A powerful automation tool that extracts structured article details and full body content from Zhihu using the BrowserAct API.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install zhihu-search-api-skill
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install zhihu-search-api-skill using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The Zhihu Search API Automated Extraction skill is a specialized tool designed for the Openclaw Skills ecosystem to streamline the retrieval of high-quality data from one of China's largest knowledge-sharing platforms. By leveraging the BrowserAct API, it bypasses common web scraping hurdles such as CAPTCHAs, IP rotations, and geo-fencing, providing a stable stream of data for researchers and developers.
This skill is particularly valuable for those needing reliable, hallucination-free data extraction. Unlike standard LLM-based web browsing, this skill uses pre-set workflows to ensure that the article titles, author names, publication dates, and full body content are captured with structural integrity, making it an essential component for any automated research pipeline.
To integrate this into your Openclaw Skills library, ensure you have Python installed and a valid API key from the BrowserAct Console.
# Set your API Key
export BROWSERACT_API_KEY='your_api_key_here'
# Run the extraction script
python -u ./scripts/zhihu_search_api.py "your keyword" "7d" 10
The skill returns a structured JSON-like output for each article found, organized as follows:
| Field | Description | Type |
|---|---|---|
title |
The full headline of the Zhihu article | String |
body_content |
The complete text content of the article body | String |
author |
The name of the publishing user or organization | String |
publication_date |
Date the article was published | String |
image_url |
URL for the article's main cover image | String (URL) |
url_link |
The permanent direct link to the original post | String (URL) |
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