China Shopping
Recommend suitable Chinese shopping platforms based on product category and shopping intent.
This is a lightweight Python-backed skill. It uses a local Python script plus bundled JSON data to map product names to shopping categories and recommend suitable Chinese e-commerce platforms.
It does not perform live browsing, real-time price checks, or seller verification. For live page inspection, real-time pricing, or store-level comparison, switch to browser-based workflows instead of pretending this skill does live retrieval.
Runtime requirement
Require:
Do not require:
- - INLINECODE1
- shell helper scripts
- install scripts
- writable config or log paths
- credentials or API keys
Files used by this skill
- -
china-shopping.py — local CLI implementation - INLINECODE3 — category and platform recommendation data
- INLINECODE4 — product keyword mapping
- INLINECODE5 — fallback recommendations
Read these references as needed:
- -
references/category-guide.md for category-to-platform guidance - INLINECODE7 for answer structure
Workflow
- 1. Identify the product category or shopping intent.
- Accept a product type, shopping need, or product name.
- If the request is too broad, ask one short clarifying question.
- 2. Use the local Python implementation when execution is appropriate.
- Run
python3 china-shopping.py recommend "<product>" for the default recommendation flow.
- Use
python3 china-shopping.py categories when the user wants to inspect supported categories.
- 3. Explain the recommendation.
- Say why the recommended platforms fit.
- Mention meaningful trade-offs when useful.
- 4. Add practical guidance.
- Suggest what the user should check next, such as official stores, seller reputation, user reviews, authenticity, or delivery terms.
Output
Use this structure unless the user asks for something else:
Recommended Platforms
List the most suitable 2-4 platforms.
Why
Explain why each platform fits the product or need.
Best Choice
State which platform is the strongest default recommendation.
Caveats
Mention important cautions, such as seller quality differences, authenticity risk, or category-specific trade-offs.
Final Advice
Give a practical buying suggestion in plain language.
Quality bar
Do:
- - recommend platforms by category fit
- explain trade-offs clearly
- mention official stores or trusted sellers when relevant
- stay honest about not doing real-time price retrieval
Do not:
- - pretend to check live listings or prices
- claim a platform is cheapest without real-time evidence
- suggest weak-fit platforms just because they are famous
中国购物
根据产品类别和购物意图推荐合适的中国购物平台。
这是一个轻量级的、基于Python的技能。它使用本地Python脚本和捆绑的JSON数据,将产品名称映射到购物类别,并推荐合适的中国电商平台。
它不执行实时浏览、实时价格检查或卖家验证。如需实时页面检查、实时定价或店铺级比较,请切换到基于浏览器的工作流程,而不是假装此技能能进行实时检索。
运行时要求
需要:
不需要:
- - jq
- shell辅助脚本
- 安装脚本
- 可写的配置或日志路径
- 凭证或API密钥
此技能使用的文件
- - china-shopping.py — 本地CLI实现
- data/categories.json — 类别和平台推荐数据
- data/productmapping.json — 产品关键词映射
- data/generalfallback.json — 通用备选推荐
根据需要阅读以下参考资料:
- - references/category-guide.md 获取类别到平台的指导
- references/output-patterns.md 获取回答结构
工作流程
- 1. 识别产品类别或购物意图。
- 接受产品类型、购物需求或产品名称。
- 如果请求过于宽泛,提出一个简短的问题以澄清。
- 2. 在适当的情况下使用本地Python实现。
- 运行 python3 china-shopping.py recommend
进行默认推荐流程。
- 当用户想查看支持的类别时,使用 python3 china-shopping.py categories。
- 3. 解释推荐理由。
- 说明为什么推荐的平台适合。
- 在有用时提及有意义的权衡。
- 4. 提供实用指导。
- 建议用户下一步应检查什么,例如官方店铺、卖家信誉、用户评价、正品保障或配送条款。
输出
除非用户另有要求,请使用此结构:
推荐平台
列出最合适的2-4个平台。
理由
解释每个平台适合该产品或需求的原因。
最佳选择
说明哪个平台是最强的默认推荐。
注意事项
提及重要提醒,例如卖家质量差异、正品风险或特定类别的权衡。
最终建议
用通俗语言给出实用的购买建议。
质量标准
应做:
- - 根据类别匹配推荐平台
- 清晰解释权衡
- 在相关时提及官方店铺或可信卖家
- 诚实地说明不进行实时价格检索
不应做:
- - 假装检查实时列表或价格
- 在没有实时证据的情况下声称某个平台最便宜
- 仅因平台知名而推荐不匹配的平台