
+
+```
+3600           # 每小时
+86400          # 每天
+1800           # 每 30 分钟
+```
+
+#### 一次性任务 (`once`)
+指定具体时间（ISO 格式）：
+
+```
+2024-12-25T09:00:00
+2024-12-31T23:59:59
+```
+
+### 3. 查询任务列表
+
+```
+用户: 查看我的定时任务
+Agent: [调用 scheduler 工具]
+      action: list
+```
+
+### 4. 查看任务详情
+
+```
+用户: 查看任务 abc123 的详情
+Agent: [调用 scheduler 工具]
+      action: get
+      task_id: abc123
+```
+
+### 5. 删除任务
+
+```
+用户: 删除任务 abc123
+Agent: [调用 scheduler 工具]
+      action: delete
+      task_id: abc123
+```
+
+### 6. 启用/禁用任务
+
+```
+用户: 暂停任务 abc123
+Agent: [调用 scheduler 工具]
+      action: disable
+      task_id: abc123
+
+用户: 恢复任务 abc123
+Agent: [调用 scheduler 工具]
+      action: enable
+      task_id: abc123
+```
+
+## 任务存储
+
+任务保存在 JSON 文件中：
+```
+~/cow/scheduler/tasks.json
+```
+
+任务数据结构：
+
+**静态消息任务：**
+```json
+{
+  "id": "abc123",
+  "name": "每日提醒",
+  "enabled": true,
+  "created_at": "2024-01-01T10:00:00",
+  "updated_at": "2024-01-01T10:00:00",
+  "schedule": {
+    "type": "cron",
+    "expression": "0 9 * * *"
+  },
+  "action": {
+    "type": "send_message",
+    "content": "该开会了！",
+    "receiver": "wxid_xxx",
+    "receiver_name": "张三",
+    "is_group": false,
+    "channel_type": "wechat"
+  },
+  "next_run_at": "2024-01-02T09:00:00",
+  "last_run_at": "2024-01-01T09:00:00"
+}
+```
+
+**动态工具调用任务：**
+```json
+{
+  "id": "def456",
+  "name": "每日新闻",
+  "enabled": true,
+  "created_at": "2024-01-01T10:00:00",
+  "updated_at": "2024-01-01T10:00:00",
+  "schedule": {
+    "type": "cron",
+    "expression": "0 8 * * *"
+  },
+  "action": {
+    "type": "tool_call",
+    "tool_name": "bocha_search",
+    "tool_params": {
+      "query": "今日新闻"
+    },
+    "result_prefix": "📰 今日新闻播报",
+    "receiver": "wxid_xxx",
+    "receiver_name": "张三",
+    "is_group": false,
+    "channel_type": "wechat"
+  },
+  "next_run_at": "2024-01-02T08:00:00"
+}
+```
+
+## 后台服务
+
+定时任务由后台服务 `SchedulerService` 管理：
+
+- 每 30 秒检查一次到期任务
+- 自动执行到期任务
+- 计算下次执行时间
+- 记录执行历史和错误
+
+服务在 Agent 初始化时自动启动，无需手动配置。
+
+## 接收者确定
+
+定时任务会发送给**创建任务时的对话对象**：
+
+- 如果在私聊中创建，发送给该用户
+- 如果在群聊中创建，发送到该群
+- 接收者信息在创建时自动保存
+
+## 常见用例
+
+### 1. 每日提醒（静态消息）
+```
+用户: 每天早上8点提醒我吃药
+Agent: ✅ 定时任务创建成功
+       任务ID: a1b2c3d4
+       调度: 每天 8:00
+       消息: 该吃药了！
+```
+
+### 2. 工作日提醒（静态消息）
+```
+用户: 工作日下午6点提醒我下班
+Agent: [创建 cron: 0 18 * * 1-5]
+       消息: 该下班了！
+```
+
+### 3. 倒计时提醒（静态消息）
+```
+用户: 1小时后提醒我
+Agent: [创建 interval: 3600]
+```
+
+### 4. 每日新闻推送（动态工具调用）
+```
+用户: 每天早上8点帮我搜索一下当前新闻
+Agent: ✅ 定时任务创建成功
+       任务ID: news001
+       调度: 每天 8:00
+       工具: bocha_search(query='今日新闻')
+       前缀: 📰 今日新闻播报
+```
+
+### 5. 定时天气查询（动态工具调用）
+```
+用户: 每天早上7点查询今天的天气
+Agent: [创建 cron: 0 7 * * *]
+       工具: bocha_search(query='今日天气')
+       前缀: 🌤️ 今日天气预报
+```
+
+### 6. 周报提醒（动态工具调用）
+```
+用户: 每周五下午5点搜索本周热点
+Agent: [创建 cron: 0 17 * * 5]
+       工具: bocha_search(query='本周热点新闻')
+       前缀: 📊 本周热点回顾
+```
+
+### 4. 特定日期提醒
+```
+用户: 12月25日早上9点提醒我圣诞快乐
+Agent: [创建 once: 2024-12-25T09:00:00]
+```
+
+## 注意事项
+
+1. **时区**: 使用系统本地时区
+2. **精度**: 检查间隔为 30 秒，实际执行可能有 ±30 秒误差
+3. **持久化**: 任务保存在文件中，重启后自动恢复
+4. **一次性任务**: 执行后自动禁用，不会删除（可手动删除）
+5. **错误处理**: 执行失败会记录错误，不影响其他任务
+
+## 技术实现
+
+- **TaskStore**: 任务持久化存储
+- **SchedulerService**: 后台调度服务
+- **SchedulerTool**: Agent 工具接口
+- **Integration**: 与 AgentBridge 集成
+
+## 依赖
+
+- `croniter`: Cron 表达式解析（轻量级，仅 ~50KB）

agent/tools/scheduler/__init__.py

@@ -0,0 +1,7 @@
+"""
+Scheduler tool for managing scheduled tasks
+"""
+
+from .scheduler_tool import SchedulerTool
+
+__all__ = ["SchedulerTool"]

