Zhihu Content Selection Assistant
Paste the following prompt into your AI chat to install this skill:
Please install @user_5ee3d2f0/zhihu-content-selection by following the guide at https://skillhub.cn/install/skillhub.md.
About this skill
Problem Solved
Zhihu hot lists, recommended questions, and invited answers are scattered across different pages, so creators often rely on screenshots, memory, or manual exports, without a local record that can be searched by date, keyword, source, and heat. Browsing alone also makes it hard to track how hot topics evolve, how question follower counts change, and whether invited opportunities have already been covered.
How It Works and Limits
The skill collects Zhihu data into a local SQLite database, with core tables articles for hot list items, questions for recommended or invited questions, and fetch_logs for collection logs. Hot list data requires no login; recommended and invited questions require a Zhihu session in Edge, with cookies saved locally through automatic extraction or manual copying. After collection, you can query via CLI, inspect SQLite directly, or open data/index.html for a visual report filtered by date, keyword, source, and heat. It includes up to 2 retries and a roughly 2-second request interval, which suits low-frequency tracking, but it only supports Edge, requires re-login when cookies expire, and very frequent collection can still increase API risk.
Use Cases
- Operators review the Zhihu hot list daily and filter industry topics by keyword and heat.
- Bloggers check recommended and invited questions before writing to find high-attention topics.
- Writers sort captured questions by source and follower count to track reader interests in their niche.
- New users browse hot list summaries and question lists in the visual report to find suitable answer topics.
Best For
- Social media operators tracking industry hot topics and planning Zhihu content angles.
- Bloggers and KOLs discovering high-attention questions to guide answers or articles.
- Niche writers monitoring reader interests and shortlisting topics in their domain.
- Zhihu newcomers learning platform hot-topic distribution and finding suitable answers to write.
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