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amazon-product-search-api-skill

@browser-act · 收录于 1 周前 · 上游提交 2 天前

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。

/ 下载安装
amazon-product-search-api-skill.skill双击,或拖进 Claude 桌面版 / Cowork,即完成安装↓ .skill↓ .zip
用别的 agent?下载 .zip 解压,把文件夹放进它的技能目录
Claude Code~/.claude/skills/(项目级 .claude/skills/)
Codex CLI~/.codex/skills/
Cursor自动读取上面两处目录
其他工具见其文档的「skills」目录;两个下载是同一份文件,只是名字不同
/ 通过 npx 安装 校验哈希
npx oh-my-skill add browser-act/skills/amazon-product-search-api-skill
/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- browser-act/skills/amazon-product-search-api-skill
/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify browser-act/skills/amazon-product-search-api-skill
安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。
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怎么用

商店整理自技能原文 · 版本 51daea1 · 表述以原文为准
它做什么

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。

什么时候触发

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。

装好后可以这样说
Claude 会调用技能搜索并返回产品列表。
Claude 会提取价格和可用性信息。
Claude 会以日语界面搜索并返回本地化结果。
技能原文 SKILL.md作者撰写 · MIT · 51daea1

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
  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

When calling the script, the Agent should flexibly configure the following parameters based on user needs:

  1. KeyWords (Search Keywords)
  2. Type: string
  3. Description: The keywords the user wants to search for on Amazon.
  4. Example: phone, wireless earbuds, laptop stand
  1. Brand (Brand Filter)
  2. Type: string
  3. Description: Filter products by brand name shown in the listing.
  4. Example: Apple, Samsung, Sony
  1. Maximum_date (Maximum Products)
  2. Type: number
  3. Description: The maximum number of products to extract across paginated search results.
  4. Default: 50
  1. language (UI Language)
  2. Type: string
  3. Description: UI language for the Amazon browsing session.
  4. Options: en, de, fr, it, es, ja, zh-CN, zh-TW
  5. 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 name
  • product_url: Detail page URL
  • rating_score: Average star rating
  • review_count: Total number of reviews
  • monthly_sales: Estimated monthly sales (if available)
  • current_price: Current selling price
  • list_price: Original list price (if available)
  • delivery_info: Delivery or fulfillment information
  • shipping_location: Shipping origin or location
  • is_best_seller: Whether marked as Best Seller
  • is_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:

  1. Check Output Content:
  2. 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.
  3. 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.
  1. Retry Limit:
  2. 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 "wireless earbuds" from "Sony" to analyze the current market.
  2. Competitive Monitoring: Track "Samsung" phone prices and availability on Amazon.
  3. Catalog Discovery: Gather product titles and URLs for a new product catalog in the "laptop stand" category.
  4. Localized Analysis: Search Amazon in "ja" (Japanese) to understand products available in the Japan region.
  5. Best Seller Tracking: Identify products marked as "Best Seller" for a specific brand.
  6. Pricing Intelligence: Compare current_price and list_price to monitor discounts.
  7. Sales Trend Estimation: Use monthly_sales data to estimate market demand for certain items.
  8. Shipping Efficiency Study: Analyze delivery_info and shipping_location for various brands.
  9. Large-scale Data Extraction: Collect up to 100 products for a comprehensive dataset.
  10. Product Availability Check: Verify if specific brand products are currently is_available for purchase.
按 MIT 许可原样转载,未经改动 · 在 GitHub 查看 →

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