media-crawler-zhihu
Collect Zhihu answers, articles, videos, comments, and creator evidence with MediaCrawler through search and exact URLs. Use for expert discourse, problem framing, objections, terminology, topic, or creator research where content type and question context must remain explicit.
npx skills add tsingyuai/growth-lab --skill media-crawler-zhihu --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Zhihu collection Follow [media-crawler](../media-crawler/SKILL.md). Require purpose, keyword/content/creator inputs, sample and date bounds, comments/media scope, and invoking Model Memory destination. Search with `--platform zhihu --type search` using problem wording, concept/category and audience/use-case variants. Shortlist by relevance, argument/content-type diversity, recency, author fit and engagement. Configure `ZHIHU_SPECIFIED_ID_LIST` with full answer, article, or video URLs; configure `ZHIHU_CREATOR_URL_LIST` with full people URLs. Run detail/creator mode. Preserve content type. For answers retain question context; for articles retain article title; for video identify unavailable transcript rather than inventing one. Separate author text from comments, deduplicate by canonical content ID, and retain discovery-query provenance. Enable comments/media only for a shortlist and stop on challenge/risk control. Return content-type breakdown, inputs, raw/copied paths, detail/comment/media coverage, time, commit, exclusions and selection rationale.
What does the media-crawler-zhihu skill do?
Collect Zhihu answers, articles, videos, comments, and creator evidence with MediaCrawler through search and exact URLs. Use for expert discourse, problem framing, objections, terminology, topic, or creator research where content type and question context must remain explicit.
How do I install it?
Run `npx skills add tsingyuai/growth-lab --skill media-crawler-zhihu --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From tsingyuai/growth-lab, a repository with 427 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.