
1688 Product Detail Extraction
FreeEfficiently extract wholesale product data from 1688.com.
Free · Opens the source repo
What 1688 Product Detail Extraction does
The 1688 Product Detail Extraction skill is designed for users looking to gather detailed wholesale product information from 1688.com. This skill enables the extraction of over 50 fields of data from product detail pages, including title, tiered pricing, SKU variants, seller information, and promotional data. By using this skill, users can streamline their B2B sourcing processes and gain insights into product offerings from Chinese suppliers.
To utilize this skill, users need to navigate to a specific product detail page on 1688.com and execute the provided Python scripts to extract relevant data. The skill does not require any login credentials, as the data is publicly accessible. It operates by reading the data already displayed on the page and does not bypass any access controls, ensuring compliance with the website's usage policies.
This skill is particularly beneficial for businesses engaged in wholesale purchasing, dropshipping, or those looking to analyze product offerings for resale. By automating the data extraction process, users can save time and reduce manual errors associated with data entry. The extracted data can also be used for market analysis, supplier evaluation, and pricing strategy development.
Overall, the 1688 Product Detail Extraction skill is a valuable tool for anyone involved in sourcing products from 1688.com, providing a comprehensive solution for gathering essential product and seller information efficiently.
When to use it
Use this skill when you need to extract comprehensive product details from 1688.com for analysis or sourcing.
When not to use it
This skill is not suitable for extracting data from sites that require authentication or for pages that do not display product details publicly.
What you can build with it
Bulk Product Data Extraction
Use this skill to extract data for multiple products from 1688.com by iterating through a list of offer IDs.
Supplier Performance Monitoring
Leverage the skill to regularly extract and monitor seller metrics and shop scores from 1688.com.
Market Analysis for Resale
Gather detailed product information for analysis to inform pricing strategies and product selection for resale.
How to install 1688 Product Detail Extraction
View source1. Install with the skills CLI
npx skills add browser-act/skills/1688-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-act1688.com — Product Detail Extraction
Navigate to a 1688 product page → extract 50+ fields including pricing tiers, SKU variants, seller stats, attributes, promotions
Language
All process output to user (progress updates, process notifications) follows the user's language.
Objective
Extract complete wholesale product data from a 1688.com offer detail page using embedded page data and network capture for supplier metrics.
Prerequisites
- Target product detail page is open in the browser:
https://detail.1688.com/offer/{offer_id}.html - No login required for product detail pages (data is publicly accessible)
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 "$(python scripts/xxx.py {params})".$(...)is bash syntax; it is recommended to use the bash tool for execution.
DOM: Extract core product data (title, pricing, images, seller, flags)
After navigating to the product page and waiting for page load:
eval "$(python scripts/extract-product-detail.py '{offer_id}')"
Parameters:
- offer_id: Numeric 1688 offer/product ID (e.g.,
927875250705)
Output example:
{
"offerId": "927875250705",
"title": "新款苹果18promax手机壳磁吸...",
"unit": "个",
"category": { "topCategoryId": 7, "postCategoryId": 132918005 },
"pricing": {
"tiers": [
{ "minQty": "30", "price": "7.99" },
{ "minQty": "100", "price": "7.79" }
],
"priceDisplayType": "range",
"minOrderQty": 30,
"currency": "CNY"
},
"sales": {
"totalSold": 308417,
"displaySaleNum": "10万+",
"saleCountLabel": "全网销量"
},
"images": ["https://cbu01.alicdn.com/img/ibank/...jpg"],
"attributes": {
"材质": "优质TPU",
"款式": "后盖款",
"功能": "防震,磁吸,防磨,防摔",
"适用型号": "iPhone17,iphone17pro..."
