Extract seller or merchant profile data from marketplace platform seller pages. Returns seller name, rating, review count, positive feedback percentage, joined date, and return policy. Works on Amazon seller pages, eBay seller pages, and any e-commerce site with seller profiles. Use when: seller information, merchant profile, seller rating, marketplace seller data, seller details, vendor profile, store information, seller feedback, merchant rating, seller review count, get seller info, ebay seller page, amazon seller profile, marketplace vendor analysis, seller research.
npx skills add https://github.com/browser-act/skills --skill ecommerce-seller-info
> Seller/merchant profile URL → seller name, rating, review count, feedback, joined date, return policy
All process output to user (progress updates, process notifications) follows the user's language.
Extract seller profile information from marketplace platform seller or storefront pages using JSON-LD structured data and platform-specific DOM patterns.
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.
> 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 "$(python scripts/xxx.py {params})". Use the bash tool for execution.
Navigate to the seller profile URL first, then extract:
eval "$(python scripts/extract-seller.py)"
Output example:
{
"url": "https://www.amazon.com/shops/seller/A1234567890",
"name": "TechGadgets Store",
"description": "Premium electronics accessories since 2015",
"rating": 4.8,
"review_count": 12450,
"positive_feedback_pct": "98% positive feedback",
"joined": "Member since: January 2015",
"return_policy": "30-day returns accepted",
"image": null,
"_platform": "amazon"
}
Amazon seller pages follow these URL patterns:
| Seller page type | URL |
|-----------------|-----|
| Seller storefront | https://www.amazon.com/shops/{seller_id} |
| Seller feedback (from product page) | Click "Sold by {seller_name}" link on a product page |
| Third-party seller ratings | https://www.amazon.com/gp/seller/{seller_id}/ref=dp_byline_sr |
To find a seller from a product page:
wait stableeval "document.querySelector('#sellerProfileTriggerId, #merchant-info a')?.href" to get the seller URLnavigate {seller_url} → wait stableeval "$(python scripts/extract-seller.py)"| Seller page type | URL |
|-----------------|-----|
| eBay seller storefront | https://www.ebay.com/str/{seller_username} |
| eBay seller feedback | https://www.ebay.com/usr/{seller_username} |
To find seller from an eBay listing:
wait stableeval "document.querySelector('.x-sellercard-atf__data a[href*=\"/usr/\"]')?.href" to get seller URLresult.name != null
https://www.amazon.com first on fresh sessions to avoid bot detectionhttps://www.ebay.com firstPath: {working-directory}/browser-act-skill-forge-memories/ecommerce-scraper-ecommerce-seller-info.memory.md
Before execution: If the file exists, read it first — it records unexpected situations encountered during past executions; adjust strategy order accordingly.
After execution: If an unexpected situation is encountered (strategy became ineffective, page redesigned, anti-scraping upgraded, better path discovered), append a line:
{YYYY-MM-DD}: {what happened} → {conclusion}
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Take browser-act/ecommerce-seller-info from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.