AI × Cross-Border E-Commerce Knowledge Hub
An AAAI China Chapter open-source project
A hands-on AI manual for cross-border e-commerce — 69 chapters covering every step from product research to growth, each with copy-paste prompts.
This is more than a book. dist/ is a plug-and-play agent capability package — a 100-entity domain ontology, 9 installable skills, and an MCP server integration. Claude Code users can install it with two commands; the source is on GitHub.
🌐 Every chapter is available in all three languages. Use the language switcher (top right) to jump between 中文 / EN / 日本語 on any page — it keeps you on the same chapter.
Try It First
Copy this into ChatGPT or Claude and get results in 30 seconds:
You are a senior cross-border e-commerce expert with deep knowledge of the Amazon marketplace.
I want to sell a portable neck fan on Amazon US.
Please provide a quick market feasibility analysis including:
1. Category characteristics (seasonality, competition level, price range)
2. Top 3 competitors' key selling points and main pain points from negative reviews
3. 3 potential differentiation angles
4. Risk alerts (compliance, patents, seasonal inventory risks)
Present key data comparisons in table format.
<data_discipline>
- Specific figures or facts about market data, search volume, competitor performance, regulatory text, or fee rates must come from what I supplied. **Don't fill gaps from memory** — these facts move fast and your version may be stale
- When you need a fact to make a judgment, tell me which official source to verify it against, then stop and ask me
- Tag every conclusion with its source: [supplied by me] or [model inference]
</data_discipline>
How This Hub Is Organized
Six tracks:
| Track | For | Covers |
|---|---|---|
| Foundations | Everyone | AI literacy, prompt engineering, agents, RAG, RPA |
| Operators | Operations roles | Product research, listings, ads, customer service, compliance, finance |
| Developers | Engineers | Data pipelines, prediction models, RAG, agents, MCP |
| Managers | Team leads | Capability assessment, team building, ROI, risk governance |
| Marketplaces | All roles | Hands-on guides for 13 e-commerce platforms |
| Social Media | All roles | AI playbooks for 7 social channels |
Want to see what AI can (and can’t) do first? Start with the AI Landscape Assessment.
About the Prompts
All prompt templates in this hub were tested against:
- The T2 workhorse tier of ChatGPT / Claude / Gemini — re-verified July 2026 (current model ids in the model matrix)
- Claude (Opus 4 / Sonnet 4) — March 2026
Results can vary across models. If a prompt underperforms, try another model or add more context at the top of the prompt. AI models iterate quickly — re-validate prompts you rely on periodically.