OpenClaw 上手指南：从安装到深度实践

# 全局安装
npm install -g openclaw@latest

# 初始化配置（交互式）
openclaw onboard

# 方式一：前台运行
openclaw gateway

# 方式二：后台守护进程
openclaw daemon start

# 登录 Telegram（获取 bot token）
openclaw channels login telegram

openclaw channels login whatsapp

openclaw channels login feishu

// 在代码中调用
await sessions_spawn({
  runtime: "subagent",
  task: "帮我查一下今天 AI 圈发生了什么大事",
  label: "research-agent"
});

# 每天早上 9 点推送 AI 资讯
openclaw cron add "AI 资讯推送" "cron 0 9 * * *" \
  --task "搜索今天 AI 圈重大新闻，推送到指定渠道"

// 记住重要信息
await write("MEMORY.md", "用户喜欢在下午 2 点开会");

// 截图
await browser({ action: "screenshot", path: "./screenshot.png" });

// 自动化操作
await browser({
  action: "act",
  request: { kind: "click", ref: "login-btn" }
});

# 从 ClawHub 安装技能
clawhub install weather

// 在 openclaw.json 中配置 MCP
{
  "mcpServers": {
    "filesystem": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-filesystem", "/你的项目路径"]
    },
    "brave-search": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-brave-search", "--api-key", "你的 Brave API Key"]
    }
  }
}

// 跨 Agent 协作
const result = await a2a.send({
  agent: "research-agent",
  task: "调研 OpenAI 最新模型",
  callback: "my-agent"  // 结果返回给我
});

// 定时触发：每天早上 9 点
// 1. 读取昨天 CRM 数据
const crmData = await feishu_bitale_list_records({
  app_token: "你的 CRM 应用",
  table_id: "客户表"
});

// 2. 让 AI 分析并生成报告
const report = await callAI({
  model: "deepseek/deepseek-r1",
  messages: [
    { role: "system", content: "你是一个专业的商业分析师" },
    { role: "user", content: `分析以下客户数据，生成今日报告：${JSON.stringify(crmData)}` }
  ]
});

// 3. 写入飞书文档并通知相关人
await feishu_doc({
  action: "append",
  doc_token: "团队共享文档",
  content: report
});

await feishu_chat({
  action: "send",
  chat_id: "销售群",
  message: "📊 今日客户分析报告已生成"
});

// 监听 GitHub Webhook
// 当有新 PR 时自动触发

const prDetails = await github.getPR({ owner, repo, pr_number });

const review = await callAI({
  model: "claude-sonnet-4",
  messages: [
    { 
      role: "system", 
      content: "你是一个资深代码审查专家，关注：安全性、性能、可维护性" 
    },
    { 
      role: "user", 
      content: `审查以下 PR：\n\nTitle: ${prDetails.title}\n\nDiff: ${prDetails.diff}` 
    }
  ]
});

// 评论 PR
await github.createReviewComment({
  owner, repo, pr_number,
  body: review
});

// 监听消息
onmessage(async (msg) => {
  // 1. 意图识别
  const intent = await callAI({
    model: "qwen/qwen-2.5-72b",
    messages: [
      { role: "user", content: msg.text }
    ],
    tools: [{
      name: "classify_intent",
      description: "识别用户意图",
      parameters: {
        type: "object",
        properties: {
          intent: { type: "string", enum: ["咨询", "投诉", "技术问题", "其他"] },
          urgency: { type: "string", enum: ["低", "中", "高"] }
        }
      }
    }]
  });

  // 2. 根据意图处理
  if (intent.intent === "技术问题") {
    // 检索知识库
    const solution = await rag.search(intent.query);
    await msg.reply(solution);
  } else if (intent.urgency === "高") {
    // 升级人工客服
    await notifyHuman({
      channel: "feishu",
      user: "客服主管",
      message: `高优先级工单：${msg.text}`
    });
  }
});

// 每天定时执行
openclaw cron add "AI 资讯推送" \
  "cron 0 9 * * * @ Asia/Shanghai"

const news = await tavily_search({
  query: "AI news today",
  topic: "news",
  time_range: "day"
});

await feishu_doc({
  action: "write",
  doc_token: "你的飞书文档 ID",
  content: formatNews(news)
});

await tts({
  text: "今天天气晴朗，适合外出",
  channel: "telegram"
});

// 生成封面图
await canvas({
  action: "present",
  javaScript: `generateCover("${title}", "${subtitle}")`
});

// 自动发布
await xhs_publisher({
  title: "AI 教程",
  content: "今天教大家用...",
  images: ["./cover.png"]
});

{
  // AI Provider 配置
  providers: {
    openai: { apiKey: process.env.OPENAI_API_KEY },
    minimax: { apiKey: process.env.MINIMAX_API_KEY }
  },
  
  // 默认模型
  model: "minimax-portal/MiniMax-M2.5",
  
  // 渠道配置
  channels: {
    telegram: { enabled: true },
    feishu: { enabled: true }
  },
  
  // 安全设置
  security: {
    allowlist: ["你的 user ID"]
  },
  
  // 消息设置
  messages: {
    groupChat: {
      requireMention: true  // 群聊需要 @ 才响应
    }
  }
}