Ecommerce Reviews

Extract customer reviews from any e-commerce product page or reviews page.

Install

npx skills add browser-act/skills --skill ecommerce-reviews -g -a claude-code -y

Press to copy:C Claude CodeX CodexU CursorA Ask your agent

Repository: browser-act/skills6.3k
Category: Engineering
Updated: 2mo ago
License: MIT
Context cost: Lightabout 1,199 tokens
Runs scripts: Yes, review before use

What it does

Extract customer reviews from any e-commerce product page or reviews page. Returns reviewer name, star rating, date, review title, review body, verified purchase status, and helpful votes per review. Works on Amazon, WooCommerce, Shopify, and any site with standard review markup. Supports pagination for multi-page review sections. Use when: product reviews, customer feedback, review scraping, get reviews, sentiment analysis data, review extraction, customer ratings, extract customer opinions, product feedback, user reviews, review mining, bulk review collection, review analysis, scrape ratings and comments, ecommerce review data.

E-commerce, Product Reviews

Product URL → paginated customer reviews (reviewer, rating, date, title, body, verified, helpful votes)

Language

All process output to user (progress updates, process notifications) follows the user's language.

Objective

Extract customer reviews from any publicly accessible e-commerce product or reviews page using a multi-strategy approach (JSON-LD Review → Amazon DOM → WooCommerce DOM → generic microdata → generic CSS patterns).

Prerequisites

Target browser is open and connected
No login required for public review pages

Pre-execution Checks

1. Tool Readiness

If browser-act has been confirmed available in the current session → skip this step.

Invoke browser-act via Skill tool to load usage. If installation or configuration issues arise, follow its guidance to resolve then retry.

Capability Components

This Skill's operational boundary = what the user can manually do in their browser. It only reads data already displayed to the user on the page. JS code is encapsulated in Python files under the scripts/ directory, invoked via eval "$(python scripts/xxx.py {params})". Use the bash tool for execution.

DOM: Extract reviews from current page

Navigate to the product/reviews page first, then extract:

eval "$(python scripts/extract-reviews.py --max-reviews 20)"

Parameters:

--max-reviews: max reviews to return per page, default 20

Output example:

{
  "count": 20,
  "reviews": [
    {
      "reviewer": "John D.",
      "rating": 5.0,
      "date": "Reviewed in the United States on May 15, 2026",
      "title": "Great product, exactly as described",
      "body": "I've been using this for two weeks and it works perfectly...",
      "verified": true,
      "helpful_votes": 42
    }
  ]
}

Composite: Product URL → reviews with sort and pagination

Step 1, Navigate to reviews page:

Read the whole SKILL.md on GitHub