JD Product Info Fetcher
Batch-fetch complete JD product details including price, promotions, reviews, and brand info.
What Is JD Product Info Fetcher?
JD Product Info Fetcher (京东商品采集器) is an automated web-scraping and e-commerce intelligence skill on EasyClaw designed to harvest complete, real-time product information from Jingdong (JD.com). Operating headlessly through clean browser automation, it bypasses manual copy-pasting to extract comprehensive product details — including retail prices, active coupons and promotions, structured review counts, brand specifications, and multi-angle product media — compiling them into standard, spreadsheet-ready datasets.
The skill is built for e-commerce developers running domestic price-comparison apps, brand managers tracking competitor promotions, and sourcing agents auditing retail arbitrage margins.
The expected outcome is a structured, production-ready e-commerce dataset: a clean CSV and JSON file detailing product IDs, titles, current pricing, coupon values, and review metrics, written directly to your local workspace exports.
How JD Product Info Fetcher Works
1. Analyze target URL and scope. Provide a list of JD product links, store URLs, or keyword queries, and specify if you want to limit the number of listings collected.
2. Headless product page parsing. The skill’s browser automation engine opens the target JD listings headlessly, bypassing personal tracking cookies to fetch clean-state details.
3. Structured metadata extraction. It parses the page layouts to isolate and extract key e-commerce fields: Product ID, Title, Current Price, Original Price, Active Coupons/Discounts, Brand Name, Category Path, Review Volume, and Main Image URL.
4. Interactive store scraping. For full store crawls (e.g., "Get all product info from this store"), the skill walks through paginations sequentially, compiling a consolidated database of the store's full product catalog.
5. Output compiling and saving. Parsed data is written directly to your local workspace exports directory (`public/data/exports/`) as clean CSV and JSON files, paired with a scannable summary in your conversation.
Key Features
- JD.com listing parser: Scrapes complete pricing, coupon, and review metrics headlessly.
- Store-wide catalog crawler: Iterates through store listings sequentially to compile full product databases.
- Coupon and promotion extractor: Automatically isolates active coupons, flash sale events, and volume discounts.
- Review volume tracker: Pulls structured review counts and positive feedback rates from listings.
- Direct CSV/JSON export: Writes clean, spreadsheet-ready files directly to your workspace.
- Frictionless error handling: Proactively prompts you for missing store links or parameters before running.
What Problems Does JD Product Info Fetcher Solve?
1. Auditing competitor pricing and active coupons on JD
A consumer brand manager wants to track how a top competitor is pricing their "ergonomic office chairs" on JD.com during a shopping festival (like 618). They point the skill to the competitor's listings. The fetcher scrapes the data, returning a clean table showing current prices, active coupons (e.g., "¥200 off ¥1,000"), and review counts, allowing the manager to adjust their own promotions.
2. Compiling full store catalog data for price comparison
A developer building a local price-monitoring platform wants to import the full catalog of an official electronics store on JD. They provide the store homepage URL. The skill crawls the store's video and product grids, aggregates all active SKUs, and exports a unified JSON file directly to their local database directory.
3. Quick product price and stock checks
An online arbitrage buyer wants to check the live price and availability of a specific high-demand cosmetic item on JD. They paste the product link. The skill retrieves the listing details instantly, reporting the current price and stock status without requiring the buyer to open the JD application.
4. Sourcing products for wholesale arbitrage
A cross-border merchant searches for popular smart household appliances on JD. The skill compiles 30 listings with pricing, shipping details, and active coupons. The exporter reveals which listings offer the lowest landed costs when bulk coupon discounts are applied, highlighting highly profitable sourcing options.
5. Automatically prompting for missing store links
A user types a vague instruction: *"Get all product info from this store"* without providing a URL. The skill's context logic intercepts the request and prompts politely: *"To crawl the store, could you please share the JD store's homepage URL? And do you want to limit the total number of products collected?"* preventing failed crawls.
Example Workflow
A merchant needs to collect pricing and coupon details for a specific JD listing.
1. They open EasyClaw and activate JD Product Info Fetcher.
2. They run: *"Get the price and promotions for this JD listing: https://item.jd.com/12345678.html."*
3. The skill launches the browser automation, accesses the JD page, and parses the details.
4. It outputs the structured JD Product Snapshot:
- Title: Mechanical Keyboard RGB Blue Switch.
- Current Price: 349.00 RMB (Original: 399.00 RMB).
- Coupons: ¥30 off over ¥300 (Active).
- Reviews: 5,000+ comments (98% positive rate).
5. It saves the details to: `public/data/exports/jd-12345678-details.json`.
Product details and coupon summaries retrieved headlessly in under 20 seconds.
Getting Started with JD Product Info Fetcher
Product details: Get the price and promotions for these JD products -> Returns full details including title, price, coupons, and review count
Store scrape: Get all product info from this JD store -> Missing store link — please provide the store homepage URL and whether to limit the number of products
Quick check: What's the current price for this item? -> Please share the JD product link and I'll look it up
Frequently Asked Questions
Do I need a JD developer account to use this skill?
No. The skill operates headlessly using secure browser automation over public JD listing grids, meaning you do not need an official JD open platform developer account or API key to collect data.
Will using this skill trigger anti-bot blocks?
The browser automation engine incorporates human-like scroll pacing and connection delays designed to comply with e-commerce safety guidelines, ensuring stable data collection without triggering IP blocks.
What is the difference between "Product details" and "Store scrape"?
"Product details" pulls comprehensive metrics for specific listing URLs you provide. "Store scrape" headlessly navigates a seller's full storefront, iterating through pagination to compile their complete active catalog.
What fields are included in the exported CSV?
Standard exported fields include: Product ID, Product Title, Brand Name, Current Price, Original Price, Active Coupons, Total Review Count, Positive Review Rate, and Main Image URL.
Can I export the data directly to Google Sheets?
The skill exports standard CSV files directly to your local workspace exports directory. You can easily upload this CSV file to Google Drive and open it in Google Sheets with one click.
How does the skill handle coupon data?
The parser extracts active platform-wide and seller-specific coupons displayed on the page (e.g., "¥20 off ¥199" or "Buy 2 get 10% off"), mapping them clearly in your data sheets.
Is there an offline log of my scraping actions?
Yes. Every successful product fetch and store crawl is logged locally under `public/data/logs/` in your workspace, creating a clear history of your market research.
Can I translate and summarize JD descriptions?
Yes. The skill supports multilingual parsing. You can request the extracted product details, specifications, and descriptions translated and summarized into professionally structured English.
Can I scrape wholesale pricing on JD?
The fetcher parses the active public prices listed on JD.com. For specialized enterprise or wholesale B2B pricing, ensure your local browser session is logged into your corporate JD account before scanning.
Is my personal search history private?
Yes. All scraping operations, URL navigations, and file writes are executed entirely locally in your workspace session, keeping your competitive research private.
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