📚 OpenClaw 最佳实践案例集

┌─────────────┐ │ GitHub Webhook │ └──────┬──────┘ │ ▼ ┌─────────────┐ │ OpenClaw Agent │ │ - 接收事件 │ │ - 分析内容 │ │ - 生成回复 │ └──────┬──────┘ │ ├─▶ 回复 Issue (GitHub API) ├─▶ 更新标签 (GitHub API) └─▶ 通知飞书 (Feishu API)

// skills/github-auto-reply/index.js const { Octokit } = require('octokit'); module.exports = { name: "github-auto-reply", description: "GitHub Issue自动回复", async onWebhook(event) { if (event.name !== "issues") return; const { action, issue } = event.payload; if (action !== "opened") return; // 1. 分析 Issue 类型 const type = await analyzeIssue(issue.title + "\n" + issue.body); // 2. 生成回复 let reply = ""; let labels = []; if (type === "bug") { reply = "🐛 感谢提交Bug！我们已收到，会尽快处理。\n\n临时解决方案：..."; labels = ["bug", "needs-triage"]; await notifyFeishu(issue); } else if (type === "feature") { reply = "✨ 很棒的想法！你有兴趣提交PR吗？\n\n参考：CONTRIBUTING.md"; labels = ["enhancement"]; } else { reply = "🤔 感谢提问！请查看文档：https://docs.miaoquai.com"; labels = ["question"]; } // 3. 回复 Issue const octokit = new Octokit({ token: process.env.GITHUB_TOKEN }); await octokit.rest.issues.createComment({ owner: "miaoquai", repo: "miaoquai", issue_number: issue.number, body: reply }); // 4. 添加标签 await octokit.rest.issues.addLabels({ owner: "miaoquai", repo: "miaoquai", issue_number: issue.number, labels: labels }); } }; async function analyzeIssue(content) { const agent = new OpenClaw(); const response = await agent.ask(`分析以下GitHub Issue的类型（bug/feature/question）：\n\n${content}`); return response.trim().toLowerCase(); } async function notifyFeishu(issue) { // 调用飞书API发送通知... }

┌──────────────┐ │ OpenClaw Cron │ (定时任务) └──────┬───────┘ │ 每天8:00/14:00/22:00 ▼ ┌──────────────┐ │ RSS聚合器 │ (抓取新闻) └──────┬───────┘ │ ▼ ┌──────────────┐ │ Agent处理器 │ (生成摘要) └──────┬───────┘ │ ▼ ┌──────────────┐ │ Discord Bot │ (发送消息) └──────────────┘

// 定时任务配置（使用 OpenClaw Cron） openclaw cron add \ name:"daily-ai-news" \ schedule:"0 8,14,22 * * *" \ payload.kind:"agentTurn" \ payload.message:"读取RSS最新内容，生成今日AI新闻摘要，发送到Discord频道1483699648890802201" \ sessionTarget:"isolated" // Agent 处理逻辑 async function sendDailyNews() { // 1. 抓取 RSS const feeds = [ "https://openai.com/blog/rss.xml", "https://www.anthropic.com/rss.xml", "https://huggingface.co/blog/feed.xml" ]; const articles = await fetchRSS(feeds); // 2. 生成摘要 const summary = await generateSummary(articles); // 3. 发送到 Discord const channelId = "1483699648890802201"; await sendToDiscord(channelId, { embeds: [{ title: "📰 今日AI新闻", description: summary, color: 0x667eea, timestamp: new Date().toISOString() }] }); }

// skills/rss-aggregator/index.js module.exports = { name: "rss-aggregator", description: "RSS新闻聚合与推送", async onSchedule() { // 1. 抓取所有源 const sources = [ "https://openai.com/blog/rss.xml", "https://www.anthropic.com/rss.xml", "https://huggingface.co/blog/feed.xml", "https://thegradient.pub/rss/" ]; const allArticles = []; for (const url of sources) { const articles = await parseRSS(url); allArticles.push(...articles); } // 2. 去重（基于标题相似度） const uniqueArticles = removeDuplicates(allArticles); // 3. 分类和评分 const categorized = await categorizeArticles(uniqueArticles); // 4. 生成HTML页面 await generateHTMLPage(categorized); // 5. 推送到Discord await pushToDiscord(categorized.slice(0, 5)); // 6. 发送飞书通知 await notifyFeishu(categorized.length); } };

Agent1 (关键词研究) → Agent2 (大纲生成) → Agent3 (文章撰写) → Agent4 (SEO优化) → Agent5 (发布)

// 使用 OpenClaw 多Agent协作 const workflow = [ { agent: "keyword-researcher", task: "研究OpenClaw相关热词" }, { agent: "outline-generator", task: "根据关键词生成大纲" }, { agent: "content-writer", task: "根据大纲撰写文章" }, { agent: "seo-optimizer", task: "优化SEO元素" }, { agent: "publisher", task: "发布到网站" } ]; for (const step of workflow) { const result = await runAgent(step.agent, step.task, context); context[step.agent] = result; }

// 使用 OpenClaw + MCP + Vector DB const { createVectorDB } = require('openclaw-vector'); // 1. 文档向量化 async function indexDocuments(docsPath) { const files = await readDir(docsPath); for (const file of files) { const content = await readFile(file); const embedding = await getEmbedding(content); await vectorDB.insert({ id: file.name, vector: embedding, metadata: { path: file.path, author: file.author } }); } } // 2. 语义搜索 async function searchDocs(query) { const queryEmbedding = await getEmbedding(query); const results = await vectorDB.search(queryEmbedding, 5); return results; } // 3. RAG 问答 async function answerQuestion(question, user) { // 检查权限 if (!hasPermission(user, "read-docs")) { return "❌ 你没有权限访问文档"; } // 搜索相关文档 const docs = await searchDocs(question); // 构建 Prompt const prompt = `基于以下文档回答问题：\n\n${docs.map(d => d.content).join("\n\n")}\n\n问题：${question}`; // 调用 LLM const answer = await llm.ask(prompt); return answer; }