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Walmart Product Detail Extractor

Free

Effortlessly extract detailed product data from Walmart.

by browser-act5.3k stars on browser-act/skills
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Updated Aug 5, 2026
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Free · Opens the source repo

What Walmart Product Detail Extractor does

The Walmart Product Detail Extractor skill enables users to easily gather comprehensive product information from Walmart's product pages. By simply providing a Walmart product URL, this skill extracts essential details such as item ID, title, brand, model, UPC, price, availability, category, seller information, images, descriptions, specifications, and fulfillment options. This functionality is particularly useful for developers and researchers who need to compile product catalogs or conduct competitive analysis based on Walmart's offerings.

To use the extractor, users must navigate to the specific product page on Walmart's website. Once there, the skill utilizes a Python script to scrape the displayed data, mimicking the manual process of copying and pasting information. This automation saves time and reduces the risk of human error, allowing users to focus on analysis rather than data collection. The extracted data is returned in a structured JSON format, making it easy to integrate into applications or databases for further processing.

This skill is ideal for e-commerce developers, data analysts, and product researchers who frequently need to gather detailed product data from Walmart. Whether building a product catalog, monitoring price changes, or enriching datasets with product specifications, the Walmart Product Detail Extractor streamlines the process, making it more efficient and reliable. It is particularly beneficial for tasks that require batch processing of multiple product URLs, allowing users to gather data in a single session without triggering anti-scraping measures.

However, users should be aware of certain limitations, such as potential null values for specific fields like 'wasPrice' or 'sellerAverageRating' depending on the product type. Understanding these constraints will help users set realistic expectations for the data they can extract.

When to use it

Use this skill when you need to gather detailed product information from Walmart for analysis, cataloging, or research purposes.

When not to use it

This skill is not suitable for extracting data from pages that require authentication or for products not listed on Walmart's site.

What you can build with it

Building a Product Catalog

Use the extractor to gather detailed product information for creating a comprehensive catalog of Walmart items.

Monitoring Price Changes

Set up a process to regularly extract product details and track price fluctuations over time.

Competitive Product Research

Extract data from Walmart to analyze competitor offerings and inform your own product strategies.

How to install Walmart Product Detail Extractor

View source

1. Install with the skills CLI

npx skills add browser-act/skills/walmart-product-detail --agent claude-code

2. 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-act

Walmart — Product Detail

product URL → full structured product data from walmart.com product detail page

Language

All process output to user (progress updates, process notifications) follows the user's language.

Objective

Extract complete product data from a Walmart product detail page, including pricing, images, specifications, variants, fulfillment options, and review summary.

Prerequisites

  • Target product page is open in the browser: https://www.walmart.com/ip/{product-slug}/{item-id}

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. Its role is equivalent to copy-pasting on the user's behalf — the data is already on screen, automation merely saves time. JS code is encapsulated in Python files under the scripts/ directory, invoked via eval "$(python scripts/xxx.py {params})". $(...) is bash syntax; it is recommended to use the bash tool for execution.

Below are all atomic capabilities discovered and verified during the exploration phase, listed by command template with parameters. Simply invoke them as needed — no need to read scripts/*.py source code or re-verify. Only inspect scripts when execution fails for troubleshooting. Combine freely as needed during execution.

DOM: extract full product data from current product page

Navigate to the product URL first, then extract:

  1. navigate "https://www.walmart.com/ip/{product-slug}/{item-id}"
  2. wait stable
  3. eval "$(python scripts/extract-product-detail.py)"

The item-id is the numeric Walmart item ID (usItemId). The product-slug portion of the URL does not affect which product is loaded — only the item-id matters.

Output example:

