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:

• python3

Do not require:

• jq
• 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
• data/categories.json — category and platform recommendation data
• data/product_mapping.json — product keyword mapping
• data/general_fallback.json — fallback recommendations

Read these references as needed:

• references/category-guide.md for category-to-platform guidance
• references/output-patterns.md 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.

1. Use the local Python implementation when execution is appropriate.
• Run python3 china-shopping.py recommend "" for the default recommendation flow.
• Use python3 china-shopping.py categories when the user wants to inspect supported categories.

1. Explain the recommendation.
• Say why the recommended platforms fit.
• Mention meaningful trade-offs when useful.

1. 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