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1688 Scraper
by
howerlin0329
· GitHub ↗
· v1.0.0
· MIT-0
193
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Install in OpenClaw
/install 1688-scraper
Description
采集1688商品详情包含标题、价格、SKU、店铺信息、销售数据、全部商品属性及图片,并保存为本地数据包和图片文件夹。
README (SKILL.md)
1688 商品采集 Skill
功能
采集 1688 商品详情页面的完整数据,包括商品图片、标题、价格、SKU、店铺信息等,并以数据包形式保存到本地。
使用方法
基础用法
采集 1688 商品:https://detail.1688.com/offer/{商品 ID}.html
带参数
采集 1688 商品:{URL} 保存到:{路径}
输出
- 商品图片文件夹:
{桌面}/1688-商品详情-{商品 ID}-图片/ - JSON 数据包:
{桌面}/1688-商品详情-{商品 ID}.json
采集内容
- 商品标题、ID、URL
- 店铺信息(名称、评分、回头率等)
- 价格信息
- 销售数据(已售、评价等)
- 完整 SKU 列表(颜色、尺码、库存)
- 所有商品图片(主图 + 详情图)
- 商品属性(完整采集属性表格中的所有字段,包括但不限于):
- 材质、品牌、货号、风格、产地
- 规格、型号、颜色、尺寸、重量
- 适用场景、适用人群、主要销售地区
- 以及其他所有在属性表格中展示的字段
- 用户评价
技术实现
- 使用浏览器 Performance API 捕获所有图片资源
- 深度滚动触发懒加载图片
- 自动清理 URL 后缀获取原图
- 批量下载图片到本地
Usage Guidance
This skill appears to do what it claims: open a 1688 product page in a browser context, scroll to trigger lazy-loading, capture image URLs and attributes, and download images + save a JSON data package to your Desktop. Before installing: (1) confirm where the 'browser' tool runs (local machine vs remote/cloud) — running a scraper in a remote/shared environment can expose scraped data and downloaded files to others; (2) note the code uses process.env.HOME to write to ~/Desktop but the skill metadata doesn't declare that requirement — if your environment lacks HOME or has different filesystem layout, provide an explicit output path; (3) ensure the agent has curl and permission to write to the target folder; (4) consider legal/ToS and anti-scraping rules for 1688 and Alibaba domains and add rate-limiting if you will run many requests; (5) run first in a controlled sandbox or with a single test URL to verify behavior and avoid accidental mass downloads or IP blocking.
Capability Assessment
Purpose & Capability
The name/description (scrape 1688 product pages and save images/JSON) aligns with the included code and SKILL.md: browser-driven scrolling, Performance API capture, URL cleaning, and curl-based downloads. package.json lists expected runtime requirements (browser tool, curl, desktop write). Minor mismatch: the code reads process.env.HOME to build a Desktop path but the skill's metadata does not declare any required environment variables or config paths.
Instruction Scope
SKILL.md and README clearly instruct the agent to open the product URL in a browser context, deep-scroll to trigger lazy-loading, collect images and attributes, and download images to a local folder. The instructions do not attempt to read unrelated files, request unrelated credentials, or post collected data to external endpoints other than the image hosts (alicdn). They do assume the agent has a 'browser' tool and filesystem write access.
Install Mechanism
No install spec is provided (instruction-only skill with an included helper JS file). That is low-risk: nothing is automatically downloaded or written during install. The skill expects existing tools (browser, curl) rather than installing arbitrary packages or fetching code from third‑party URLs.
Credentials
The skill does not request API keys/secrets and only interacts with public image hosts (cbu01.alicdn.com). However, it uses process.env.HOME in scraper.js to compute the Desktop path but the manifest declares no env variables — this is a small inconsistency that could cause runtime surprises if HOME is unset or if the agent's working environment differs. It also assumes write permission to the user's Desktop, which should be considered before running.
Persistence & Privilege
always is false and the skill does not request persistent platform privileges; it only writes files under a constructed local path and does not modify other skills or system-wide settings. Autonomous invocation is allowed (platform default) but not combined with any other broad privileges.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install 1688-scraper - After installation, invoke the skill by name or use
/1688-scraper - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release—collects complete product data from 1688 product detail pages.
- Scrapes comprehensive details: images, title, price, SKUs, shop info, sales, and user reviews.
- Saves product images and data package (JSON) to desktop.
- Supports inputting just a product URL, or specifying a save path.
- Captures all product attributes as shown in the 1688 attribute table.
- Leverages browser Performance API and advanced image handling for complete downloads.
Metadata
Frequently Asked Questions
What is 1688 Scraper?
采集1688商品详情包含标题、价格、SKU、店铺信息、销售数据、全部商品属性及图片,并保存为本地数据包和图片文件夹。 It is an AI Agent Skill for Claude Code / OpenClaw, with 193 downloads so far.
How do I install 1688 Scraper?
Run "/install 1688-scraper" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is 1688 Scraper free?
Yes, 1688 Scraper is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does 1688 Scraper support?
1688 Scraper is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created 1688 Scraper?
It is built and maintained by howerlin0329 (@howerlin0329); the current version is v1.0.0.
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