},
"skuCount": 339,
"skuWeightData": [
{ "weight": 40, "length": 17, "width": 7, "height": 1, "volume": 119 }
],
"seller": {
"companyName": "佛山市南海区三丰手机配件有限公司",
"loginId": "fssf06",
"memberId": "b2b-2850655109d72ea",
"userId": 2850655109,
"shopUrl": "https://shop1460393846166.1688.com",
"cardType": "cjgc",
"isPmPlus": true,
"serviceScore": "4.5分",
"buyerRepeatRate": "65.82%"
},
"offerFlags": {
"isSkuOffer": true,
"isPreSell": false,
"isConsignMarketOffer": true,
"isDistribution": true,
"isChtOffer": true,
"isBuyerProtection": true
},
"crossBorder": {
"foreignLanguagePackageAvailable": true,
"boxMarkAvailable": true,
"fbaLabelAvailable": true
},
"guarantees": ["买家保障", "正品保障"],
"descriptionUrl": "https://detail.1688.com/...",
"offerMemberTags": [4336705, 519170],
"sellerWinportUrlMap": {}
}
DOM: Extract SKU variants (color/model combinations with weight/dimensions)
eval "$(python scripts/extract-sku-details.py '{offer_id}')"
Parameters:
- offer_id: Numeric 1688 offer/product ID
Output example:
{
"offerId": "927875250705",
"skuCount": 339,
"skuRangePrices": [
{ "price": "7.99", "beginAmount": "30" },
{ "price": "7.79", "beginAmount": "100" }
],
"skus": [
{
"skuId": 5833485852524,
"specId": "...",
"attrs": { "颜色": "黑色", "适用型号": "iPhone17" },
"saleCount": 0,
"canBookCount": 9999,
"isPromotionSku": false,
"packInfo": { "weight": 40, "length": 17, "width": 7, "height": 1, "volume": 119 }
}
],
"skuImageMap": {}
}
DOM: Extract coupon and promotion data
eval "$(python scripts/extract-promotions.py '{offer_id}')"
Parameters:
- offer_id: Numeric 1688 offer/product ID
Output example:
{
"offerId": "927875250705",
"coupons": [
{ "couponType": "INTERACT", "couponContent": "满100减5券" }
],
"promotionModel": {
"buttonName": "领券",
"promotionList": [
{
"type": "INTERACT",
"name": "互动优惠券",
"summary": "入会有礼券",
"promotionItems": [
{
"label": "满100减5券",
"availablePeriod": "有效期:2026.05.28 00:00:00-2026.11.24 23:59:59",
"canApply": true
}
]
}
]
},
"activity": {
"activityType": null,
"activityName": null,
"activityUrl": null,
"countdown": null,
"activityId": null
},
"bannerImage": ""
}
DOM: Extract seller params (for shopcard network capture)
eval "$(python scripts/extract-seller-params.py '{offer_id}')"
Parameters:
- offer_id: Numeric 1688 offer/product ID
Output example:
{
"offerId": "927875250705",
"seller": {
"companyName": "佛山市南海区三丰手机配件有限公司",
"loginId": "fssf06",
"memberId": "b2b-2850655109d72ea",
"userId": 2850655109,
"shopUrl": "https://shop1460393846166.1688.com",
"cardType": "cjgc",
"serviceScore": "4.5分",
"buyerRepeatRate3m": "65.82%"
},
"shopcardParams": {
"offerId": "927875250705",
"userId": 0,
"offerMemberTags": [4336705, 519170, "..."],
"sellerUserId": 2850655109,
"sellerMemberId": "b2b-2850655109d72ea",
"topCategoryId": 7,
"offerModelSign": { "isBuyerProtection": true, "isDistribution": true },
"sellerIdentity": "cjgc",
"sellerWinportUrlMap": { "indexUrl": "...", "defaultUrl": "..." },
"winportUrl": "https://shop1460393846166.1688.com"
}
}
Network Capture: Get shop scores and metrics (shopcard API)
The shopcard API uses dynamic sign tokens — let the page JS handle it, read from network traffic.
After the product detail page loads fully (wait stable), the shopcard request fires automatically:
wait stablenetwork requests --type xhr,fetch --filter h5api.m.1688.com- Find request with URL containing
mtop.1688.moga.pc.shopcard network request <id>
Endpoint characteristic: URL contains mtop.1688.moga.pc.shopcard
If the shopcard request is not in traffic (navigated away or cleared), reload the product page:
navigate https://detail.1688.com/offer/{offer_id}.htmlwait stable- Repeat steps 2–4 above
Error handling: If request not found after page reload, check if the product page loaded correctly (screenshot), then retry once. If still unavailable, shopcard data is unavailable for this offer.
