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。
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionecommerce-supportExecute the skills CLI command in your project's root directory to begin installation:
Fetches ecommerce-support from yangliu2060/smith--skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate ecommerce-support. Access via /ecommerce-support in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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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。
当用户说以下内容时启动此技能:
| 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 |
┌─────────────────────┐
│ 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 │
└─────────────────┘
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]
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"
}
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:
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"
}
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~
// 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
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:
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
{
"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"
}
]
}
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!
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!
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。
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?
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?"
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
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
platform: taobao
login_url: https://login.taobao.com
seller_url: https://myseller.taobao.com
order_path: /home.htm#/order-manage
search_selector: "#keyword"
platform: jd
login_url: https://passport.jd.com
seller_url: https://shop.jd.com
order_path: /order/list
search_selector: ".search-input"
✓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
Steps
- 1Install product management skill
- 2Start with user story generation for known feature
- 3Progress to competitive analysis: research 2-3 competitors
- 4Use for roadmap prioritization: apply RICE/ICE scoring
- 5Draft stakeholder communications and refine based on feedback
- 6Build template library for recurring PM tasks
- 7Share 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
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
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4.7★★★★★28 reviews- XXiao Abebe★★★★★Dec 16, 2024
Useful defaults in ecommerce-support — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- YYuki Rahman★★★★★Dec 12, 2024
I recommend ecommerce-support for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- YYuki Gonzalez★★★★★Nov 23, 2024
ecommerce-support reduced setup friction for our internal harness; good balance of opinion and flexibility.
- DDaniel Anderson★★★★★Nov 7, 2024
ecommerce-support is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- RRahul Santra★★★★★Nov 3, 2024
Registry listing for ecommerce-support matched our evaluation — installs cleanly and behaves as described in the markdown.
- ZZaid 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.
- DDaniel 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.
- PPratham Ware★★★★★Oct 22, 2024
ecommerce-support reduced setup friction for our internal harness; good balance of opinion and flexibility.
- AAisha Jain★★★★★Oct 22, 2024
ecommerce-support is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- JJin 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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