agent/tools/scheduler/integration.py

@@ -0,0 +1,239 @@
+"""
+Integration module for scheduler with AgentBridge
+"""
+
+import os
+from typing import Optional
+from config import conf
+from common.log import logger
+from bridge.context import Context, ContextType
+from bridge.reply import Reply, ReplyType
+
+# Global scheduler service instance
+_scheduler_service = None
+_task_store = None
+
+
+def init_scheduler(agent_bridge) -> bool:
+    """
+    Initialize scheduler service
+    
+    Args:
+        agent_bridge: AgentBridge instance
+        
+    Returns:
+        True if initialized successfully
+    """
+    global _scheduler_service, _task_store
+    
+    try:
+        from agent.tools.scheduler.task_store import TaskStore
+        from agent.tools.scheduler.scheduler_service import SchedulerService
+        
+        # Get workspace from config
+        workspace_root = os.path.expanduser(conf().get("agent_workspace", "~/cow"))
+        store_path = os.path.join(workspace_root, "scheduler", "tasks.json")
+        
+        # Create task store
+        _task_store = TaskStore(store_path)
+        logger.info(f"[Scheduler] Task store initialized: {store_path}")
+        
+        # Create execute callback
+        def execute_task_callback(task: dict):
+            """Callback to execute a scheduled task"""
+            try:
+                action = task.get("action", {})
+                action_type = action.get("type")
+                
+                if action_type == "send_message":
+                    _execute_send_message(task, agent_bridge)
+                elif action_type == "tool_call":
+                    _execute_tool_call(task, agent_bridge)
+                else:
+                    logger.warning(f"[Scheduler] Unknown action type: {action_type}")
+            except Exception as e:
+                logger.error(f"[Scheduler] Error executing task {task.get('id')}: {e}")
+        
+        # Create scheduler service
+        _scheduler_service = SchedulerService(_task_store, execute_task_callback)
+        _scheduler_service.start()
+        
+        logger.info("[Scheduler] Scheduler service initialized and started")
+        return True
+        
+    except Exception as e:
+        logger.error(f"[Scheduler] Failed to initialize scheduler: {e}")
+        return False
+
+
+def get_task_store():
+    """Get the global task store instance"""
+    return _task_store
+
+
+def get_scheduler_service():
+    """Get the global scheduler service instance"""
+    return _scheduler_service
+
+
+def _execute_send_message(task: dict, agent_bridge):
+    """
+    Execute a send_message action
+    
+    Args:
+        task: Task dictionary
+        agent_bridge: AgentBridge instance
+    """
+    try:
+        action = task.get("action", {})
+        content = action.get("content", "")
+        receiver = action.get("receiver")
+        is_group = action.get("is_group", False)
+        channel_type = action.get("channel_type", "unknown")
+        
+        if not receiver:
+            logger.error(f"[Scheduler] Task {task['id']}: No receiver specified")
+            return
+        
+        # Create context for sending message
+        context = Context(ContextType.TEXT, content)
+        context["receiver"] = receiver
+        context["isgroup"] = is_group
+        context["session_id"] = receiver
+        
+        # For web channel, generate a virtual request_id
+        if channel_type == "web":
+            import uuid
+            request_id = f"scheduler_{task['id']}_{uuid.uuid4().hex[:8]}"
+            context["request_id"] = request_id
+            logger.debug(f"[Scheduler] Generated request_id for web channel: {request_id}")
+        
+        # Create reply
+        reply = Reply(ReplyType.TEXT, content)
+        
+        # Get channel and send
+        from channel.channel_factory import create_channel
+        
+        try:
+            channel = create_channel(channel_type)
+            if channel:
+                # For web channel, register the request_id to session mapping
+                if channel_type == "web" and hasattr(channel, 'request_to_session'):
+                    channel.request_to_session[request_id] = receiver
+                    logger.debug(f"[Scheduler] Registered request_id {request_id} -> session {receiver}")
+                
+                channel.send(reply, context)
+                logger.info(f"[Scheduler] Task {task['id']} executed: sent message to {receiver}")
+            else:
+                logger.error(f"[Scheduler] Failed to create channel: {channel_type}")
+        except Exception as e:
+            logger.error(f"[Scheduler] Failed to send message: {e}")
+            
+    except Exception as e:
+        logger.error(f"[Scheduler] Error in _execute_send_message: {e}")
+
+
+def _execute_tool_call(task: dict, agent_bridge):
+    """
+    Execute a tool_call action
+    
+    Args:
+        task: Task dictionary
+        agent_bridge: AgentBridge instance
+    """
+    try:
+        action = task.get("action", {})
+        tool_name = action.get("tool_name")
+        tool_params = action.get("tool_params", {})
+        result_prefix = action.get("result_prefix", "")
+        receiver = action.get("receiver")
+        is_group = action.get("is_group", False)
+        channel_type = action.get("channel_type", "unknown")
+        
+        if not tool_name:
+            logger.error(f"[Scheduler] Task {task['id']}: No tool_name specified")
+            return
+        
+        if not receiver:
+            logger.error(f"[Scheduler] Task {task['id']}: No receiver specified")
+            return
+        
+        # Get tool manager and create tool instance
+        from agent.tools.tool_manager import ToolManager
+        tool_manager = ToolManager()
+        tool = tool_manager.create_tool(tool_name)
+        
+        if not tool:
+            logger.error(f"[Scheduler] Task {task['id']}: Tool '{tool_name}' not found")
+            return
+        
+        # Execute tool
+        logger.info(f"[Scheduler] Task {task['id']}: Executing tool '{tool_name}' with params {tool_params}")
+        result = tool.execute(tool_params)
+        
+        # Get result content
+        if hasattr(result, 'result'):
+            content = result.result
+        else:
+            content = str(result)
+        
+        # Add prefix if specified
+        if result_prefix:
+            content = f"{result_prefix}\n\n{content}"
+        
+        # Send result as message
+        context = Context(ContextType.TEXT, content)
+        context["receiver"] = receiver
+        context["isgroup"] = is_group
+        context["session_id"] = receiver
+        
+        # For web channel, generate a virtual request_id
+        if channel_type == "web":
+            import uuid
+            request_id = f"scheduler_{task['id']}_{uuid.uuid4().hex[:8]}"
+            context["request_id"] = request_id
+            logger.debug(f"[Scheduler] Generated request_id for web channel: {request_id}")
+        
+        reply = Reply(ReplyType.TEXT, content)
+        
+        # Get channel and send
+        from channel.channel_factory import create_channel
+        
+        try:
+            channel = create_channel(channel_type)
+            if channel:
+                # For web channel, register the request_id to session mapping
+                if channel_type == "web" and hasattr(channel, 'request_to_session'):
+                    channel.request_to_session[request_id] = receiver
+                    logger.debug(f"[Scheduler] Registered request_id {request_id} -> session {receiver}")
+                
+                channel.send(reply, context)
+                logger.info(f"[Scheduler] Task {task['id']} executed: sent tool result to {receiver}")
+            else:
+                logger.error(f"[Scheduler] Failed to create channel: {channel_type}")
+        except Exception as e:
+            logger.error(f"[Scheduler] Failed to send tool result: {e}")
+            
+    except Exception as e:
+        logger.error(f"[Scheduler] Error in _execute_tool_call: {e}")
+
+
+def attach_scheduler_to_tool(tool, context: Context = None):
+    """
+    Attach scheduler components to a SchedulerTool instance
+    
+    Args:
+        tool: SchedulerTool instance
+        context: Current context (optional)
+    """
+    if _task_store:
+        tool.task_store = _task_store
+    
+    if context:
+        tool.current_context = context
+        
+        # Also set channel_type from config
+        channel_type = conf().get("channel_type", "unknown")
+        if not tool.config:
+            tool.config = {}
+        tool.config["channel_type"] = channel_type

