ecommerce-reviews
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
npx skills add browser-act/skills --skill ecommerce-reviews --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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 "$(python scripts/xxx.py {params})"`. Use the bash tool for execution. ### DOM: Extract revi
- Language
- Objective
- Prerequisites
- Pre-execution Checks
- 1. Tool Readiness
- Capability Components
- DOM: Extract reviews from current page
- Composite: Product URL → reviews with sort and pagination
- Pagination
- Success Criteria
- Known Limitations
- Execution Efficiency
- Experience Notes
eval "$(python scripts/extract-reviews.py --max-reviews 20)"
What does the ecommerce-reviews skill do?
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
How do I install it?
Run `npx skills add browser-act/skills --skill ecommerce-reviews --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From browser-act/skills, a repository with 5,160 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.