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Get Started Free →browser-act/ecommerce-listing
Extract product list from any e-commerce category page, search results page, or keyword search with filters. Returns paginated product arrays with URL, name, price, currency, image, rating, review count per item. Supports URL input, keyword search, and site-scoped search with filters: price range, brand, category, minimum rating, in-stock only, and sort order. Works on Amazon, eBay, Walmart, Shopify collections, WooCommerce shops, Google Shopping, and any public product listing page.
Passed 14 of 19 test cases with the skill, and 5 of 19 without it.
and 10 more in the full report
11 fixed6 passed either way6 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 11 test cases the skill fixed. Same model, same prompt, with and without the skill.
What exact string is appended to Amazon's `rh` parameter to filter products with a 3-star rating or higher?
| Checked | Without skill | With skill |
|---|---|---|
| Appends avg_customer_review:three-and-above. | Missed | Passed |
The instructions your model reads when the skill loads.
Category/search URL or keyword + filters → paginated product list (URL, name, price, image, rating per item)
All process output to user (progress updates, process notifications) follows the user's language.
Extract a structured list of products from any e-commerce category, search results, or keyword search page, with support for price/brand/rating filters and multi-page pagination.
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 viaeval "$(python scripts/xxx.py {params})". Use the bash tool for execution.
Navigate to the listing/search page first, then extract:
eval "$(python scripts/extract-listing.py --max-results 20)"
Parameters:
--max-results: max items to return per page, default 20test cases passed, vs 5 / 19 without
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