agent/tools/scheduler/scheduler_service.py

@@ -0,0 +1,192 @@
+"""
+Background scheduler service for executing scheduled tasks
+"""
+
+import time
+import threading
+from datetime import datetime, timedelta
+from typing import Callable, Optional
+from croniter import croniter
+from common.log import logger
+
+
+class SchedulerService:
+    """
+    Background service that executes scheduled tasks
+    """
+    
+    def __init__(self, task_store, execute_callback: Callable):
+        """
+        Initialize scheduler service
+        
+        Args:
+            task_store: TaskStore instance
+            execute_callback: Function to call when executing a task
+        """
+        self.task_store = task_store
+        self.execute_callback = execute_callback
+        self.running = False
+        self.thread = None
+        self._lock = threading.Lock()
+    
+    def start(self):
+        """Start the scheduler service"""
+        with self._lock:
+            if self.running:
+                logger.warning("[Scheduler] Service already running")
+                return
+            
+            self.running = True
+            self.thread = threading.Thread(target=self._run_loop, daemon=True)
+            self.thread.start()
+            logger.info("[Scheduler] Service started")
+    
+    def stop(self):
+        """Stop the scheduler service"""
+        with self._lock:
+            if not self.running:
+                return
+            
+            self.running = False
+            if self.thread:
+                self.thread.join(timeout=5)
+            logger.info("[Scheduler] Service stopped")
+    
+    def _run_loop(self):
+        """Main scheduler loop"""
+        logger.info("[Scheduler] Scheduler loop started")
+        
+        while self.running:
+            try:
+                self._check_and_execute_tasks()
+            except Exception as e:
+                logger.error(f"[Scheduler] Error in scheduler loop: {e}")
+            
+            # Sleep for 30 seconds between checks
+            time.sleep(30)
+    
+    def _check_and_execute_tasks(self):
+        """Check for due tasks and execute them"""
+        now = datetime.now()
+        tasks = self.task_store.list_tasks(enabled_only=True)
+        
+        for task in tasks:
+            try:
+                # Check if task is due
+                if self._is_task_due(task, now):
+                    logger.info(f"[Scheduler] Executing task: {task['id']} - {task['name']}")
+                    self._execute_task(task)
+                    
+                    # Update next run time
+                    next_run = self._calculate_next_run(task, now)
+                    if next_run:
+                        self.task_store.update_task(task['id'], {
+                            "next_run_at": next_run.isoformat(),
+                            "last_run_at": now.isoformat()
+                        })
+                    else:
+                        # One-time task, disable it
+                        self.task_store.update_task(task['id'], {
+                            "enabled": False,
+                            "last_run_at": now.isoformat()
+                        })
+                        logger.info(f"[Scheduler] One-time task completed and disabled: {task['id']}")
+            except Exception as e:
+                logger.error(f"[Scheduler] Error processing task {task.get('id')}: {e}")
+    
+    def _is_task_due(self, task: dict, now: datetime) -> bool:
+        """
+        Check if a task is due to run
+        
+        Args:
+            task: Task dictionary
+            now: Current datetime
+            
+        Returns:
+            True if task should run now
+        """
+        next_run_str = task.get("next_run_at")
+        if not next_run_str:
+            # Calculate initial next_run_at
+            next_run = self._calculate_next_run(task, now)
+            if next_run:
+                self.task_store.update_task(task['id'], {
+                    "next_run_at": next_run.isoformat()
+                })
+                return False
+            return False
+        
+        try:
+            next_run = datetime.fromisoformat(next_run_str)
+            return now >= next_run
+        except:
+            return False
+    
+    def _calculate_next_run(self, task: dict, from_time: datetime) -> Optional[datetime]:
+        """
+        Calculate next run time for a task
+        
+        Args:
+            task: Task dictionary
+            from_time: Calculate from this time
+            
+        Returns:
+            Next run datetime or None for one-time tasks
+        """
+        schedule = task.get("schedule", {})
+        schedule_type = schedule.get("type")
+        
+        if schedule_type == "cron":
+            # Cron expression
+            expression = schedule.get("expression")
+            if not expression:
+                return None
+            
+            try:
+                cron = croniter(expression, from_time)
+                return cron.get_next(datetime)
+            except Exception as e:
+                logger.error(f"[Scheduler] Invalid cron expression '{expression}': {e}")
+                return None
+        
+        elif schedule_type == "interval":
+            # Interval in seconds
+            seconds = schedule.get("seconds", 0)
+            if seconds <= 0:
+                return None
+            return from_time + timedelta(seconds=seconds)
+        
+        elif schedule_type == "once":
+            # One-time task at specific time
+            run_at_str = schedule.get("run_at")
+            if not run_at_str:
+                return None
+            
+            try:
+                run_at = datetime.fromisoformat(run_at_str)
+                # Only return if in the future
+                if run_at > from_time:
+                    return run_at
+            except:
+                pass
+            return None
+        
+        return None
+    
+    def _execute_task(self, task: dict):
+        """
+        Execute a task
+        
+        Args:
+            task: Task dictionary
+        """
+        try:
+            # Call the execute callback
+            self.execute_callback(task)
+        except Exception as e:
+            logger.error(f"[Scheduler] Error executing task {task['id']}: {e}")
+            # Update task with error
+            self.task_store.update_task(task['id'], {
+                "last_error": str(e),
+                "last_error_at": datetime.now().isoformat()
+            })

