amazon-product-detail
Amazon product detail page scraper: extract full product data from any open Amazon product detail URL (any /dp/{asin} or /gp/product/{asin} page across all Amazon regional TLDs) — returns asin, url, title, brand, price, listPrice, stars, reviewsCount, starsBreakdown (5/4/3/2/1 star percentages), answeredQuestions, inStock, inStockText, delivery, fastestDelivery, returnPolicy, breadCrumbs, features (bullet points), description, bookDescription, thumbnailImage, highResolutionImages, galleryThumbnails, productOverview (Brand/Model/etc.), attributes (tech spec table), attributesMapped (flat key-value), bestsellerRanks (rank + category + url), variantAttributes (currently selected color/size/style), variantAsins, seller (name + id + url), isAmazonChoice, amazonChoiceText, monthlyPurchaseVolume, hasAPlusContent, hasBrandStory, aiReviewsSummary, reviewsLink, productPageReviews (sample), videosCount, locationText, loadedCountryCode. Works on amazon.com, amazon.co.uk, amazon.de, amazon.co.jp, amazon.fr, amazon.it, amazon.es, amazon.ca, amazon.com.au, amazon.in, amazon.com.mx, amazon.com.br, amazon.nl, amazon.se, amazon.sg, amazon.ae, amazon.sa, amazon.pl, amazon.tr, amazon.eg. Use when user mentions Amazon product page, Amazon /dp/, Amazon dp URL, Amazon ASIN scraper, Amazon product detail, Amazon PDP, Amazon product data, Amazon product info, Amazon product fields, Amazon product attributes, Amazon full field extraction, Amazon per-ASIN enrichment, Amazon rating breakdown, Amazon stars breakdown, Amazon bestseller rank, Amazon BSR, Amazon variants, Amazon variant ASINs, Amazon color size options, Amazon feature bullets, Amazon A+ content, Amazon brand story, Amazon AI review summary, Amazon bought in past month, Amazon monthly sales volume, Amazon Amazon's Choice badge, Amazon seller info, scrape Amazon product, enrich Amazon ASIN, Amazon ASIN details, Amazon product review data. Also applies to bulk ASIN enrichment from a list of URLs, competitive product research, brand catalog audits, price and stock monitoring per ASIN, and building a normalized product dataset from a list of Amazon URLs.
git clone --depth 1 https://github.com/browser-act/skills /tmp/amazon-product-detail && cp -r /tmp/amazon-product-detail/solutions/ecommerce/amazon-product-detail ~/.claude/skills/amazon-product-detailSKILL.md
# Amazon — Product Detail
> Input any Amazon product URL → output full product record (100+ fields).
## Language
All process output to user (progress updates, process notifications) follows the user's language.
## Objective
Extract the complete product record from any Amazon detail page URL across all Amazon regional TLDs, including price, ratings breakdown, attributes, variants, bestseller ranks, seller info, delivery, and sample reviews.
## Prerequisites
- Target page is already open in the browser: any Amazon product URL (e.g. `https://www.amazon.com/dp/{ASIN}`, `https://www.amazon.com/gp/product/{ASIN}`, `https://www.amazon.co.uk/dp/{ASIN}`, or the canonical SEO-slug URL `https://www.amazon.com/{slug}/dp/{ASIN}`)
- No login required
## 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, never bypassing authentication or access controls. Its role is equivalent to copy-pasting on the user's behalf — the data is already on screen, automation merely saves time. JS code is encapsulated in Python files under the `scripts/` directory, invoked via `browser-act --session {name} eval "$(python scripts/xxx.py {params})"`. The `$(...)` is bash command substitution — it runs the python script, captures its printed JS text, and hands that JS string as a single argument to `browser-act eval`. Do not run `eval "$(python ...)"` as a bare shell command; that would ask bash to execute the JS as shell, which fails.
