Agent skill · Data & Analytics

amazon-best-selling-products-finder-api-skill

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,

browser-actgithub.com/browser-actGitHub ↗
claude-codecodexcursorships scriptsMIT
Install
npx skills add browser-act/skills --skill amazon-best-selling-products-finder-api-skill --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 6 KB
Bundled scripts: yes
Path: solutions/ecommerce/amazon-best-selling-products-finder-api-skill/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 5,160
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Amazon Best Selling Products Finder API Skill ## 📖 Skill Introduction This skill provides users with a one-stop product data extraction service using the BrowserAct Amazon Best Selling Products Finder API template. It can directly extract structured best-selling product data from Amazon. By inputting search keywords, data limit, and marketplace URL, you can easily get clean and usable product data including titles, prices, ratings, reviews, sales volume, and promotional details. ## ✨ Features 1. **No hallucinations, ensuring stable and precise data extraction**: Preset workflows avoid AI generative hallucinations. 2. **No CAPTCHA issues**: No need to handle reCAPTCHA or other verification challenges. 3. **No IP access restrictions and geofencing**: No need to handle regional IP restrictions. 4. **More agile execution speed**: Compared to pure AI-driven browser automation solutions, task execution is faster. 5. **Extremely high cost-effectiveness**: Significantly reduces data acquisition costs compared to AI solutions that consume a large number of Tokens. ## 🔑 API Key Guide Flow Before running, first check the `BROWSERACT_API_KEY` environment variable. If it is not set, do not

What's inside
Steps it walks through
  1. 📖 Skill Introduction
  2. ✨ Features
  3. 🔑 API Key Guide Flow
  4. 🛠️ Input Parameters
  5. 🚀 Call Method (Recommended)
  6. ⏳ Running Status Monitoring
  7. 📊 Data Output Description
  8. ⚠️ Error Handling & Retry Mechanism
  9. 🌟 Typical Use Cases
Ships with 1 file
  • scripts/amazon_best_selling_products_finder_api.py
Commands it runs
Call example
python -u ./scripts/amazon_best_selling_products_finder_api.py "search keywords" limit "marketplace_url"
More from skills
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About this skill
What does the amazon-best-selling-products-finder-api-skill skill do?

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,

How do I install it?

Run `npx skills add browser-act/skills --skill amazon-best-selling-products-finder-api-skill --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From browser-act/skills, a repository with 5,160 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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