agent/tools/scheduler/scheduler_tool.py

@@ -0,0 +1,439 @@
+"""
+Scheduler tool for creating and managing scheduled tasks
+"""
+
+import uuid
+from datetime import datetime
+from typing import Any, Dict, Optional
+from croniter import croniter
+
+from agent.tools.base_tool import BaseTool, ToolResult
+from bridge.context import Context, ContextType
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+
+
+class SchedulerTool(BaseTool):
+    """
+    Tool for managing scheduled tasks (reminders, notifications, etc.)
+    """
+    
+    name: str = "scheduler"
+    description: str = (
+        "创建、查询和管理定时任务。支持两种任务类型：\n"
+        "1. 静态消息任务：定时发送预定义的消息\n"
+        "2. 动态工具任务：定时执行工具调用并发送结果（如搜索新闻、查询天气等）\n\n"
+        "使用方法：\n"
+        "- 创建静态消息任务：action='create', name='任务名', message='消息内容', schedule_type='interval'/'cron'/'once', schedule_value='间隔秒数/cron表达式/时间'\n"
+        "- 创建动态工具任务：action='create', name='任务名', tool_call={'tool_name': '工具名', 'tool_params': {...}, 'result_prefix': '前缀'}, schedule_type='interval'/'cron'/'once', schedule_value='值'\n"
+        "- 查询列表：action='list'\n"
+        "- 查看详情：action='get', task_id='任务ID'\n"
+        "- 删除任务：action='delete', task_id='任务ID'\n"
+        "- 启用任务：action='enable', task_id='任务ID'\n"
+        "- 禁用任务：action='disable', task_id='任务ID'\n\n"
+        "调度类型说明：\n"
+        "- interval: 固定间隔秒数（如3600表示每小时）\n"
+        "- cron: cron表达式（如'0 9 * * *'表示每天9点，'*/10 * * * *'表示每10分钟）\n"
+        "- once: 一次性任务，ISO时间格式（如'2024-12-25T09:00:00'）\n\n"
+        "示例：每天早上8点搜索新闻\n"
+        "action='create', name='每日新闻', tool_call={'tool_name': 'bocha_search', 'tool_params': {'query': '今日新闻'}, 'result_prefix': '📰 今日新闻播报'}, schedule_type='cron', schedule_value='0 8 * * *'"
+    )
+    params: dict = {
+        "type": "object",
+        "properties": {
+            "action": {
+                "type": "string",
+                "enum": ["create", "list", "get", "delete", "enable", "disable"],
+                "description": "操作类型: create(创建), list(列表), get(查询), delete(删除), enable(启用), disable(禁用)"
+            },
+            "task_id": {
+                "type": "string",
+                "description": "任务ID (用于 get/delete/enable/disable 操作)"
+            },
+            "name": {
+                "type": "string",
+                "description": "任务名称 (用于 create 操作)"
+            },
+            "message": {
+                "type": "string",
+                "description": "要发送的静态消息内容 (用于 create 操作，与tool_call二选一)"
+            },
+            "tool_call": {
+                "type": "object",
+                "description": "要执行的工具调用 (用于 create 操作，与message二选一)",
+                "properties": {
+                    "tool_name": {
+                        "type": "string",
+                        "description": "工具名称，如 'bocha_search'"
+                    },
+                    "tool_params": {
+                        "type": "object",
+                        "description": "工具参数"
+                    },
+                    "result_prefix": {
+                        "type": "string",
+                        "description": "结果前缀，如 '今日新闻：'"
+                    }
+                },
+                "required": ["tool_name"]
+            },
+            "schedule_type": {
+                "type": "string",
+                "enum": ["cron", "interval", "once"],
+                "description": "调度类型 (用于 create 操作): cron(cron表达式), interval(固定间隔秒数), once(一次性)"
+            },
+            "schedule_value": {
+                "type": "string",
+                "description": (
+                    "调度值 (用于 create 操作):\n"
+                    "- cron类型: cron表达式，如 '0 9 * * *' (每天9点)，'*/10 * * * *' (每10分钟)\n"
+                    "- interval类型: 间隔秒数，如 '3600' (每小时)，'10' (每10秒)\n"
+                    "- once类型: ISO时间，如 '2024-12-25T09:00:00'"
+                )
+            }
+        },
+        "required": ["action"]
+    }
+    
+    def __init__(self, config: dict = None):
+        super().__init__()
+        self.config = config or {}
+        
+        # Will be set by agent bridge
+        self.task_store = None
+        self.current_context = None
+    
+    def execute(self, params: dict) -> ToolResult:
+        """
+        Execute scheduler operations
+        
+        Args:
+            params: Dictionary containing:
+                - action: Operation type (create/list/get/delete/enable/disable)
+                - Other parameters depending on action
+            
+        Returns:
+            ToolResult object
+        """
+        # Extract parameters
+        action = params.get("action")
+        kwargs = params
+        
+        if not self.task_store:
+            return ToolResult.fail("错误: 定时任务系统未初始化")
+        
+        try:
+            if action == "create":
+                result = self._create_task(**kwargs)
+                return ToolResult.success(result)
+            elif action == "list":
+                result = self._list_tasks(**kwargs)
+                return ToolResult.success(result)
+            elif action == "get":
+                result = self._get_task(**kwargs)
+                return ToolResult.success(result)
+            elif action == "delete":
+                result = self._delete_task(**kwargs)
+                return ToolResult.success(result)
+            elif action == "enable":
+                result = self._enable_task(**kwargs)
+                return ToolResult.success(result)
+            elif action == "disable":
+                result = self._disable_task(**kwargs)
+                return ToolResult.success(result)
+            else:
+                return ToolResult.fail(f"未知操作: {action}")
+        except Exception as e:
+            logger.error(f"[SchedulerTool] Error: {e}")
+            return ToolResult.fail(f"操作失败: {str(e)}")
+    
+    def _create_task(self, **kwargs) -> str:
+        """Create a new scheduled task"""
+        name = kwargs.get("name")
+        message = kwargs.get("message")
+        tool_call = kwargs.get("tool_call")
+        schedule_type = kwargs.get("schedule_type")
+        schedule_value = kwargs.get("schedule_value")
+        
+        # Validate required fields
+        if not name:
+            return "错误: 缺少任务名称 (name)"
+        if not message and not tool_call:
+            return "错误: 必须提供 message 或 tool_call 之一"
+        if message and tool_call:
+            return "错误: message 和 tool_call 不能同时提供，请选择其一"
+        if not schedule_type:
+            return "错误: 缺少调度类型 (schedule_type)"
+        if not schedule_value:
+            return "错误: 缺少调度值 (schedule_value)"
+        
+        # Validate schedule
+        schedule = self._parse_schedule(schedule_type, schedule_value)
+        if not schedule:
+            return f"错误: 无效的调度配置 - type: {schedule_type}, value: {schedule_value}"
+        
+        # Get context info for receiver
+        if not self.current_context:
+            return "错误: 无法获取当前对话上下文"
+        
+        context = self.current_context
+        
+        # Create task
+        task_id = str(uuid.uuid4())[:8]
+        
+        # Build action based on message or tool_call
+        if message:
+            action = {
+                "type": "send_message",
+                "content": message,
+                "receiver": context.get("receiver"),
+                "receiver_name": self._get_receiver_name(context),
+                "is_group": context.get("isgroup", False),
+                "channel_type": self.config.get("channel_type", "unknown")
+            }
+        else:  # tool_call
+            action = {
+                "type": "tool_call",
+                "tool_name": tool_call.get("tool_name"),
+                "tool_params": tool_call.get("tool_params", {}),
+                "result_prefix": tool_call.get("result_prefix", ""),
+                "receiver": context.get("receiver"),
+                "receiver_name": self._get_receiver_name(context),
+                "is_group": context.get("isgroup", False),
+                "channel_type": self.config.get("channel_type", "unknown")
+            }
+        
+        task = {
+            "id": task_id,
+            "name": name,
+            "enabled": True,
+            "created_at": datetime.now().isoformat(),
+            "updated_at": datetime.now().isoformat(),
+            "schedule": schedule,
+            "action": action
+        }
+        
+        # Calculate initial next_run_at
+        next_run = self._calculate_next_run(task)
+        if next_run:
+            task["next_run_at"] = next_run.isoformat()
+        
+        # Save task
+        self.task_store.add_task(task)
+        
+        # Format response
+        schedule_desc = self._format_schedule_description(schedule)
+        receiver_desc = task["action"]["receiver_name"] or task["action"]["receiver"]
+        
+        if message:
+            content_desc = f"💬 消息: {message}"
+        else:
+            tool_name = tool_call.get("tool_name")
+            tool_params_str = str(tool_call.get("tool_params", {}))
+            prefix = tool_call.get("result_prefix", "")
+            content_desc = f"🔧 工具调用: {tool_name}({tool_params_str})"
+            if prefix:
+                content_desc += f"\n📝 结果前缀: {prefix}"
+        
+        return (
+            f"✅ 定时任务创建成功\n\n"
+            f"📋 任务ID: {task_id}\n"
+            f"📝 名称: {name}\n"
+            f"⏰ 调度: {schedule_desc}\n"
+            f"👤 接收者: {receiver_desc}\n"
+            f"{content_desc}\n"
+            f"🕐 下次执行: {next_run.strftime('%Y-%m-%d %H:%M:%S') if next_run else '未知'}"
+        )
+    
+    def _list_tasks(self, **kwargs) -> str:
+        """List all tasks"""
+        tasks = self.task_store.list_tasks()
+        
+        if not tasks:
+            return "📋 暂无定时任务"
+        
+        lines = [f"📋 定时任务列表 (共 {len(tasks)} 个)\n"]
+        
+        for task in tasks:
+            status = "✅" if task.get("enabled", True) else "❌"
+            schedule_desc = self._format_schedule_description(task.get("schedule", {}))
+            next_run = task.get("next_run_at")
+            next_run_str = datetime.fromisoformat(next_run).strftime('%m-%d %H:%M') if next_run else "未知"
+            
+            lines.append(
+                f"{status} [{task['id']}] {task['name']}\n"
+                f"   ⏰ {schedule_desc} | 下次: {next_run_str}"
+            )
+        
+        return "\n".join(lines)
+    
+    def _get_task(self, **kwargs) -> str:
+        """Get task details"""
+        task_id = kwargs.get("task_id")
+        if not task_id:
+            return "错误: 缺少任务ID (task_id)"
+        
+        task = self.task_store.get_task(task_id)
+        if not task:
+            return f"错误: 任务 '{task_id}' 不存在"
+        
+        status = "启用" if task.get("enabled", True) else "禁用"
+        schedule_desc = self._format_schedule_description(task.get("schedule", {}))
+        action = task.get("action", {})
+        next_run = task.get("next_run_at")
+        next_run_str = datetime.fromisoformat(next_run).strftime('%Y-%m-%d %H:%M:%S') if next_run else "未知"
+        last_run = task.get("last_run_at")
+        last_run_str = datetime.fromisoformat(last_run).strftime('%Y-%m-%d %H:%M:%S') if last_run else "从未执行"
+        
+        return (
+            f"📋 任务详情\n\n"
+            f"ID: {task['id']}\n"
+            f"名称: {task['name']}\n"
+            f"状态: {status}\n"
+            f"调度: {schedule_desc}\n"
+            f"接收者: {action.get('receiver_name', action.get('receiver'))}\n"
+            f"消息: {action.get('content')}\n"
+            f"下次执行: {next_run_str}\n"
+            f"上次执行: {last_run_str}\n"
+            f"创建时间: {datetime.fromisoformat(task['created_at']).strftime('%Y-%m-%d %H:%M:%S')}"
+        )
+    
+    def _delete_task(self, **kwargs) -> str:
+        """Delete a task"""
+        task_id = kwargs.get("task_id")
+        if not task_id:
+            return "错误: 缺少任务ID (task_id)"
+        
+        task = self.task_store.get_task(task_id)
+        if not task:
+            return f"错误: 任务 '{task_id}' 不存在"
+        
+        self.task_store.delete_task(task_id)
+        return f"✅ 任务 '{task['name']}' ({task_id}) 已删除"
+    
+    def _enable_task(self, **kwargs) -> str:
+        """Enable a task"""
+        task_id = kwargs.get("task_id")
+        if not task_id:
+            return "错误: 缺少任务ID (task_id)"
+        
+        task = self.task_store.get_task(task_id)
+        if not task:
+            return f"错误: 任务 '{task_id}' 不存在"
+        
+        self.task_store.enable_task(task_id, True)
+        return f"✅ 任务 '{task['name']}' ({task_id}) 已启用"
+    
+    def _disable_task(self, **kwargs) -> str:
+        """Disable a task"""
+        task_id = kwargs.get("task_id")
+        if not task_id:
+            return "错误: 缺少任务ID (task_id)"
+        
+        task = self.task_store.get_task(task_id)
+        if not task:
+            return f"错误: 任务 '{task_id}' 不存在"
+        
+        self.task_store.enable_task(task_id, False)
+        return f"✅ 任务 '{task['name']}' ({task_id}) 已禁用"
+    
+    def _parse_schedule(self, schedule_type: str, schedule_value: str) -> Optional[dict]:
+        """Parse and validate schedule configuration"""
+        try:
+            if schedule_type == "cron":
+                # Validate cron expression
+                croniter(schedule_value)
+                return {"type": "cron", "expression": schedule_value}
+            
+            elif schedule_type == "interval":
+                # Parse interval in seconds
+                seconds = int(schedule_value)
+                if seconds <= 0:
+                    return None
+                return {"type": "interval", "seconds": seconds}
+            
+            elif schedule_type == "once":
+                # Parse datetime
+                datetime.fromisoformat(schedule_value)
+                return {"type": "once", "run_at": schedule_value}
+            
+        except Exception as e:
+            logger.error(f"[SchedulerTool] Invalid schedule: {e}")
+            return None
+        
+        return None
+    
+    def _calculate_next_run(self, task: dict) -> Optional[datetime]:
+        """Calculate next run time for a task"""
+        schedule = task.get("schedule", {})
+        schedule_type = schedule.get("type")
+        now = datetime.now()
+        
+        if schedule_type == "cron":
+            expression = schedule.get("expression")
+            cron = croniter(expression, now)
+            return cron.get_next(datetime)
+        
+        elif schedule_type == "interval":
+            seconds = schedule.get("seconds", 0)
+            from datetime import timedelta
+            return now + timedelta(seconds=seconds)
+        
+        elif schedule_type == "once":
+            run_at_str = schedule.get("run_at")
+            return datetime.fromisoformat(run_at_str)
+        
+        return None
+    
+    def _format_schedule_description(self, schedule: dict) -> str:
+        """Format schedule as human-readable description"""
+        schedule_type = schedule.get("type")
+        
+        if schedule_type == "cron":
+            expr = schedule.get("expression", "")
+            # Try to provide friendly description
+            if expr == "0 9 * * *":
+                return "每天 9:00"
+            elif expr == "0 */1 * * *":
+                return "每小时"
+            elif expr == "*/30 * * * *":
+                return "每30分钟"
+            else:
+                return f"Cron: {expr}"
+        
+        elif schedule_type == "interval":
+            seconds = schedule.get("seconds", 0)
+            if seconds >= 86400:
+                days = seconds // 86400
+                return f"每 {days} 天"
+            elif seconds >= 3600:
+                hours = seconds // 3600
+                return f"每 {hours} 小时"
+            elif seconds >= 60:
+                minutes = seconds // 60
+                return f"每 {minutes} 分钟"
+            else:
+                return f"每 {seconds} 秒"
+        
+        elif schedule_type == "once":
+            run_at = schedule.get("run_at", "")
+            try:
+                dt = datetime.fromisoformat(run_at)
+                return f"一次性 ({dt.strftime('%Y-%m-%d %H:%M')})"
+            except:
+                return "一次性"
+        
+        return "未知"
+    
+    def _get_receiver_name(self, context: Context) -> str:
+        """Get receiver name from context"""
+        try:
+            msg = context.get("msg")
+            if msg:
+                if context.get("isgroup"):
+                    return msg.other_user_nickname or "群聊"
+                else:
+                    return msg.from_user_nickname or "用户"
+        except:
+            pass
+        return "未知"