### DOM: extract full product detail from current product page
Amazon detail pages are server-rendered HTML — no XHR/fetch API for detail data. All fields come from stable DOM selectors:
1. `navigate {any Amazon product URL, e.g. https://www.amazon.com/dp/{ASIN}}`
2. `wait stable`
3. Extract: `browser-act --session {name} eval "$(python scripts/extract-product-detail.py)"`
On error paths, the script returns:
- `{"error": true, "message": "product_not_found: 404 page"}` when the URL resolves to Amazon's not-found page
- `{"error": true, "message": "productTitle not found - page may not be a product detail page"}` when the URL resolves to a non-detail page (e.g. search results, homepage)
Output example:
```json
{
"asin": "B09S3HNMHF", // parsed from /dp/{ASIN} or /gp/product/{ASIN} path segment
"url": "https://www.amazon.com/dp/B09S3HNMHF", // canonical origin + pathname
"title": "Samsung 14\" Galaxy Chromebook Go ...", // #productTitle
"brand": "Samsung", // #bylineInfo, falls back to attributesMapped.Brand/Manufacturer
"price": {"value": 179.99, "currencyRaw": "$", "raw": "$179.99"}, // current buybox price, null when no offer
"listPrice": {"value": 190.99, "currencyRaw": "$", "raw": "$190.99"}, // strike-through list price, null when absent
"stars": 4.3, // 0-5 average rating, null when no reviews
"reviewsCount": 632, // total review count, null when no reviews
"starsBreakdown": {"5 star": 70, "4 star": 13, "3 star": 5, "2 star": 3, "1 star": 9}, // percentage per star bucket
"answeredQuestions": null, // number, null when absent or non-numeric
"inStock": true, // derived from availability text, null when unclear
"inStockText": "In Stock", // raw #availability text
"delivery": "FREE delivery Wednesday, July 15", // primary delivery message, null when absent
"fastestDelivery": null, // secondary/fastest delivery, null when absent
"returnPolicy": "30-day return period", // null when absent
"breadCrumbs": "Electronics > Computers > Laptops > Traditional Laptops", // joined with ' > ', "" when absent
"features": ["Slim design", "12-hour battery", "..."], // #feature-bullets bullet points
"description": "A+ in performance and value...", // #productDescription, null when absent
"bookDescription": null, // #bookDescription_feature_div for books, null otherwise
"thumbnailImage": "https://m.media-amazon.com/images/I/51...jpg",
"highResolutionImages": ["https://m.media-amazon.com/images/I/51...SY450_.jpg", "..."], // from #imgTagWrapperId data-a-dynamic-image JSON
"galleryThumbnails": ["https://m.media-amazon.com/images/I/41...jpg", "..."],
"productOverview": [{"key": "Brand", "value": "Samsung"}, {"key": "Model Name", "value": "XE340XDA-KA2US"}], // #productOverview_feature_div table
"attributes": [{"key": "Color", "value": "Silver"}, {"key": "Item Weight", "value": "3.2 pounds"}], // technical spec tables
"attributesMapped": {"Brand": "Samsung", "Item Weight": "3.2 pounds"}, // flat merged key-value
"bestsellerRanks": [
{"rank": 44, "category": "Computers & Accessories", "url": "https://www.amazon.com/gp/bestsellers/pc/..."},
{"rank": 5, "category": "Traditional Laptop Computers", "url": "https://www.amazon.com/gp/bestsellers/pc/13896615011/..."}
],
"variantAttributes": [{"key": "Color", "value": "Silver"}], // currently selected variant dimensions
"variantAsins": ["B09S3HNMHF", "B0G4WBD45V", "B0GG2CPM1K"], // all variant ASINs from swatches, empty [] when no variants
"seller": {"name": "Amazon.com", "id": "ATVPDKIKX0DER", "url": "https://www.amazon.com/sp?seller=..."}, // null when no seller link
"isAmazonChoice": false, // .ac-badge-rectangle presence
"amazonChoiceText": null, // Amazon's Choice label text, null when badge absent
"monthlyPurchaseVolume":Extracts comprehensive wholesale product data from 1688.com product detail pages: title, tiered pricing, SKU variants with dimensions/weight, product images, seller info, shop scores, buyer protection, cross-border flags, product attributes, coupon/promotion data, and review stats. Use when user mentions 1688, 1688.com, wholesale China, alibaba wholesale, B2B China sourcing, Chinese wholesale scraper, 1688 product scrape, 1688 offer, 1688 detail, extract 1688 data, pull 1688 listings, get wholesale price, 1688 supplier info, factory stats 1688, 1688 SKU variants, 1688 product attributes, 1688 shop score, DSR score 1688, 1688 buyer protection, 1688 cross-border, 1688 dropship. Also applies to: scraping bulk product data from 1688 by offer ID list, monitoring 1688 supplier metrics, extracting 1688 pricing tiers for resale analysis.
Fetches complete Airbnb listing details for a given numeric listing ID via the internal GraphQL API, returning title, room type, description, amenities, photos, coordinates, city, house rules, highlights, ratings, review count, bedroom configuration, and property overview. Use when user mentions Airbnb listing details, Airbnb property info, Airbnb room details, get Airbnb listing data, Airbnb amenities list, Airbnb house rules, Airbnb property description, Airbnb detail page scraper, Airbnb rooms detail, Airbnb property page data, Airbnb listing info, fetch Airbnb room details, pull Airbnb listing.
