ecommerce-support

yangliu2060/smith--skills · updated Apr 8, 2026

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$npx skills add https://github.com/yangliu2060/smith--skills --skill ecommerce-support
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summary

AI 驱动的电商客服机器人,自动识别客户意图,处理订单查询、商品推荐、投诉工单等场景。

skill.md

电商客服助手

AI 驱动的电商客服机器人,自动识别客户意图,处理订单查询、商品推荐、投诉工单等场景。

触发条件

当用户说以下内容时启动此技能:

  • "客服回复"
  • "处理客户问题"
  • "订单查询"
  • "ecommerce support"
  • "帮我回复客户"
  • "生成客服话术"

依赖的 MCP 服务

MCP 用途 必需
playwright 自动登录电商后台查询订单 可选
supabase 存储订单/工单数据 可选
memory 保持对话上下文 可选

工作流程

┌─────────────────────┐
│   客户消息输入       │
└──────────┬──────────┘
┌─────────────────────┐
│   AI 意图识别       │
│   分析客户需求       │
└──────────┬──────────┘
     ┌─────┼─────┬──────────┐
     │     │     │          │
     ▼     ▼     ▼          ▼
┌───────┐┌───────┐┌───────┐┌───────┐
│订单   ││商品   ││投诉   ││常见   │
│查询   ││推荐   ││工单   ││问答   │
└───┬───┘└───┬───┘└───┬───┘└───┬───┘
    │        │        │        │
    ▼        ▼        ▼        ▼
┌───────┐┌───────┐┌───────┐┌───────┐
│Playwright│ AI   ││创建   ││知识库 │
│查后台  ││分析   ││工单   ││匹配   │
└───┬───┘└───┬───┘└───┬───┘└───┬───┘
    │        │        │        │
    └────────┴────────┴────────┘
         ┌─────────────────┐
         │  生成客服回复    │
         │  保存对话记录    │
         └─────────────────┘

执行步骤

步骤 1:接收客户消息

输入格式

用户: 帮我回复这个客户:
"你好,我的订单123456怎么还没发货?已经3天了!"

或批量处理:

用户: 处理这些客服消息 [消息列表/文件]

步骤 2:AI 意图识别

意图分类

意图 关键词 处理方式
订单查询 订单、发货、物流、到哪了 查询订单状态
退款退货 退款、退货、换货、不想要了 创建退货工单
商品咨询 有货吗、尺码、颜色、推荐 商品推荐
投诉建议 投诉、差评、不满意、垃圾 创建投诉工单
优惠活动 优惠券、满减、活动、便宜 活动信息
售后问题 坏了、质量问题、维修 创建售后工单
闲聊其他 你好、谢谢、在吗 常规回复

意图识别提示词

分析以下客户消息的意图:

【客户消息】
{message}

【输出格式】
{
  "intent": "order_query|refund|product_inquiry|complaint|promotion|after_sale|chat",
  "confidence": 0.95,
  "entities": {
    "order_id": "123456",
    "product_name": "",
    "emotion": "negative|neutral|positive"
  },
  "urgency": "high|medium|low"
}

步骤 3:订单查询处理

方式 A:使用 Playwright MCP 查询真实订单

适用场景:需要查询电商后台真实订单状态

// Playwright MCP 操作步骤

1. 打开电商后台
   browser_navigate({ url: "https://seller.taobao.com" })
   // 或其他电商平台后台

2. 检查登录状态
   - 如未登录,提示用户先登录
   - 保存登录状态供后续使用

3. 进入订单管理
   browser_click({ element: "订单管理" })

4. 搜索订单号
   browser_type({
     element: "订单搜索框",
     text: "{order_id}"
   })
   browser_click({ element: "搜索" })

5. 获取订单状态
   browser_snapshot() // 截图获取订单信息

6. 解析订单状态
   - 订单状态(待发货/已发货/已签收)
   - 物流信息
   - 预计到达时间

支持的电商平台

  • 淘宝/天猫卖家中心
  • 京东商家后台
  • 拼多多商家版
  • Shopify Admin
  • 有赞商家后台

方式 B:模拟订单数据

适用场景:演示或无后台访问权限

{
  "order_id": "123456",
  "status": "shipped",
  "status_text": "已发货,运输中",
  "logistics": {
    "company": "顺丰速运",
    "tracking_no": "SF1234567890",
    "last_update": "2025-12-28 15:30",
    "location": "深圳转运中心"
  },
  "estimated_delivery": "2025-12-30"
}

步骤 4:商品推荐处理

推荐逻辑

1. 解析客户需求(品类、价格区间、偏好)
2. 匹配商品库/搜索商品
3. 生成推荐话术

【推荐话术模板】
亲,根据您的需求,为您推荐以下商品:

1️⃣ **{商品名1}** - ¥{价格}
   {商品亮点}

2️⃣ **{商品名2}** - ¥{价格}
   {商品亮点}

您看哪款更合适呢?有任何问题随时问我~

使用 Playwright 获取商品信息

// 从电商平台获取商品详情

1. 打开商品页面
   browser_navigate({ url: "{product_url}" })

2. 获取商品信息
   browser_snapshot()

3. 解析信息
   - 商品名称
   - 价格
   - 库存状态
   - 规格参数

步骤 5:工单处理

创建工单

{
  "ticket_id": "TK20251229001",
  "type": "complaint",
  "customer_id": "C12345",
  "order_id": "123456",
  "description": "客户投诉物流慢",
  "priority": "high",
  "status": "open",
  "created_at": "2025-12-29T10:30:00Z"
}

