
E-commerce Product Detail
FreeEffortlessly extract product data from e-commerce sites.
Free · Opens the source repo
What E-commerce Product Detail does
The E-commerce Product Detail skill enables users to extract comprehensive product information from various e-commerce platforms. By simply providing a product URL, keyword, or identifier like SKU/ASIN/EAN/UPC, users can retrieve essential details such as product name, price, brand, images, description, stock availability, ratings, and more. This skill operates on a wide range of sites including popular platforms like Amazon, eBay, Walmart, and Shopify, making it a versatile tool for anyone involved in product research or data collection.
The extraction process utilizes a multi-layer strategy that prioritizes structured data formats like JSON-LD, followed by platform-specific DOM scraping, and finally, Open Graph meta tags. This ensures that the most accurate and relevant product details are captured. Users can initiate the extraction by navigating to the desired product page and executing a simple command in the terminal. The output is formatted in JSON, making it easy to integrate with other applications or workflows.
This skill is particularly useful for developers, data analysts, and e-commerce professionals who need to gather product information for comparison, cataloging, or monitoring purposes. It allows for efficient data scraping without the need for complex setups or extensive coding knowledge. Additionally, the skill is designed to handle common challenges such as bot detection and site-specific navigation requirements, providing a robust solution for product data extraction.
While the skill is powerful, it does have limitations, such as potential CAPTCHA challenges on sites like Amazon and eBay, which may require additional navigation steps. Users should also be aware that some product data may not be available if a site requires login for pricing or stock information. Overall, this skill streamlines the process of obtaining product details, making it an essential tool for e-commerce data extraction.
When to use it
Use this skill when you need to scrape product details from e-commerce pages for research, comparison, or cataloging.
When not to use it
Avoid using this skill for private product pages that require login or for sites that heavily rely on client-side JavaScript rendering.
What you can build with it
Product Research
Quickly gather product details from various e-commerce sites for market analysis or competitor research.
Price Monitoring
Regularly check and compare prices across multiple platforms to find the best deals.
Cataloging Products
Efficiently compile product information into a database for inventory management or online catalogs.
How to install E-commerce Product Detail
View source1. Install with the skills CLI
npx skills add browser-act/skills/ecommerce-product-detail --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by browser-actE-commerce — Product Detail
Product URL / keyword / SKU → complete product data (name, price, brand, images, identifiers, availability, rating, variants)
Language
All process output to user (progress updates, process notifications) follows the user's language.
Objective
Extract complete product information from any publicly accessible e-commerce product page using a universal multi-layer extraction strategy (JSON-LD → platform-specific DOM → OG meta → microdata).
Prerequisites
- Target browser is open and connected
- No login required for public product pages
Pre-execution Checks
1. Tool Readiness
If browser-act has been confirmed available in the current session → skip this step.
Invoke browser-act via Skill tool to load usage. If installation or configuration issues arise, follow its guidance to resolve then retry.
Capability Components
This Skill's operational boundary = what the user can manually do in their browser. It only reads data already displayed to the user on the page, never bypassing authentication or access controls. JS code is encapsulated in Python files under the
scripts/directory, invoked viaeval "$(python scripts/xxx.py {params})". Use the bash tool for execution.
DOM: Extract product data from current product page
Navigate to the product URL first, then extract:
eval "$(python scripts/extract-product.py)"
Output example:
{
"url": "https://www.amazon.com/dp/B09WNK39JN",
"name": "Amazon Echo Pop",
"price": 39.99,
"price_currency": "USD",
"brand": "Amazon",
"image": "https://m.media-amazon.com/images/I/61bTwy0ooPL.jpg",
"images": ["https://...jpg", "https://...jpg"],
"description": "Compact smart speaker with Alexa...",
"category": ["Electronics", "Smart Speakers"],
"sku": "B09WNK39JN",
"gtin": null,
"mpn": null,
"availability": "InStock",
"rating": 4.7,
"review_count": 103789,
"variants": [{"name": "Charcoal", "sku": "B09WNK39JN", "price": 39.99}],
"seller": "Amazon",
"identifiers": {"ASIN": "B09WNK39JN", "Best Sellers Rank": "#1 in Smart Speakers"},
"_platform": "amazon",
"_source": "json-ld"
}
Composite: Keyword or SKU → product detail
When input is a keyword, ASIN/SKU, or EAN/UPC rather than a direct product URL:
Step 1 — Navigate to search URL based on input type:
| Input type | Target site | URL pattern |
|---|---|---|
| ASIN (10-char alphanumeric) | Amazon | https://www.amazon.com/dp/{ASIN} |
| Keyword | Amazon | https://www.amazon.com/s?k={keyword_urlencoded} |
| Keyword | eBay | https://www.ebay.com/sch/i.html?_nkw={keyword_urlencoded} |
| Keyword | Walmart | https://www.walmart.com/search?q={keyword_urlencoded} |
Keyword + --site specified | Any site | https://{site}/search?q={keyword_urlencoded} |
| Keyword (no site) | Cross-site | https://www.google.com/search?tbm=shop&q={keyword_urlencoded} |
| EAN / UPC / GTIN | Cross-site | https://www.google.com/search?tbm=shop&q={identifier} |
Step 2 — If landed on a search/listing page (multiple results):
wait stableeval "$(python scripts/extract-listing.py --max-results 3)"— get top 3 results- Pick the most relevant product URL from
items[0].url navigate {product_url}→wait stable
Step 3 — Extract product data:
eval "$(python scripts/extract-product.py)"
Note: scripts/extract-listing.py is located in ../ecommerce-listing/scripts/extract-listing.py if used as a standalone Skill install; otherwise reference the listing Skill.
Success Criteria
result.name != null AND (result.price != null OR result.availability != null)
Known Limitations
- Amazon bot detection: direct navigation to a product URL may redirect to a CAPTCHA or bot-check page on fresh sessions. Navigate from
https://www.amazon.comfirst to establish session cookies, then navigate to the product page - eBay product pages may require navigating from
https://www.ebay.comfirst; usesolve-captchaif a challenge appears - Some sites render product data entirely via client-side JavaScript; always use
wait stablebefore extracting - Price may be null for out-of-stock items or when login is required to view pricing
- Variant data completeness depends on whether the site includes full variant markup in JSON-LD
Execution Efficiency
- Batch orchestration: Write a bash script to loop through product URLs serially within a single session; add 1–2 second intervals between requests to avoid triggering anti-scraping restrictions
- Test before batch execution: Test with 1–2 URLs before running the full batch
- Error resumption: Save results item by item; on failure, resume from the breakpoint rather than starting over
Experience Notes
Path: {working-directory}/browser-act-skill-forge-memories/ecommerce-scraper-ecommerce-product-detail.memory.md
Before execution: If the file exists, read it first — it records unexpected situations encountered during past executions (e.g., a strategy has become ineffective); adjust strategy order accordingly.
After execution: If an unexpected situation is encountered (strategy became ineffective, page redesigned, anti-scraping upgraded, better path discovered), append a line:
{YYYY-MM-DD}: {what happened} → {conclusion}
Frequently asked questions about E-commerce Product Detail
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