{
  "itemId": "18656507313",
  "url": "https://www.walmart.com/ip/HP-14-N150-4-128-Blue/18656507313",
  "title": "HP 14 inch HD Windows Laptop Intel Processor N150 4GB 128GB UFS Waterfall Blue",
  "brand": "HP",
  "brandUrl": "https://www.walmart.com/search?q=HP&facet=brand:HP",
  "model": "14-ep2112wm",
  "upc": "199764359186",
  "manufacturerProductId": "CQ5J6UA#ABA",
  "classType": "VARIANT",
  "price": 229,
  "priceString": "$229.00",
  "currencyUnit": "USD",
  "wasPrice": null,
  "availability": "IN_STOCK",
  "category": [
    {"name": "Electronics", "url": "https://www.walmart.com/cp/electronics/3944"},
    {"name": "Laptops", "url": "https://www.walmart.com/cp/laptops/3951"}
  ],
  "sellerId": "F55CDC31AB754BB68FE0B39041159D63",
  "sellerName": "Walmart.com",
  "sellerDisplayName": "Walmart.com",
  "sellerType": "INTERNAL",
  "sellerAverageRating": null,
  "sellerReviewCount": null,
  "averageRating": 4.4,
  "numberOfReviews": 63,
  "thumbnail": "https://i5.walmartimages.com/seo/HP-14.jpeg",
  "images": ["https://i5.walmartimages.com/seo/image1.jpeg", "https://i5.walmartimages.com/asr/image2.jpeg"],
  "shortDescription": "The HP 14 inch Laptop PC has it all...",
  "longDescription": "<ul><li><strong>Intel N150 processor:</strong> ...</li></ul>",
  "productHighlights": [
    {"name": "RAM memory", "value": "4 GB"},
    {"name": "Processor", "value": "N150"}
  ],
  "specifications": {
    "RAM memory": "DDR5",
    "OS": "Windows 11",
    "Screen size": "14 in",
    "Weight": "3.11 lb"
  },
  "variants": [
    {
      "name": "Actual Color",
      "type": "DROPDOWN",
      "options": [
        {"id": "actual_color-tranquilpink", "name": "Tranquil pink", "availability": "AVAILABLE", "itemIds": ["6G9VW0QQAI2X"]},
        {"id": "actual_color-waterfallblue", "name": "Waterfall blue", "availability": "AVAILABLE", "itemIds": ["4QPDNGIGKZZ8"]}
      ]
    }
  ],
  "fulfillmentOptions": [
    {"type": "SHIPPING", "status": "IN_STOCK", "freeShipping": true, "deliveryDate": "2026-07-09T21:59:00.000Z", "fulfillmentBadge": "Tomorrow"},
    {"type": "PICKUP", "status": "IN_STOCK", "freeShipping": true, "deliveryDate": null, "fulfillmentBadge": "Today"},
    {"type": "DELIVERY", "status": "IN_STOCK", "freeShipping": false, "deliveryDate": null, "fulfillmentBadge": "Today"}
  ],
  "returnPolicy": {
    "returnable": true,
    "freeReturns": true,
    "returnWindowDays": 30,
    "returnPolicyText": "Free 30-day returns"
  },
  "reviewSummary": {
    "averageRating": 4.2,
    "totalReviews": 279,
    "ratingBreakdown": {"5": 191, "4": 29, "3": 15, "2": 10, "1": 34},
    "reviewsLookupId": "19X7KSSCUQU5"
  }
}

Error response (when extraction fails or wrong page):

{"error": true, "message": "No product in __NEXT_DATA__. Ensure the page is a Walmart product detail page (walmart.com/ip/...)."}

Success Criteria

itemId is non-null AND title is non-null AND price is non-null OR availability is non-null

Known Limitations

  • wasPrice is null unless the item currently has an active markdown/rollback promotion
  • sellerAverageRating and sellerReviewCount are null for Walmart first-party listings (INTERNAL sellerType)
  • longDescription may be null for items without IDML data (less common)
  • specifications may be empty for items without IDML specifications
  • Variant itemIds are internal product IDs (format: alphanumeric, e.g., "6G9VW0QQAI2X"), not the usItemId; to get the usItemId for a specific variant, navigate to that variant's URL
  • Delivery dates in fulfillmentOptions reflect the browser session's location context (set by the browser's stored zip code)

Execution Efficiency

  • Batch orchestration: Write a bash script to loop through product URLs serially within a single session; do not parallelize within one browser (prone to triggering anti-scraping restrictions). Add 1–2 second intervals between navigations. To increase throughput, open multiple stealth browser sessions and distribute work across them — each session has an independent fingerprint so rate limits apply per session
  • Test before batch execution: After writing a batch script, you must first test with 1-2 items to verify the script runs correctly; only then run the full batch. Never skip testing and execute in batch directly
  • Reduce redundant pre-operations: When multiple steps depend on the same prerequisite state, complete them in batch under that state to avoid repeatedly establishing the same state
  • Error resumption: Save results item by item during batch processing; on failure, resume from the breakpoint rather than starting over

Experience Notes

Path: {working-directory}/browser-act-skill-forge-memories/walmart-scraper-walmart-product-detail.memory.md (working directory is determined by the Agent running the Skill, typically the project root or current working directory)

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}

Normal execution does not write to the file. Do not record what product URLs were scraped or what prices were found — those are task outputs, not experience.

Frequently asked questions about Walmart Product Detail Extractor

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