/Catalogue/Prompt/browser-act/browser-act-skills-amazon-product-api-skill

Origin: github

amazon-product-api-skill

This skill helps users extract structured product listings from Amazon, including titles, ASINs, prices, ratings, and specifications. Use this skill when users want to search for products on Amazon, find the best selling brand products, track price changes for items, get a list of categories with high ratings, compare different brand products on Amazon, extract Amazon product data for market research, look for products in a specific language or marketplace, analyze competitor pricing for keywords, find featured products for search terms, get technical specifications like material or color for product lists.

by browser-act · updated 1mo ago · imported from GitHub

Installs0+0/7d
Security score92/100
Retention 14d0%
GitHub stars6K

Skill logic

Execution graph
User message
Prompt rewrites behaviour
Response

SKILL.md

View on GitHub ↗

Amazon Product Search Skill

📖 Introduction

This skill utilizes BrowserAct's Amazon Product API template to extract structured product listings from Amazon search results. It provides detailed information including titles, ASINs, prices, ratings, and product specifications, enabling efficient market research and product monitoring without manual data collection.

✨ Features

  1. No Hallucinations: Pre-set workflows avoid AI generative hallucinations, ensuring stable and precise data extraction.
  2. No Captcha Issues: No need to handle reCAPTCHA or other verification challenges.
  3. No IP Restrictions: No need to handle regional IP restrictions or geofencing.
  4. Faster Execution: Tasks execute faster compared to pure AI-driven browser automation solutions.
  5. Cost-Effective: Significantly lowers data acquisition costs compared to high-token-consuming AI solutions.

🔑 API Key Setup

Before running, check the BROWSERACT_API_KEY environment variable. If not set, do not take other measures; ask and wait for the user to provide it. Agent must inform the user:

"Since you haven't configured the BrowserAct API Key, please visit the BrowserAct Console to get your Key."

🛠️ Input Parameters

The agent should configure the following parameters based on user requirements:

  1. KeyWords

    • Type: string
    • Description: Search keywords used to find products on Amazon.
    • Required: Yes
    • Example: laptop, wireless earbuds
  2. Brand

    • Type: string
    • Description: Filter products by brand name.
    • Default: Apple
    • Example: Dell, Samsung
  3. Maximum_number_of_page_turns

    • Type: number
    • Description: Number of search result pages to paginate through.
    • Default: 1
  4. language

    • Type: string
    • Description: UI language for the Amazon browsing session.
    • Default: en
    • Example: zh-CN, de

🚀 Usage

Agent should use the following independent script to achieve "one-line command result":

# Example Usage
python -u ./scripts/amazon_product_api.py "keywords" "brand" pages "language"

⏳ Execution Monitoring

Since this task involves automated browser operations, it may take some time (several minutes). The script will continuously output status logs with timestamps (e.g., [14:30:05] Task Status: running). Agent Instructions:

  • While waiting for the script result, keep monitoring the terminal output.
  • As long as the terminal is outputting new status logs, the task is running normally; do not mistake it for a deadlock or unresponsiveness.
  • Only if the status remains unchanged for a long time or the script stops outputting without returning a result should you consider triggering the retry mechanism.

📊 Data Output

Upon success, the script parses and prints the structured product data from the API response, which includes:

  • product_title: Full title of the product.
  • asin: Amazon Standard Identification Number.
  • product_url: URL of the Amazon product page.
  • brand: Brand name.
  • price_current_amount: Current price.
  • price_original_amount: Original price (if applicable).
  • rating_average: Average star rating.
  • rating_count: Total number of ratings.
  • featured: Badges like "Best Seller" or "Amazon's Choice".
  • color, material, style: Product attributes (if available).

⚠️ Error Handling & Retry

If an error occurs during script execution (e.g., network fluctuations or task failure), the Agent should follow this logic:

  1. Check Output Content:

    • If the output contains "Invalid authorization", it means the API Key is invalid or expired. Do not retry; guide the user to re-check and provide the correct API Key.
    • If the output does not contain "Invalid authorization" but the task failed (e.g., output starts with Error: or returns empty results), the Agent should automatically try to re-execute the script once.
  2. Retry Limit:

    • Automatic retry is limited to one time. If the second attempt fails, stop retrying and report the specific error information to the user.

