1688 Product Detail logo

1688 Product Detail

OrganizationPopular
browser-act
1688-product-detail

Extracts comprehensive wholesale product data from 1688.com product detail pages: title, tiered pricing, SKU variants with dimensions/weight, product images, seller info, shop scores, buyer protection, cross-border flags, product attributes, coupon/promotion data, and review stats. Use when user mentions 1688, 1688.com, wholesale China, alibaba wholesale, B2B China sourcing, Chinese wholesale scraper, 1688 product scrape, 1688 offer, 1688 detail, extract 1688 data, pull 1688 listings, get wholesale price, 1688 supplier info, factory stats 1688, 1688 SKU variants, 1688 product attributes, 1688 shop score, DSR score 1688, 1688 buyer protection, 1688 cross-border, 1688 dropship. Also applies to: scraping bulk product data from 1688 by offer ID list, monitoring 1688 supplier metrics, extracting 1688 pricing tiers for resale analysis.

Overview

Publisherbrowser-act
Repositoryskills
Skill name1688-product-detail
Stars
5.9K
Forks
295
Bundled files
4
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by browser-act on GitHub. Read the source before you install it.

Installation

Install the 1688 Product Detail AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/browser-act/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/solutions/ecommerce/1688-product-detail .claude/skills/1688-product-detail
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable 1688 Product Detail in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads 1688 Product Detail on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so 1688 Product Detail is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

1688.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 via eval "$(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:

json
{
  "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:

json
{
  "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:

json
{
  "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:

json
{
  "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:

  1. wait stable
  2. network requests --type xhr,fetch --filter h5api.m.1688.com
  3. Find request with URL containing mtop.1688.moga.pc.shopcard
  4. 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:

  1. navigate https://detail.1688.com/offer/{offer_id}.html
  2. wait stable
  3. 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:

json
{
  "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:

  1. wait stable
  2. network requests --type xhr,fetch --filter h5api.m.1688.com
  3. Find request with URL containing querydsrratedatav2
  4. 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:

json
{
  "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:

  1. navigate https://detail.1688.com/offer/{offer_id}.html
  2. wait stable
  3. eval "$(python scripts/extract-product-detail.py '{offer_id}')" → core data
  4. eval "$(python scripts/extract-sku-details.py '{offer_id}')" → SKU variants
  5. eval "$(python scripts/extract-promotions.py '{offer_id}')" → coupons/activity
  6. network requests --type xhr,fetch --filter h5api.m.1688.com → locate shopcard and DSR requests
  7. network request <shopcard_request_id> → shop scores
  8. network request <dsr_request_id> → review stats
  9. 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 empty shopData for some offer types or if the session has expired; navigate to the product page to refresh
  • productAttributes DOM module has a server-side rendering bug (JSONArray cast error in page metadata) — attributes are extracted from DOM fallback selectors instead
  • freightInfo.totalCost (shipping cost) comes from the freight API which requires sendAddressCode and receiveAddressCode; 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.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the 1688 Product Detail AI skill do?

Extracts comprehensive wholesale product data from 1688.com product detail pages: title, tiered pricing, SKU variants with dimensions/weight, product images, seller info, shop scores, buyer protection, cross-border flags, product attributes, coupon/promotion data, and review stats. Use when user mentions 1688, 1688.com, wholesale China, alibaba wholesale, B2B China sourcing, Chinese wholesale scraper, 1688 product scrape, 1688 offer, 1688 detail, extract 1688 data, pull 1688 listings, get wholesale price, 1688 supplier info, factory stats 1688, 1688 SKU variants, 1688 product attributes, 16...

Why use 1688 Product Detail on TypingMind?

Because you install it once and use it with any model. 1688 Product Detail is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install 1688 Product Detail in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/browser-act/skills/tree/main/solutions/ecommerce/1688-product-detail. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use 1688 Product Detail?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with 1688 Product Detail?

As many as you like. As long as a model supports skills, you can use 1688 Product Detail with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the 1688 Product Detail AI skill free?

Yes. It is published on GitHub by browser-act under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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