A powerful AI-driven tool for Amazon sellers to automatically fetch and analyze product reviews using VOC.AI and Claude AI.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install amazon-review-scraper
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install amazon-review-scraper using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The Amazon Review Scraper is a developer-focused tool designed to automate Voice of Customer (VOC) research for Amazon FBA sellers and marketers. By integrating with the VOC.AI API and leveraging Claude AI for deep analysis, this skill transforms raw product reviews into actionable business intelligence. Unlike traditional scraping methods that are prone to IP blocks, this tool uses a reliable API-based approach to ensure data integrity and speed.
This Openclaw Skills integration allows users to input an ASIN and receive a comprehensive report covering sentiment distribution, top pain points, and specific optimization strategies for Amazon listings. It bridges the gap between raw data and strategic decision-making, providing a streamlined workflow for product research and competitive analysis.
Ensure you have Python 3.8+ installed. The requests library will be automatically handled on the first run. Integration with Openclaw Skills ensures a smooth setup process.
# Basic analysis (8 reviews free, English report)
bash voc.sh B08N5WRWNW
# Chinese report
bash voc.sh B08N5WRWNW --lang zh
# Save to file
bash voc.sh B08N5WRWNW --output report.md
To access more than 8 reviews, export your VOC.AI token:
export VOC_TOKEN=YOUR_TOKEN
The skill organizes its output into two primary formats: raw JSON data and a structured Markdown report. This data structure allows users to leverage Openclaw Skills for further data processing or visualization.
| Feature | Details |
|---|---|
| Sentiment | Percentage distribution of Positive, Neutral, and Negative reviews |
| Ratings | Visual bar chart representing the 1-5 star distribution and average rating |
| Pain Points | Bulleted list of common complaints with direct customer quotes |
| Selling Points | Key features highlighted by satisfied customers |
| SEO Keywords | AI-extracted keywords for backend search term optimization |
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