Extracts Airbnb accommodation search results from a destination query via SSR-embedded data, returning listing ID, URL, name, coordinates, rating, price, photos, and badge info for each result, plus pagination cursors for multi-page retrieval. Use when user mentions Airbnb search results, Airbnb listings, vacation rental search, short-term rental listings, scrape Airbnb, get Airbnb data, find rentals on Airbnb, Airbnb destination search, Airbnb property list, Airbnb stays search, Airbnb accommodation results, pull Airbnb listings, collect Airbnb search data, Airbnb scraper, Airbnb search page extraction, Airbnb search by destination.
Amazon Alexa for Shopping Q&A automation: submits questions to Amazon's Alexa/Rufus AI shopping assistant and collects response text; supports optional keyword search context (navigate to search results page before asking for category-specific answers). Use when user mentions Amazon Alexa, Rufus, Amazon shopping assistant, Amazon AI chat, ask Amazon, Amazon Q&A, automate Alexa questions, Rufus chatbot, Amazon assistant automation, collect Alexa responses, bulk question submission to Amazon, keyword search context, category research. Also applies to extracting Amazon product recommendations from conversational AI, automating repeated queries to Amazon's AI shopping feature, collecting Alexa shopping responses at scale, or market research within a specific product category.
This skill helps users extract structured product details from Amazon using a specific ASIN (Amazon Standard Identification Number). Use this skill when the user asks to get Amazon product details by ASIN, lookup Amazon product title and price using ASIN, extract Amazon product ratings and reviews count for a specific ASIN, check Amazon product availability and current price, get Amazon product description and features via ASIN, enrich product catalog with Amazon data using ASIN, monitor Amazon product price changes for specific ASINs, retrieve Amazon product brand and material information, fetch Amazon product images and specifications by ASIN, validate Amazon ASIN and get product metadata.
This skill helps users extract structured best-selling product data from Amazon via the BrowserAct API. Agent should proactively apply this skill when users express needs like search for best selling products on Amazon, extract Amazon product data based on keywords, find top rated Amazon products, monitor Amazon competitor prices and sales, discover trending products on Amazon marketplace, extract Amazon product titles prices and ratings, gather Amazon product sales volume for market research, search Amazon best sellers in specific region, collect Amazon product reviews and promotion details, analyze Amazon product availability and badges, get Amazon product data for market analysis.
Amazon Best Sellers listing scraper: extract product cards from any Amazon Best Sellers (zgbs) or /gp/bestsellers/ category page — returns rank (position on chart), asin, title, url, image, imageAlt, price, stars, reviewCount, ratingRaw per item, plus category metadata (categoryName, categoryFullName, categoryUrl) and pagination state (currentPage, hasNextPage, nextPageUrl). Works across all Amazon regional TLDs (amazon.com, amazon.co.uk, amazon.de, amazon.co.jp, amazon.fr, amazon.it, amazon.es, amazon.ca, amazon.com.au, amazon.in, etc.). Use when user mentions Amazon Best Sellers, Amazon bestsellers, Amazon top 100, Amazon zgbs, Amazon /zgbs/, Amazon /gp/bestsellers/, Amazon Best Sellers Rank, Amazon BSR, Amazon top ranked products, Amazon top-selling products, Amazon chart, Amazon category ranking, Amazon best sellers by category, Amazon best sellers electronics, Amazon best sellers kitchen, Amazon best sellers toys, scrape Amazon bestsellers, extract Amazon top 100, Amazon rank scraper, Amazon best seller list, Amazon leaderboard, Amazon trending products, discover trending Amazon products, Amazon niche discovery, Amazon top ranked ASINs. Also applies to competitive intelligence via ranking snapshots, spotting up-and-coming products, sourcing bestseller ASINs for further enrichment, tracking rank changes over time, and building bestseller-per-category datasets.
This skill helps users extract basic product details other sellers prices and seller ratings from Amazon via ASIN automatically using the BrowserAct API. Agent should proactively apply this skill when users express needs like query Amazon buy box information, monitor Amazon product prices, extract Amazon product details by ASIN, check other sellers prices on Amazon, get Amazon seller ratings and feedback count, monitor buy box ownership for a specific ASIN, track Amazon fulfillment methods for competitors, compare Amazon product prices across different sellers, retrieve Amazon buy box availability status, analyze Amazon seller profile details.