ecommerce-seller-info — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited ecommerce-seller-info (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
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 thescripts/directory, invoked viaeval "$(python scripts/xxx.py {params})". Use the bash tool for execution.
Navigate to the seller profile URL first, then extract:
eval "$(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}
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.