amazon-product-search-api-skill
This skill is designed to help users automatically extract product data from Amazon search results. The Agent should proactively apply this skill when users request searching for products related to keywords, finding best-selling items from specific brands, monitoring product prices and availability on Amazon, extracting product listings for market research, collecting product ratings and review counts for competitive analysis, finding specific products with a maximum count, searching Amazon in different languages for localized results, tracking monthly sales estimates for brand products, gathering product URLs and titles for a product catalog, scanning Amazon for Best Seller tags in a specific category, monitoring shipping and delivery information for brand items, building a structured dataset of Amazon search results.
适合你,如果需要在亚马逊上批量获取商品信息用于市场分析。
用别的 agent?下载 .zip 解压,把文件夹放进它的技能目录
~/.claude/skills/(项目级 .claude/skills/)~/.codex/skills/npx oh-my-skill add browser-act/skills/amazon-product-search-api-skillcurl -fsSL https://oh-my-skill.com/install.sh | bash -s -- browser-act/skills/amazon-product-search-api-skillnpx oh-my-skill verify browser-act/skills/amazon-product-search-api-skill怎么用
商店整理自技能原文 · 版本 51daea1 · 表述以原文为准安装后,Claude 能根据你的指令自动从亚马逊搜索结果中提取产品数据,包括标题、价格、评分、销量、配送信息等,并以结构化列表返回。
当你要求搜索亚马逊上的产品、查询特定品牌的热销商品、监控价格或可用性、进行市场调研或竞品分析时触发。
技能原文 SKILL.md
Amazon Product Search Automation Skill
📖 Introduction
This skill provides a one-stop product data collection service through BrowserAct's Amazon Product Search API template. It directly extracts structured product results from Amazon search lists. Simply input search keywords, brand filters, and quantity limits to get clean, usable product data.
✨ Features
- No Hallucinations: Pre-set workflows avoid AI generative hallucinations, ensuring stable and precise data extraction.
- No Captcha Issues: No need to handle reCAPTCHA or other verification challenges.
- No IP Restrictions: No need to handle regional IP restrictions or geofencing.
- Faster Execution: Tasks execute faster compared to pure AI-driven browser automation solutions.
- 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
When calling the script, the Agent should flexibly configure the following parameters based on user needs:
- KeyWords (Search Keywords)
- Type:
string - Description: The keywords the user wants to search for on Amazon.
- Example:
phone,wireless earbuds,laptop stand
- Brand (Brand Filter)
- Type:
string - Description: Filter products by brand name shown in the listing.
- Example:
Apple,Samsung,Sony
- Maximum_date (Maximum Products)
- Type:
number - Description: The maximum number of products to extract across paginated search results.
- Default:
50
- language (UI Language)
- Type:
string - Description: UI language for the Amazon browsing session.
- Options:
en,de,fr,it,es,ja,zh-CN,zh-TW - Default:
en
🚀 Usage
The Agent should execute the following independent script to achieve "one-line command result":
# Example Call python -u ./scripts/amazon_product_search_api.py "Keywords" "Brand" Quantity "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
After successful execution, the script will parse and print results directly from the API response. Results include:
product_title: Product nameproduct_url: Detail page URLrating_score: Average star ratingreview_count: Total number of reviewsmonthly_sales: Estimated monthly sales (if available)current_price: Current selling pricelist_price: Original list price (if available)delivery_info: Delivery or fulfillment informationshipping_location: Shipping origin or locationis_best_seller: Whether marked as Best Selleris_available: Whether available for purchase
⚠️ Error Handling & Retry
If an error occurs during script execution (e.g., network fluctuations or task failure), the Agent should follow this logic:
- 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 withError:or returns empty results), the Agent should automatically try to re-execute the script once.
- 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
- Market Research: Search for "wireless earbuds" from "Sony" to analyze the current market.
- Competitive Monitoring: Track "Samsung" phone prices and availability on Amazon.
- Catalog Discovery: Gather product titles and URLs for a new product catalog in the "laptop stand" category.
- Localized Analysis: Search Amazon in "ja" (Japanese) to understand products available in the Japan region.
- Best Seller Tracking: Identify products marked as "Best Seller" for a specific brand.
- Pricing Intelligence: Compare
current_priceandlist_priceto monitor discounts. - Sales Trend Estimation: Use
monthly_salesdata to estimate market demand for certain items. - Shipping Efficiency Study: Analyze
delivery_infoandshipping_locationfor various brands. - Large-scale Data Extraction: Collect up to 100 products for a comprehensive dataset.
- Product Availability Check: Verify if specific brand products are currently
is_availablefor purchase.