agent/tools/scheduler/task_store.py

@@ -0,0 +1,200 @@
+"""
+Task storage management for scheduler
+"""
+
+import json
+import os
+import threading
+from datetime import datetime
+from typing import Dict, List, Optional
+from pathlib import Path
+
+
+class TaskStore:
+    """
+    Manages persistent storage of scheduled tasks
+    """
+    
+    def __init__(self, store_path: str = None):
+        """
+        Initialize task store
+        
+        Args:
+            store_path: Path to tasks.json file. Defaults to ~/cow/scheduler/tasks.json
+        """
+        if store_path is None:
+            # Default to ~/cow/scheduler/tasks.json
+            home = os.path.expanduser("~")
+            store_path = os.path.join(home, "cow", "scheduler", "tasks.json")
+        
+        self.store_path = store_path
+        self.lock = threading.Lock()
+        self._ensure_store_dir()
+    
+    def _ensure_store_dir(self):
+        """Ensure the storage directory exists"""
+        store_dir = os.path.dirname(self.store_path)
+        os.makedirs(store_dir, exist_ok=True)
+    
+    def load_tasks(self) -> Dict[str, dict]:
+        """
+        Load all tasks from storage
+        
+        Returns:
+            Dictionary of task_id -> task_data
+        """
+        with self.lock:
+            if not os.path.exists(self.store_path):
+                return {}
+            
+            try:
+                with open(self.store_path, 'r', encoding='utf-8') as f:
+                    data = json.load(f)
+                    return data.get("tasks", {})
+            except Exception as e:
+                print(f"Error loading tasks: {e}")
+                return {}
+    
+    def save_tasks(self, tasks: Dict[str, dict]):
+        """
+        Save all tasks to storage
+        
+        Args:
+            tasks: Dictionary of task_id -> task_data
+        """
+        with self.lock:
+            try:
+                # Create backup
+                if os.path.exists(self.store_path):
+                    backup_path = f"{self.store_path}.bak"
+                    try:
+                        with open(self.store_path, 'r') as src:
+                            with open(backup_path, 'w') as dst:
+                                dst.write(src.read())
+                    except:
+                        pass
+                
+                # Save tasks
+                data = {
+                    "version": 1,
+                    "updated_at": datetime.now().isoformat(),
+                    "tasks": tasks
+                }
+                
+                with open(self.store_path, 'w', encoding='utf-8') as f:
+                    json.dump(data, f, ensure_ascii=False, indent=2)
+            except Exception as e:
+                print(f"Error saving tasks: {e}")
+                raise
+    
+    def add_task(self, task: dict) -> bool:
+        """
+        Add a new task
+        
+        Args:
+            task: Task data dictionary
+            
+        Returns:
+            True if successful
+        """
+        tasks = self.load_tasks()
+        task_id = task.get("id")
+        
+        if not task_id:
+            raise ValueError("Task must have an 'id' field")
+        
+        if task_id in tasks:
+            raise ValueError(f"Task with id '{task_id}' already exists")
+        
+        tasks[task_id] = task
+        self.save_tasks(tasks)
+        return True
+    
+    def update_task(self, task_id: str, updates: dict) -> bool:
+        """
+        Update an existing task
+        
+        Args:
+            task_id: Task ID
+            updates: Dictionary of fields to update
+            
+        Returns:
+            True if successful
+        """
+        tasks = self.load_tasks()
+        
+        if task_id not in tasks:
+            raise ValueError(f"Task '{task_id}' not found")
+        
+        # Update fields
+        tasks[task_id].update(updates)
+        tasks[task_id]["updated_at"] = datetime.now().isoformat()
+        
+        self.save_tasks(tasks)
+        return True
+    
+    def delete_task(self, task_id: str) -> bool:
+        """
+        Delete a task
+        
+        Args:
+            task_id: Task ID
+            
+        Returns:
+            True if successful
+        """
+        tasks = self.load_tasks()
+        
+        if task_id not in tasks:
+            raise ValueError(f"Task '{task_id}' not found")
+        
+        del tasks[task_id]
+        self.save_tasks(tasks)
+        return True
+    
+    def get_task(self, task_id: str) -> Optional[dict]:
+        """
+        Get a specific task
+        
+        Args:
+            task_id: Task ID
+            
+        Returns:
+            Task data or None if not found
+        """
+        tasks = self.load_tasks()
+        return tasks.get(task_id)
+    
+    def list_tasks(self, enabled_only: bool = False) -> List[dict]:
+        """
+        List all tasks
+        
+        Args:
+            enabled_only: If True, only return enabled tasks
+            
+        Returns:
+            List of task dictionaries
+        """
+        tasks = self.load_tasks()
+        task_list = list(tasks.values())
+        
+        if enabled_only:
+            task_list = [t for t in task_list if t.get("enabled", True)]
+        
+        # Sort by next_run_at
+        task_list.sort(key=lambda t: t.get("next_run_at", float('inf')))
+        
+        return task_list
+    
+    def enable_task(self, task_id: str, enabled: bool = True) -> bool:
+        """
+        Enable or disable a task
+        
+        Args:
+            task_id: Task ID
+            enabled: True to enable, False to disable
+            
+        Returns:
+            True if successful
+        """
+        return self.update_task(task_id, {"enabled": enabled})

