An automated utility for extracting structured product data and pagination status from Amazon search results and category browse pages.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install amazon-search-listing
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install amazon-search-listing using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The Amazon Search & Category Listing scraper is a structured data extraction utility designed to capture product listings directly from Amazon Search Engine Results Pages (SERPs) and category browse pages. Operating directly within an active browser session via browser-act, this tool reads client-side DOM elements to capture real-time product catalogs. This utility belongs to the collection of Openclaw Skills, helping developers write resilient automation scripts for browser-based tasks.
Unlike traditional raw HTTP scrapers, this approach processes the actual rendered HTML. It extracts essential fields like ASINs, pricing, reviews, and badges while preserving localized rendering factors such as delivery options and local currency based on the browser's active session.
To deploy this skill in your project workspace, ensure you have browser-act and a Python runtime available.
browser-act --session default eval "console.log('Session ready')"
mkdir -p scripts
# Place extract-search-results.py into the scripts/ directory
mkdir -p browser-act-skill-forge-memories
touch browser-act-skill-forge-memories/amazon-scraper-amazon-search-listing.memory.md
The utility generates a structured JSON output reflecting the extracted SERP state:
| Property | Type | Description |
|---|---|---|
currentPage |
number | Present page index returned from the pagination widget. |
hasNextPage |
boolean | True if a valid next page exists in the pagination controls. |
nextPageUrl |
string | Full, absolute URL targeting the next page, or null. |
totalResultsApprox |
number | Approximated search results count parsed from the page header. |
items |
array | Array containing individual extracted product card objects. |
Each item within the items array follows this schema:
| Field | Type | Description |
|---|---|---|
asin |
string | Unique 10-character Amazon Standard Identification Number. |
positionIndex |
number | Ordinal layout position parsed from the data-index attribute. |
title |
string | Clear-text product title parsed from the search result heading. |
url |
string | Absolute canonical product detail page URL. |
image |
string | Direct asset URL for the primary product search thumbnail. |
price |
object | Contains value (float), currencyRaw (string), and raw (string). |
listPrice |
object | Contains MSRP/list price attributes, or null if not applicable. |
stars |
number | Numeric average star rating parsed out of 5.0. |
reviewCount |
number | Total count of customer reviews, or null if unrated. |
isSponsored |
boolean | Indicates whether the listing is an advertisement placement. |
Loading
A browser automation skill designed to extract customer reviews, buyer options, and photo attachments from Taobao and Tmall product pages.

A structured AI agent pipeline for generating emotionally-driven, high-velocity short-form video content featuring consistent virtual avatars.

A real-time Chinese web search skill for AI agents, leveraging the 360 search engine to deliver local news, policies, and market data.

Sector Opening Note uses Openclaw Skills to research current HK tech headlines and turn them into a concise daily pre-market brief.

Extract any open Amazon product page into a normalized 100+ field JSON record with Openclaw Skills.

Openclaw Skills turns Amazon Best Sellers pages into structured rankings, product metadata, and pagination-ready datasets for analysis.








