工单处理流程

  1. 创建工单记录
  2. 生成安抚回复
  3. 通知相关人员(可用邮件MCP)
  4. 跟踪处理进度

步骤 6:生成客服回复

回复生成提示词

你是一位专业的电商客服,请根据以下信息生成回复:

【客户消息】
{customer_message}

【意图分析】
意图: {intent}
情绪: {emotion}
紧急度: {urgency}

【查询结果】
{query_result}

【回复要求】
1. 称呼亲切(亲/您好)
2. 先共情,再解决
3. 信息准确完整
4. 语气温和专业
5. 如有问题主动道歉
6. 结尾询问是否还有其他需要

【输出格式】
直接输出回复内容,可适当使用emoji

步骤 7:保存对话记录

{
  "conversation_id": "conv_20251229_001",
  "customer_id": "C12345",
  "messages": [
    {
      "role": "customer",
      "content": "我的订单怎么还没发货?",
      "timestamp": "2025-12-29T10:30:00Z"
    },
    {
      "role": "assistant",
      "content": "亲,非常抱歉让您久等了...",
      "timestamp": "2025-12-29T10:30:05Z",
      "intent": "order_query"
    }
  ]
}

客服话术模板库

订单查询回复

已发货

亲,您的订单已经发货啦!🚚

物流信息:
📦 快递公司:{company}
📝 运单号:{tracking_no}
📍 当前位置:{location}
⏰ 预计送达:{estimated_delivery}

您可以点击订单详情查看实时物流~
还有其他问题吗?

未发货

亲,非常抱歉让您久等了!🙏

您的订单目前正在加紧处理中,预计{ship_date}前发出。
给您带来不便深感抱歉,我们会尽快为您安排~

如果着急,我可以帮您催一下仓库哦!

退款处理回复

亲,收到您的退款申请了~

我这边已经帮您提交处理:
📋 退款单号:{refund_id}
💰 退款金额:¥{amount}
⏰ 预计到账:1-3个工作日

退款会原路返回,届时请留意账户变动。
如有问题随时联系我哦!

投诉安抚回复

亲,真的非常抱歉给您带来了不好的体验!🙏

我完全理解您的心情,这确实是我们的问题。
我已经将您的情况反馈给主管,会尽快给您一个满意的解决方案。

为了表示歉意,这边给您申请了一张{coupon}优惠券,
希望能弥补一点点这次的不愉快。

请问您方便留一下联系电话吗?我们主管会亲自给您回电处理。

商品咨询回复

亲,这款商品的详细信息如下:

📦 {product_name}
💰 价格:¥{price}
📏 规格:{specs}
🎁 赠品:{gifts}
📦 库存:{stock_status}

{product_highlights}

现在下单还有{promotion}活动哦~
需要我帮您看下尺码吗?

使用示例

示例 1:单条消息回复

用户: 帮我回复:"订单123456到哪了"

Claude:
1. 识别意图:订单查询
2. [可选] 使用Playwright查询后台订单状态
3. 生成回复:
   "亲,您的订单123456已经发货啦!
    快递:顺丰 SF1234567890
    当前位置:深圳转运中心
    预计明天送达~还有其他问题吗?"

示例 2:批量处理

用户: 批量回复这10条客户消息

Claude:
1. 逐条分析意图
2. 批量查询相关信息
3. 生成10条回复
4. 输出结果供复制使用

示例 3:接入电商后台

用户: 连接淘宝后台,查询订单123456的真实状态

Claude:
1. 使用Playwright打开淘宝卖家中心
2. 检查登录状态(如需登录则提示)
3. 搜索订单号
4. 截图获取订单状态
5. 解析并生成回复

电商平台后台配置

淘宝/天猫

platform: taobao
login_url: https://login.taobao.com
seller_url: https://myseller.taobao.com
order_path: /home.htm#/order-manage
search_selector: "#keyword"

京东商家

platform: jd
login_url: https://passport.jd.com
seller_url: https://shop.jd.com
order_path: /order/list
search_selector: ".search-input"

Shopify

how to use ecommerce-support

How to use ecommerce-support on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add ecommerce-support
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/yangliu2060/smith--skills --skill ecommerce-support

The skills CLI fetches ecommerce-support from GitHub repository yangliu2060/smith--skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/ecommerce-support

Reload or restart Cursor to activate ecommerce-support. Access the skill through slash commands (e.g., /ecommerce-support) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.728 reviews
  • Xiao Abebe· Dec 16, 2024

    Useful defaults in ecommerce-support — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Yuki Rahman· Dec 12, 2024

    I recommend ecommerce-support for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Yuki Gonzalez· Nov 23, 2024

    ecommerce-support reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Daniel Anderson· Nov 7, 2024

    ecommerce-support is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Rahul Santra· Nov 3, 2024

    Registry listing for ecommerce-support matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Zaid Ghosh· Nov 3, 2024

    Keeps context tight: ecommerce-support is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Daniel Martinez· Oct 26, 2024

    Keeps context tight: ecommerce-support is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Pratham Ware· Oct 22, 2024

    ecommerce-support reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Aisha Jain· Oct 22, 2024

    ecommerce-support is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Jin Khan· Oct 14, 2024

    Registry listing for ecommerce-support matched our evaluation — installs cleanly and behaves as described in the markdown.

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