bridge/agent_bridge.py

@@ -180,6 +180,7 @@ class AgentBridge:
         self.agents = {}  # session_id -> Agent instance mapping
         self.default_agent = None  # For backward compatibility (no session_id)
         self.agent: Optional[Agent] = None
+        self.scheduler_initialized = False
     def create_agent(self, system_prompt: str, tools: List = None, **kwargs) -> Agent:
         """
         Create the super agent with COW integration
@@ -268,6 +269,21 @@ class AgentBridge:
         # Get workspace from config
         workspace_root = os.path.expanduser(conf().get("agent_workspace", "~/cow"))
 
+        # Load environment variables from workspace .env file
+        env_file = os.path.join(workspace_root, '.env')
+        if os.path.exists(env_file):
+            try:
+                from dotenv import load_dotenv
+                load_dotenv(env_file, override=True)
+                logger.info(f"[AgentBridge] Loaded environment variables from {env_file}")
+            except ImportError:
+                logger.warning("[AgentBridge] python-dotenv not installed, skipping .env file loading")
+            except Exception as e:
+                logger.warning(f"[AgentBridge] Failed to load .env file: {e}")
+        
+        # Migrate API keys from config.json to environment variables (if not already set)
+        self._migrate_config_to_env(workspace_root)
+
         # Initialize workspace and create template files
         from agent.prompt import ensure_workspace, load_context_files, PromptBuilder
 
@@ -357,7 +373,16 @@ class AgentBridge:
 
         for tool_name in tool_manager.tool_classes.keys():
             try:
-                tool = tool_manager.create_tool(tool_name)
+                # Special handling for EnvConfig tool - pass agent_bridge reference
+                if tool_name == "env_config":
+                    from agent.tools import EnvConfig
+                    tool = EnvConfig({
+                        "workspace_dir": workspace_root,
+                        "agent_bridge": self  # Pass self reference for hot reload
+                    })
+                else:
+                    tool = tool_manager.create_tool(tool_name)
+                
                 if tool:
                     # Apply workspace config to file operation tools
                     if tool_name in ['read', 'write', 'edit', 'bash', 'grep', 'find', 'ls']:
@@ -381,6 +406,36 @@ class AgentBridge:
             tools.extend(memory_tools)
             logger.info(f"[AgentBridge] Added {len(memory_tools)} memory tools")
 
+        # Initialize scheduler service (once)
+        if not self.scheduler_initialized:
+            try:
+                from agent.tools.scheduler.integration import init_scheduler
+                if init_scheduler(self):
+                    self.scheduler_initialized = True
+                    logger.info("[AgentBridge] Scheduler service initialized")
+            except Exception as e:
+                logger.warning(f"[AgentBridge] Failed to initialize scheduler: {e}")
+        
+        # Inject scheduler dependencies into SchedulerTool instances
+        if self.scheduler_initialized:
+            try:
+                from agent.tools.scheduler.integration import get_task_store, get_scheduler_service
+                from agent.tools import SchedulerTool
+                
+                task_store = get_task_store()
+                scheduler_service = get_scheduler_service()
+                
+                for tool in tools:
+                    if isinstance(tool, SchedulerTool):
+                        tool.task_store = task_store
+                        tool.scheduler_service = scheduler_service
+                        if not tool.config:
+                            tool.config = {}
+                        tool.config["channel_type"] = conf().get("channel_type", "unknown")
+                        logger.debug("[AgentBridge] Injected scheduler dependencies into SchedulerTool")
+            except Exception as e:
+                logger.warning(f"[AgentBridge] Failed to inject scheduler dependencies: {e}")
+
         logger.info(f"[AgentBridge] Loaded {len(tools)} tools: {[t.name for t in tools]}")
 
         # Load context files (SOUL.md, USER.md, etc.)
@@ -449,6 +504,21 @@ class AgentBridge:
         # Get workspace from config
         workspace_root = os.path.expanduser(conf().get("agent_workspace", "~/cow"))
 
+        # Load environment variables from workspace .env file
+        env_file = os.path.join(workspace_root, '.env')
+        if os.path.exists(env_file):
+            try:
+                from dotenv import load_dotenv
+                load_dotenv(env_file, override=True)
+                logger.info(f"[AgentBridge] Loaded environment variables from {env_file} for session {session_id}")
+            except ImportError:
+                logger.warning(f"[AgentBridge] python-dotenv not installed, skipping .env file loading for session {session_id}")
+            except Exception as e:
+                logger.warning(f"[AgentBridge] Failed to load .env file for session {session_id}: {e}")
+        
+        # Migrate API keys from config.json to environment variables (if not already set)
+        self._migrate_config_to_env(workspace_root)
+
         # Initialize workspace
         from agent.prompt import ensure_workspace, load_context_files, PromptBuilder
 
@@ -550,6 +620,36 @@ class AgentBridge:
 
         if memory_tools:
             tools.extend(memory_tools)
+        
+        # Initialize scheduler service (once, if not already initialized)
+        if not self.scheduler_initialized:
+            try:
+                from agent.tools.scheduler.integration import init_scheduler
+                if init_scheduler(self):
+                    self.scheduler_initialized = True
+                    logger.info(f"[AgentBridge] Scheduler service initialized for session {session_id}")
+            except Exception as e:
+                logger.warning(f"[AgentBridge] Failed to initialize scheduler for session {session_id}: {e}")
+        
+        # Inject scheduler dependencies into SchedulerTool instances
+        if self.scheduler_initialized:
+            try:
+                from agent.tools.scheduler.integration import get_task_store, get_scheduler_service
+                from agent.tools import SchedulerTool
+                
+                task_store = get_task_store()
+                scheduler_service = get_scheduler_service()
+                
+                for tool in tools:
+                    if isinstance(tool, SchedulerTool):
+                        tool.task_store = task_store
+                        tool.scheduler_service = scheduler_service
+                        if not tool.config:
+                            tool.config = {}
+                        tool.config["channel_type"] = conf().get("channel_type", "unknown")
+                        logger.debug(f"[AgentBridge] Injected scheduler dependencies for session {session_id}")
+            except Exception as e:
+                logger.warning(f"[AgentBridge] Failed to inject scheduler dependencies for session {session_id}: {e}")
 
         # Load context files
         context_files = load_context_files(workspace_root)
@@ -667,6 +767,17 @@ class AgentBridge:
             if not agent:
                 return Reply(ReplyType.ERROR, "Failed to initialize super agent")
             
+            # Attach context to scheduler tool if present
+            if context and agent.tools:
+                for tool in agent.tools:
+                    if tool.name == "scheduler":
+                        try:
+                            from agent.tools.scheduler.integration import attach_scheduler_to_tool
+                            attach_scheduler_to_tool(tool, context)
+                        except Exception as e:
+                            logger.warning(f"[AgentBridge] Failed to attach context to scheduler: {e}")
+                        break
+            
             # Use agent's run_stream method
             response = agent.run_stream(
                 user_message=query,
@@ -680,6 +791,72 @@ class AgentBridge:
             logger.error(f"Agent reply error: {e}")
             return Reply(ReplyType.ERROR, f"Agent error: {str(e)}")
     
