A high-precision Amazon product research automation skill that performs cross-platform data verification, image-based sourcing, and comprehensive financial margin analysis.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install amazon-deep-research-v4
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install amazon-deep-research-v4 using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Amazon Deep Selection V4 (Multi-Platform)?
Amazon Deep Selection V4 is a sophisticated AI agent skill designed for professional e-commerce sellers. It eliminates guesswork by cross-referencing data from AMZScout, Xiyouzhaoci, SellerSprite, and Amazon's official product pages. This skill automates the entire research pipeline, from identifying high-potential ASINs to performing real-time currency conversion and 1688 image-based supplier matching. By integrating these tools within Openclaw Skills, users can ensure their product selection is backed by empirical data and verified sourcing options, significantly reducing the risk of manual data entry errors or outdated estimations.
Amazon Deep Selection V4 (Multi-Platform) Use Cases
- Identifying high-margin Amazon products with verified sales and fee data from multiple authority sources.
- Finding direct Chinese suppliers on 1688 using visual search to avoid middleman costs and ensure product accuracy.
- Performing automated WIPO IP audits to mitigate trademark and patent risks before product launch.
- Generating professional, shareable HTML market analysis reports with detailed 7-point margin breakdowns.
How Amazon Deep Selection V4 (Multi-Platform) Works
- The skill fetches the latest USD/CNY exchange rate via web search on Yahoo Finance to ensure all financial modeling is current.
- It scrapes multi-platform data including BSR, monthly sales, FBA fees, and traffic scores (Natural vs. Ad) for a specific ASIN or category.
- The system performs an image-based search on air.1688.com using the Amazon main image to find exact manufacturer matches.
- A Python-based 7-item margin analysis is executed, calculating costs including sourcing, logistics (¥15/kg base), customs duties, FBA fees, returns, and TACOS.
- The product undergoes a mandatory 5-step WIPO IP compliance audit, checking trademarks and patents through Global Brand DB and Google Patents.
- A final, interactive HTML report is generated, filtering out any products that fail to meet the 20% margin threshold or represent a high IP risk.
Amazon Deep Selection V4 (Multi-Platform) Setup
To deploy this skill within your environment, ensure your agent has access to the required web search and browser tools. If using private data from platforms like SellerSprite, ensure your browser session is authenticated.
# No specific CLI installation required beyond your Openclaw Skills environment.
# The skill leverages built-in Python and Browser agents.
Amazon Deep Selection V4 (Multi-Platform) Data Schema & Taxonomy
The skill organizes its findings into a structured directory for easy auditing and review:
| File Path | Description | Data Type |
|---|---|---|
data/multi_platform.json |
Aggregated data from AMZScout, Xiyouzhaoci, and SellerSprite | JSON |
data/1688_matches.json |
Top supplier matches with pricing and product links | JSON |
data/qualified.json |
Filtered product list meeting the ≥20% margin criteria | JSON |
data/ip_audit.json |
Compliance results including risk ratings (Low/Medium/High) | JSON |
output/amazon-research-v4.html |
The final visualization report for stakeholders | HTML |
Amazon Deep Selection V4 (Multi-Platform) Advanced Features
- Image-to-Image Matching: Uses Amazon main image URLs to query 1688, bypassing the inaccuracies of keyword-based sourcing.
- Real-Time FX Integration: Dynamic exchange rate fetching ensures profit calculations are never based on stale data.
- Comprehensive Margin Logic: Includes a 7-point deduction system covering everything from head-trip freight to advertising TACOS.
- Automated IP Guardrails: Mandatory 5-step audit process that automatically disqualifies high-risk items from the final report.
- Cross-Platform Data Reconciliation: Intelligent logic to pick the most authoritative source for specific data points (e.g., using Amazon Official for dimensions but AMZScout for FBA fees).
SKILL.md
Loading
Related Openclaw Skills
Xu Jiayin Perspective v2.0
A strategic simulation skill for analyzing high-leverage business models and identifying corporate risk signals through the lens of the Evergrande framework.
Xiong Xiaoge Perspective v2.0
A sophisticated cognitive operating system that emulates the investment logic, pioneering spirit, and strategic vision of IDG Capital founder Xiong Xiaoge.
Wang Wei Perspective v2.0 (SF Express Founder Mindset)
A strategic mindset simulation of S.F. Express founder Wang Wei, focusing on direct-management, technology-driven logistics, and long-term business value.
Hot Springs Skill
A specialized CLI-driven skill for locating and booking natural hot springs, onsens, and thermal baths with real-time pricing.
Smart Data Harvester
An automated data collection and processing engine designed for seamless integration within the OpenClaw ecosystem.
Multi-Stop Flight Planner
A professional CLI-driven travel agent that automates the discovery and booking of complex multi-city flight itineraries with real-time pricing.
Featured*