Output example:
{
"api": "mtop.1688.moga.pc.shopcard",
"data": {
"model": {
"shopName": "佛山市南海区三丰手机配件有限公司",
"shopType": "cjgc",
"iconType": "cjgc",
"mainCategoryName": "手机配件",
"shopUrl": "https://shop1460393846166.1688.com",
"tpYear": 11,
"shopData": [
{ "dataKey": "店铺回头率", "dataValue": "66%" },
{ "dataKey": "店铺服务分", "dataValue": "4.5", "unit": "分" },
{ "dataKey": "准时发货率", "dataValue": "- %" },
{ "dataKey": "店铺好评率", "dataValue": "99.9%" }
],
"shopButton": {
"fuzzyFavCount": "8.6k粉丝",
"attentionRelation": false
}
}
}
}
Network Capture: Get DSR review summary (queryDsrRateDataV2 API)
After page load, the DSR scores request fires automatically alongside shopcard:
wait stablenetwork requests --type xhr,fetch --filter h5api.m.1688.com- Find request with URL containing
querydsrratedatav2 network request <id>
Endpoint characteristic: URL contains mtoprateservice.querydsrratedatav2
Error handling: Same as shopcard — if not found, navigate to the product page and retry. The DSR API fires with the POST param loginId = seller loginId and offerId; both come from extract-seller-params.py output.
Output example:
{
"data": {
"model": {
"goodRates": 99.9,
"goodsGrade": 5.0,
"fulfillmentDataList": [
{ "name": "商品好评", "value": "100%" },
{ "name": "按时发货" },
{ "name": "商品退款" }
],
"commonTagNodeList": [
{ "name": "全部", "count": 2497 },
{ "name": "有图", "count": 6 },
{ "name": "好评", "count": 2494 }
],
"impressionTagNodeList": [
{ "name": "价格很便宜", "count": 6 },
{ "name": "质量很好", "count": 5 }
]
}
}
}
Composite: Full product data extraction
Combines DOM extraction with network capture for complete data. For each offer ID:
navigate https://detail.1688.com/offer/{offer_id}.htmlwait stableeval "$(python scripts/extract-product-detail.py '{offer_id}')"→ core dataeval "$(python scripts/extract-sku-details.py '{offer_id}')"→ SKU variantseval "$(python scripts/extract-promotions.py '{offer_id}')"→ coupons/activitynetwork requests --type xhr,fetch --filter h5api.m.1688.com→ locate shopcard and DSR requestsnetwork request <shopcard_request_id>→ shop scoresnetwork request <dsr_request_id>→ review stats- Merge all results by offerId
Enum Parameters
shop type [collection failed]: cardType values (e.g., cjgc, cht) come from page data but no separate enumeration API found; values depend on seller registration type
Pagination
Not applicable — this is a single-product detail extraction capability. For bulk processing, see Execution Efficiency below.
Success Criteria
extract-product-detail.py output has no error field AND title is non-null AND pricing.tiers length >= 1
Known Limitations
- Search functionality (
s.1688.com) requires login/CN IP — this Skill covers detail pages only (publicly accessible by offer ID) - Shopcard API (
mtop.1688.moga.pc.shopcard) may return emptyshopDatafor some offer types or if the session has expired; navigate to the product page to refresh productAttributesDOM module has a server-side rendering bug (JSONArray cast error in page metadata) — attributes are extracted from DOM fallback selectors insteadfreightInfo.totalCost(shipping cost) comes from the freight API which requiressendAddressCodeandreceiveAddressCode; defaults to sender's registered address; not included in composite extraction due to address dependency- Review list detail (
queryItemRatedListV2) returns paginated individual reviews but is not included in composite — use the DSR summary instead
Execution Efficiency
- Batch orchestration: Write a bash script to loop through offer IDs serially within a single session; do not parallelize within one browser (prone to triggering anti-scraping restrictions). Add 2–3 second intervals between products. To increase throughput, open multiple stealth browser sessions and distribute offers across them.
- Test before batch execution: After writing a batch script, first test with 1–2 offer IDs to verify script runs correctly; only then run the full batch.
- Reduce redundant pre-operations: When processing multiple offers, keep the session open; don't re-launch browser-act for each offer.
- 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/1688-wholesale-scraper-1688-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 keywords were used or how many results were returned — those are task outputs, not experience.
Frequently asked questions about 1688 Product Detail Extraction
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