+    def _migrate_config_to_env(self, workspace_root: str):
+        """
+        Migrate API keys from config.json to .env file if not already set
+        
+        Args:
+            workspace_root: Workspace directory path
+        """
+        from config import conf
+        import os
+        
+        # Mapping from config.json keys to environment variable names
+        key_mapping = {
+            "open_ai_api_key": "OPENAI_API_KEY",
+            "open_ai_api_base": "OPENAI_API_BASE",
+            "gemini_api_key": "GEMINI_API_KEY",
+            "claude_api_key": "CLAUDE_API_KEY",
+            "linkai_api_key": "LINKAI_API_KEY",
+        }
+        
+        env_file = os.path.join(workspace_root, '.env')
+        
+        # Read existing env vars from .env file
+        existing_env_vars = {}
+        if os.path.exists(env_file):
+            try:
+                with open(env_file, 'r', encoding='utf-8') as f:
+                    for line in f:
+                        line = line.strip()
+                        if line and not line.startswith('#') and '=' in line:
+                            key, _ = line.split('=', 1)
+                            existing_env_vars[key.strip()] = True
+            except Exception as e:
+                logger.warning(f"[AgentBridge] Failed to read .env file: {e}")
+        
+        # Check which keys need to be migrated
+        keys_to_migrate = {}
+        for config_key, env_key in key_mapping.items():
+            # Skip if already in .env file
+            if env_key in existing_env_vars:
+                continue
+            
+            # Get value from config.json
+            value = conf().get(config_key, "")
+            if value and value.strip():  # Only migrate non-empty values
+                keys_to_migrate[env_key] = value.strip()
+        
+        # Write new keys to .env file
+        if keys_to_migrate:
+            try:
+                # Ensure .env file exists
+                if not os.path.exists(env_file):
+                    os.makedirs(os.path.dirname(env_file), exist_ok=True)
+                    open(env_file, 'a').close()
+                
+                # Append new keys
+                with open(env_file, 'a', encoding='utf-8') as f:
+                    f.write('\n# Auto-migrated from config.json\n')
+                    for key, value in keys_to_migrate.items():
+                        f.write(f'{key}={value}\n')
+                        # Also set in current process
+                        os.environ[key] = value
+                
+                logger.info(f"[AgentBridge] Migrated {len(keys_to_migrate)} API keys from config.json to .env: {list(keys_to_migrate.keys())}")
+            except Exception as e:
+                logger.warning(f"[AgentBridge] Failed to migrate API keys: {e}")
+    
     def clear_session(self, session_id: str):
         """
         Clear a specific session's agent and conversation history
@@ -695,4 +872,43 @@ class AgentBridge:
         """Clear all agent sessions"""
         logger.info(f"[AgentBridge] Clearing all sessions ({len(self.agents)} total)")
         self.agents.clear()
-        self.default_agent = None
+        self.default_agent = None
+    
+    def refresh_all_skills(self) -> int:
+        """
+        Refresh skills in all agent instances after environment variable changes.
+        This allows hot-reload of skills without restarting the agent.
+        
+        Returns:
+            Number of agent instances refreshed
+        """
+        import os
+        from dotenv import load_dotenv
+        from config import conf
+        
+        # Reload environment variables from .env file
+        workspace_root = os.path.expanduser(conf().get("agent_workspace", "~/cow"))
+        env_file = os.path.join(workspace_root, '.env')
+        
+        if os.path.exists(env_file):
+            load_dotenv(env_file, override=True)
+            logger.info(f"[AgentBridge] Reloaded environment variables from {env_file}")
+        
+        refreshed_count = 0
+        
+        # Refresh default agent
+        if self.default_agent and hasattr(self.default_agent, 'skill_manager'):
+            self.default_agent.skill_manager.refresh_skills()
+            refreshed_count += 1
+            logger.info("[AgentBridge] Refreshed skills in default agent")
+        
+        # Refresh all session agents
+        for session_id, agent in self.agents.items():
+            if hasattr(agent, 'skill_manager'):
+                agent.skill_manager.refresh_skills()
+                refreshed_count += 1
+        
+        if refreshed_count > 0:
+            logger.info(f"[AgentBridge] Refreshed skills in {refreshed_count} agent instance(s)")
+        
+        return refreshed_count

requirements.txt

@@ -9,6 +9,9 @@ pre-commit
 web.py
 linkai>=0.0.6.0
 agentmesh-sdk>=0.1.3
+python-dotenv>=1.0.0
+PyYAML>=6.0
+croniter>=2.0.0
 
 # feishu websocket mode
 lark-oapi

skills/bocha-search/SKILL.md

@@ -0,0 +1,91 @@
+---
+name: bocha-search
+description: High-quality web search with AI-optimized results. Use when user needs to search the internet for current information, news, or research topics.
+homepage: https://open.bocha.cn/
+metadata:
+  emoji: 🔍
+  requires:
+    bins: ["curl"]
+    env: ["BOCHA_API_KEY"]
+  primaryEnv: "BOCHA_API_KEY"
+---
+
+# Bocha Search
+
+High-quality web search powered by Bocha AI, optimized for AI consumption. Returns web pages, images, and detailed metadata.
+
+## Setup
+
+This skill requires a Bocha API key. If not configured:
+
+1. Visit https://open.bocha.cn to get an API key
+2. Set the key using: `env_config(action="set", key="BOCHA_API_KEY", value="your-key")`
+3. Or manually add to `~/cow/.env`: `BOCHA_API_KEY=your-key`
+
+## Usage
+
+**Important**: Scripts are located relative to this skill's base directory.
+
+When you see this skill in `<available_skills>`, note the `<base_dir>` path.
+
+```bash
+# General pattern:
+bash "<base_dir>/scripts/search.sh" "<query>" [count] [freshness] [summary]
+
+# Parameters:
+# - query: Search query (required)
+# - count: Number of results (1-50, default: 10)
+# - freshness: Time range filter (default: noLimit)
+#   Options: noLimit, oneDay, oneWeek, oneMonth, oneYear, YYYY-MM-DD..YYYY-MM-DD
+# - summary: Include text summary (true/false, default: false)
+```
+
+## Examples
+
+### Basic search
+```bash
+bash "<base_dir>/scripts/search.sh" "latest AI news"
+```
+
+### Search with more results
+```bash
+bash "<base_dir>/scripts/search.sh" "Python tutorials" 20
+```
+
+### Search recent content with summary
+```bash
+bash "<base_dir>/scripts/search.sh" "阿里巴巴ESG报告" 10 oneWeek true
+```
+
+### Search specific date range
+```bash
+bash "<base_dir>/scripts/search.sh" "tech news" 15 "2025-01-01..2025-02-01"
+```
+
+## Response Format
+
+The API returns structured data compatible with Bing Search API:
+
+**Web Pages** (in `data.webPages.value`):
+- `name`: Page title
+- `url`: Page URL
+- `snippet`: Short description
+- `summary`: Full text summary (if requested)
+- `siteName`: Website name
+- `siteIcon`: Website icon URL
+- `datePublished`: Publication date (UTC+8)
+- `language`: Page language
+
+**Images** (in `data.images.value`):
+- `contentUrl`: Image URL
+- `hostPageUrl`: Source page URL
+- `width`, `height`: Image dimensions
+- `thumbnailUrl`: Thumbnail URL
+
+## Notes
+
+- **Optimized for AI**: Results include summaries and structured metadata
+- **Time range**: Use `noLimit` for best results (algorithm auto-optimizes time range)
+- **Timeout**: 30 seconds
+- **Rate limits**: Check your API plan at https://open.bocha.cn
+- **Response format**: Compatible with Bing Search API for easy integration