🌟 Typical Use Cases

  1. Market Research: Search for a specific product category to analyze top brands and pricing.
  2. Competitor Monitoring: Track product listings and price changes for specific competitor brands.
  3. Product Catalog Enrichment: Extract structured details like ASINs and specifications to build or update a product database.
  4. Rating Analysis: Find high-rated products for specific keywords to identify market leaders.
  5. Localized Research: Search Amazon in different languages to analyze international markets.
  6. Price Tracking: Monitor current and original prices to identify discount trends.
  7. Brand Performance: Evaluate the presence of a specific brand in search results across multiple pages.
  8. Attribute Extraction: Gather technical specifications like material or color for a list of products.
  9. Lead Generation: Identify popular products and their manufacturers for business outreach.
  10. Automated Data Feed: Periodically pull Amazon search results into external BI tools or dashboards.

Discussion

No comments yet — start the thread.

Sign in to join the discussion.

/More from browser-act/skills

browser-act· 1mo agoCommunity
goofish-search-list

Prompts · Python · v0.1.0

Scrapes second-hand item search results from Goofish (闲鱼/xianyu, goofish.com) — China's largest second-hand marketplace. Input: keyword, optional sort/filter params. Output: list of items with id, title, price, image, location, want-count per page (30 items/page). Use when user mentions goofish, 闲鱼, xianyu, 二手交易, second-hand marketplace China, 二手商品搜索, search used goods, scrape goofish listings, xianyu search results, collect second-hand prices, monitor used item prices, 闲鱼关键词搜索, 闲鱼数据采集, 批量抓取闲鱼, goofish scraper, goofish data, xianyu data extraction, 二手商品价格监控, used iPhone prices, 二手手机价格. Also applies to: price research on Chinese second-hand market, competitor product monitoring via used goods listings, inventory analysis.

#agent-infrastructure#ai-agents#automation

0 6K
browser-act· 1mo agoCommunity
taobao-keyword-search

Prompts · Python · v0.1.0

Search Taobao and Tmall product listings by keyword, returning paginated product cards with title, price, shop, image, sales, and tags. Use when user asks to search Taobao, find products on Taobao/Tmall, scrape Taobao search results, get product listings from Taobao, collect Taobao items by keyword, 搜索淘宝, 淘宝关键词搜索, 采集淘宝商品, 抓取淘宝搜索结果, 淘宝天猫商品列表. Also applies to bulk keyword searches, price monitoring across keywords, and competitive product research on Taobao.

#agent-infrastructure#ai-agents#automation

0 6K
browser-act· 1mo agoCommunity
taobao-product-detail

Prompts · Python · v0.1.0

Fetch full product detail from a Taobao or Tmall product page by itemId, returning title, price, shop info, images, SKU variants, and product attributes. Use when user asks to get product details from Taobao, scrape a Taobao item page, extract product info by item ID, fetch Tmall product data, 抓取淘宝商品详情, 获取淘宝商品信息, 淘宝商品页面采集, 天猫商品详情, 按商品ID获取信息. Also applies to building product databases, price tracking by itemId, and product comparison research.

#agent-infrastructure#ai-agents#automation

0 6K
browser-act· 1mo agoCommunity
taobao-product-reviews

Prompts · Python · v0.1.0

Fetch customer reviews for a Taobao or Tmall product by itemId, returning reviewer name, date, purchased variant, review text, and photo URLs. Use when user asks to get product reviews from Taobao, scrape Taobao customer feedback, extract buyer reviews by item ID, collect Tmall ratings and comments, 采集淘宝商品评价, 抓取淘宝买家评论, 获取淘宝商品评论, 天猫商品评价抓取, 按商品ID获取评价. Also applies to sentiment analysis of product reviews, building review datasets, and monitoring product rating changes.

#agent-infrastructure#ai-agents#automation

0 6K