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Agent skill

Amazon Product Search Extractor

by browser-act in browser-act/skills

Pulls structured Amazon search results (titles, ASINs, prices, ratings, specifications) for a keyword and brand through BrowserAct's Amazon Product API template.

MITAuto-check passedData & Analytics

Install Amazon Product Search Extractor

skills CLI
$ npx skills add browser-act/skills --skill amazon-product-api-skill -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install browser-act/skills amazon-product-api-skill --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/browser-act/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/solutions/ecommerce/amazon-product-api-skill .claude/skills/amazon-product-api-skill && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
amazon-product-api-skill
GitHub stars
6.1k
Used in
2 other repos
Token cost
~1.5k tokens
SKILL.md length
674 words
Files
2 (incl. scripts)
Skills in repo
87
Repo updated
First seen
Licence
MIT

At a glance

Pulls structured Amazon search results (titles, ASINs, prices, ratings, specifications) for a keyword and brand through BrowserAct's Amazon Product API template.

  • Works in 5 steps: No Hallucinations: Pre-set workflows… → No Captcha Issues: No need to handle… → No IP Restrictions: No need to handle… → …
  • Comparing prices for a keyword across brands on Amazon
  • SKILL.md covers 📖 Introduction, ✨ Features, 🔑 API Key Setup and 🛠️ Input Parameters, plus 4 more sections
  • Runs Python scripts from its folder; calls python; needs BROWSERACT_API_KEY

What it does

The skill runs scripts/amazon_product_api.py, which calls BrowserAct's Amazon Product API template and returns structured listings from Amazon search results. Each record carries a title, ASIN, price, rating and product specifications, which suits market research, competitor price checks and product monitoring without collecting the data by hand.

Inputs are a required keyword, a brand filter that defaults to Apple, the number of result pages to turn through (default 1) and a browsing language that defaults to en. The task can take several minutes, and the script prints timestamped status lines while it runs. A BROWSERACT_API_KEY environment variable is required. If it is missing, the agent is told to stop and ask you to get a key from the BrowserAct console instead of trying anything else.

When your agent uses it

  • Comparing prices for a keyword across brands on Amazon
  • Collecting ASINs, ratings and specifications for market research
  • Checking how competitors price products for a search term
  • Searching Amazon in another language, such as German or Chinese

Example prompts

  • “Search Amazon for wireless earbuds from Samsung and list titles, prices and ratings.”
  • “Pull two pages of Dell laptop results with ASINs and specifications.”
  • “Find Apple laptops on Amazon in German and show me the price range.”
  • “Extract a product list for noise-cancelling headphones so I can compare ratings by brand.”

Requirements

  • Python to run scripts/amazon_product_api.py
  • A BrowserAct API key in the BROWSERACT_API_KEY environment variable

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  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.

What it can do on your machine

Read from SKILL.md and the folder at commit 11c057b. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • browseract.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • BROWSERACT_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Amazon Product Search Extractor loads about 1.5k tokens when it runs. Until then it costs about 160 tokens; SKILL.md has 674 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~160
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from browser-act/skills at commit 11c057b, republished under its MIT licence (© browser-act). 674 words, ~1,517 tokens.

Download SKILL.mdSave it as .claude/skills/amazon-product-api-skill/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
amazon-product-api-skill
description
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.

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":

bash
# 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).
Show full SKILL.md (256 more words)Show less

⚠️ 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.

© browser-act, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (scripts) in solutions/ecommerce/amazon-product-api-skill of browser-act/skills.

  • SKILL.md
  • scripts/amazon_product_api.py

Open the folder on GitHubat commit 11c057b

Used in 2 other repositories

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in browser-act/skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Amazon Product Search Extractor next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Amazon Product Search Extractor compared with similar skills
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Amazon Product Search Extractor this skillbrowser-act/skills6.1k2 repos~1.5kAutomated safety check: PassMIT
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LinkfoxagentLeoYeAI/openclaw-master-skills2.2k—~3.8kAutomated safety check: PassMIT
Competitor Analysissocial-media-skills/skills125—~1.3kAutomated safety check: PassMIT
Extractactionbook/actionbook1.6k2 repos~3.4kAutomated safety check: PassApache-2.0
Vendor Pricing Trackerfirecrawl/web-agent1.2k—~1.2kAutomated safety check: PassMIT

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Categories

Questions about Amazon Product Search Extractor

What does Amazon Product Search Extractor do?

Pulls structured Amazon search results (titles, ASINs, prices, ratings, specifications) for a keyword and brand through BrowserAct's Amazon Product API template. py, which calls BrowserAct's Amazon Product API template and returns structured listings from Amazon search results. Each record carries a title, ASIN, price, rating and product specifications, which suits market research, competitor price checks and product monitoring without collecting the data by hand.

When should I use Amazon Product Search Extractor?

Amazon Product Search Extractor fits situations like: comparing prices for a keyword across brands on Amazon; collecting ASINs, ratings and specifications for market research; checking how competitors price products for a search term; searching Amazon in another language, such as German or Chinese.

How do I install Amazon Product Search Extractor in Claude Code?

Run `npx skills add browser-act/skills --skill amazon-product-api-skill -a claude-code`. Or copy the skill folder (solutions/ecommerce/amazon-product-api-skill in browser-act/skills) into .claude/skills/amazon-product-api-skill in your project. Claude Code loads it when a task matches its description.

How do I install Amazon Product Search Extractor in Codex?

Run `npx skills add browser-act/skills --skill amazon-product-api-skill -a codex`. Or copy the skill folder (solutions/ecommerce/amazon-product-api-skill in browser-act/skills) into .agents/skills/amazon-product-api-skill in your project. Codex loads it when a task matches its description.

Can I use Amazon Product Search Extractor in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add browser-act/skills --skill amazon-product-api-skill -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/amazon-product-api-skill, .gemini/skills/amazon-product-api-skill, .github/skills/amazon-product-api-skill and .opencode/skills/amazon-product-api-skill in your project.

What does Amazon Product Search Extractor need to run?

Going by SKILL.md and its folder, Amazon Product Search Extractor needs Python for the scripts in its folder, the command-line tools its instructions call (python) and credentials named BROWSERACT_API_KEY. Our summary lists: Python to run scripts/amazon_product_api.py; A BrowserAct API key in the BROWSERACT_API_KEY environment variable.

Does Amazon Product Search Extractor access the network?

SKILL.md names 1 domain. As links in the text: browseract.com. This is read from the text; nothing was executed.

Is Amazon Product Search Extractor safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Amazon Product Search Extractor use?

Amazon Product Search Extractor is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Amazon Product Search Extractor use?

About 1.5k tokens (SKILL.md is roughly 6.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Amazon Product Search Extractor?

Skills that share tags, products or a category with Amazon Product Search Extractor: Competitor Comparison Matrix (firecrawl/web-agent, 1.2k stars), Linkfoxagent (LeoYeAI/openclaw-master-skills, 2.2k stars), Competitor Analysis (social-media-skills/skills, 125 stars) and Extract (actionbook/actionbook, 1.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Amazon Product Search Extractor?

browser-act (a GitHub organization) maintains it in browser-act/skills, which has 6,114 GitHub stars. The repository holds 87 skills in this directory. The repository was last updated on August 24, 2026.

Source: browser-act/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.