skills/bocha-search/scripts/search.sh

@@ -0,0 +1,75 @@
+#!/usr/bin/env bash
+# Bocha Web Search API wrapper
+# API Docs: https://open.bocha.cn/
+
+set -euo pipefail
+
+query="${1:-}"
+count="${2:-10}"
+freshness="${3:-noLimit}"
+summary="${4:-false}"
+
+if [ -z "$query" ]; then
+    echo '{"error": "Query is required", "usage": "bash search.sh <query> [count] [freshness] [summary]"}'
+    exit 1
+fi
+
+if [ -z "${BOCHA_API_KEY:-}" ]; then
+    echo '{"error": "BOCHA_API_KEY environment variable is not set", "help": "Visit https://open.bocha.cn to get an API key"}'
+    exit 1
+fi
+
+# Validate count (1-50)
+if ! [[ "$count" =~ ^[0-9]+$ ]] || [ "$count" -lt 1 ] || [ "$count" -gt 50 ]; then
+    count=10
+fi
+
+# Build JSON request body
+request_body=$(cat <<EOF
+{
+  "query": "$query",
+  "count": $count,
+  "freshness": "$freshness",
+  "summary": $summary
+}
+EOF
+)
+
+# Call Bocha API
+response=$(curl -sS --max-time 30 \
+    -X POST \
+    -H "Authorization: Bearer $BOCHA_API_KEY" \
+    -H "Content-Type: application/json" \
+    -H "Accept: application/json" \
+    -d "$request_body" \
+    "https://api.bocha.cn/v1/web-search" 2>&1)
+
+curl_exit_code=$?
+
+if [ $curl_exit_code -ne 0 ]; then
+    echo "{\"error\": \"Failed to call Bocha API\", \"details\": \"$response\"}"
+    exit 1
+fi
+
+# Simple JSON validation - check if response starts with { or [
+if [[ ! "$response" =~ ^[[:space:]]*[\{\[] ]]; then
+    echo "{\"error\": \"Invalid JSON response from API\", \"response\": \"$response\"}"
+    exit 1
+fi
+
+# Extract API code using grep and sed (basic JSON parsing)
+api_code=$(echo "$response" | grep -o '"code"[[:space:]]*:[[:space:]]*[0-9]*' | grep -o '[0-9]*' | head -1)
+
+# If code extraction failed or code is not 200, check for error
+if [ -n "$api_code" ] && [ "$api_code" != "200" ]; then
+    # Try to extract error message
+    api_msg=$(echo "$response" | grep -o '"msg"[[:space:]]*:[[:space:]]*"[^"]*"' | sed 's/"msg"[[:space:]]*:[[:space:]]*"\(.*\)"/\1/' | head -1)
+    if [ -z "$api_msg" ]; then
+        api_msg="Unknown error"
+    fi
+    echo "{\"error\": \"API returned error\", \"code\": $api_code, \"message\": \"$api_msg\"}"
+    exit 1
+fi
+
+# Return the full response
+echo "$response"

skills/skill-creator/SKILL.md

@@ -243,20 +243,87 @@ If you used `--examples`, delete any placeholder files that are not needed for t
 
 ##### Frontmatter
 
-Write the YAML frontmatter with `name` and `description`:
+Write the YAML frontmatter with `name`, `description`, and optional `metadata`:
 
 - `name`: The skill name
 - `description`: This is the primary triggering mechanism for your skill, and helps the agent understand when to use the skill.
   - Include both what the Skill does and specific triggers/contexts for when to use it.
   - Include all "when to use" information here - Not in the body. The body is only loaded after triggering, so "When to Use This Skill" sections in the body are not helpful to the agent.
   - Example description for a `docx` skill: "Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. Use when the agent needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks"
+- `metadata`: (Optional) Specify requirements and configuration
+  - `requires.bins`: Required binaries (e.g., `["curl", "jq"]`)
+  - `requires.env`: Required environment variables (e.g., `["OPENAI_API_KEY"]`)
+  - `primaryEnv`: Primary environment variable name (for API keys)
+  - `always`: Set to `true` to always load regardless of requirements
+  - `emoji`: Skill icon (optional)
 
-Do not include any other fields in YAML frontmatter.
+**API Key Requirements**:
+
+If your skill needs an API key, declare it in metadata:
+
+```yaml
+---
+name: my-search
+description: Search using MyAPI
+metadata:
+  requires:
+    bins: ["curl"]
+    env: ["MYAPI_KEY"]
+  primaryEnv: "MYAPI_KEY"
+---
+```
+
+**Auto-enable rule**: Skills are automatically enabled when required environment variables are set, and automatically disabled when missing. No manual configuration needed.
 
 ##### Body
 
 Write instructions for using the skill and its bundled resources.
 
+**If your skill requires an API key**, include setup instructions in the body:
+
+```markdown
+## Setup
+
+This skill requires an API key from [Service Name].
+
+1. Visit https://service.com to get an API key
+2. Configure it using: `env_config(action="set", key="SERVICE_API_KEY", value="your-key")`
+3. Or manually add to `~/cow/.env`: `SERVICE_API_KEY=your-key`
+4. Restart the agent for changes to take effect
+
+## Usage
+...
+```
+
+The bash script should check for the key and provide helpful error messages:
+
+```bash
+#!/usr/bin/env bash
+if [ -z "${SERVICE_API_KEY:-}" ]; then
+    echo "Error: SERVICE_API_KEY not set"
+    echo "Please configure your API key first (see SKILL.md)"
+    exit 1
+fi
+
+curl -H "Authorization: Bearer $SERVICE_API_KEY" ...
+```
+
+**Script Path Convention**:
+
+When writing SKILL.md instructions, remember that:
+- Skills are listed in `<available_skills>` with a `<base_dir>` path
+- Scripts should be referenced as: `<base_dir>/scripts/script_name.sh`
+- The AI will see the base_dir and can construct the full path
+
+Example instruction in SKILL.md:
+```markdown
+## Usage
+
+Scripts are in this skill's base directory (shown in skill listing).
+
+bash "<base_dir>/scripts/my_script.sh" <args>
+```
+
 ### Step 5: Validate (Optional)
 
 Validate skill format:

skills/web-fetch/SKILL.md

@@ -1,11 +1,12 @@
 ---
 name: web-fetch
-description: Fetch and extract readable content from web pages
+description: Fetch and extract readable content from web pages. Use for lightweight page access without browser automation.
 homepage: https://github.com/zhayujie/chatgpt-on-wechat
 metadata:
   emoji: 🌐
   requires:
     bins: ["curl"]
+  always: true
 ---
 
 # Web Fetch
@@ -14,10 +15,16 @@ Fetch and extract readable content from web pages using curl and basic text proc
 
 ## Usage
 
-Use the provided script to fetch a URL and extract its content:
+**Important**: Scripts are located relative to this skill's base directory.
+
+When you see this skill in `<available_skills>`, note the `<base_dir>` path.
 
 ```bash
-bash scripts/fetch.sh <url> [output_file]
+# General pattern:
+bash "<base_dir>/scripts/fetch.sh" <url> [output_file]
+
+# Example (replace <base_dir> with actual path from skill listing):
+bash "~/chatgpt-on-wechat/skills/web-fetch/scripts/fetch.sh" "https://example.com"
 ```
 
 **Parameters:**
@@ -31,18 +38,18 @@ bash scripts/fetch.sh <url> [output_file]
 
 ### Fetch a web page
 ```bash
-bash scripts/fetch.sh "https://example.com"
+bash "<base_dir>/scripts/fetch.sh" "https://example.com"
 ```
 
 ### Save to file
 ```bash
-bash scripts/fetch.sh "https://example.com" output.txt
+bash "<base_dir>/scripts/fetch.sh" "https://example.com" output.txt
 cat output.txt
 ```
 
 ## Notes
 
-- Uses curl for HTTP requests (timeout: 20s)
+- Uses curl for HTTP requests (timeout: 10s)
 - Extracts title and basic text content
 - Removes HTML tags and scripts
 - Works with any standard web page

skills/web-fetch/scripts/fetch.sh

@@ -19,7 +19,7 @@ if [[ ! "$url" =~ ^https?:// ]]; then
 fi
 
 # Fetch the page with curl
-html=$(curl -sS -L --max-time 20 \
+html=$(curl -sS -L --max-time 10 \
     -H "User-Agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36" \
     -H "Accept: text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8" \
     "$url" 2>&1) || {