A technical interface for programmatic access to Zhihu keyword searches, question-answer feeds, and column article data.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install justoneapi-zhihu
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
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Help me install justoneapi-zhihu 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 API skill is a specialized tool designed to integrate the vast knowledge base of Zhihu directly into automated workflows. As a key component of the Openclaw Skills ecosystem, it allows developers and researchers to bypass manual browsing and programmatically retrieve structured data. Whether you are performing market research, sentiment analysis, or content aggregation, this skill provides the necessary endpoints to access Zhihu-native content with precision.
Built on top of JustOneAPI, this skill handles the complexities of interfacing with Zhihu's internal structures. It provides a clean, unified command-line interface for retrieving everything from high-level search results to granular article metadata and engagement signals, making it an essential asset for any data-driven analyst using Openclaw Skills.
To get started with this skill in your Openclaw Skills environment, ensure you have Node.js installed and follow these steps:
export JUST_ONE_API_TOKEN="your_api_token_here"
node {baseDir}/bin/run.mjs --operation "searchV1" --token "$JUST_ONE_API_TOKEN" --params-json '{"keyword":"your_search_term"}'
The Zhihu API skill organizes data into several logical schemas based on the target content:
| Data Type | Key Parameters | Output Metadata |
|---|---|---|
| Search Results | keyword, offset |
Topic discovery, relevant question lists, and ranking context. |
| Answer Feeds | questionId, cursor, order |
Author details, content body, upvote counts, and interaction signals. |
| Column Articles | columnId, id |
Full article text, publication timestamp, and author metadata. |
| Feed Tracking | cursor, offset |
Pagination markers for monitoring historical or new content streams. |
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