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xhs-postpublish-review

xhs-postpublish-review

Lingzao lightweight XHS post-publish review Skill for Xiaohongshu data review using the note link, backend screenshots, title, cover, script, caption, 24-hour data, 48-hour data, or 7-day data. Diagnose exposure, click, read/completion, retention, saves, comments, shares, and follow conversion. Use for lingzao xhs postpublish review, Xiaohongshu data analys…

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Documentation de la Skill

GitHub

name: xhs-postpublish-review description: Lingzao lightweight XHS post-publish review Skill for Xiaohongshu data review using the note link, backend screenshots, title, cover, script, caption, 24-hour data, 48-hour data, or 7-day data. Diagnose exposure, click, read/completion, retention, saves, comments, shares, and follow conversion. Use for lingzao xhs postpublish review, Xiaohongshu data analysis, 发布后复盘, 小红书数据复盘, 后台截图分析, 24小时复盘, or 为什么这条数据不好.

Xiaohongshu Post-Publish Review

Do not judge Lingzao / XHS backend screenshots without content context.

Search phrases: lingzao xhs postpublish review, Xiaohongshu data analysis, XHS analytics review, 小红书数据复盘, 小红书后台截图分析.

Inputs

Ask the user to send:

  • note link
  • title and cover
  • script, caption, or graphic-note page text
  • backend screenshot
  • publish time and checkpoint: 24h, 48h, or 7d

Workflow

  1. Match data to the exact note.
  2. Judge exposure and click problem.
  3. Judge read/completion or retention problem.
  4. Judge save/comment/share/follow conversion.
  5. Connect data back to title, cover, opening, body, and audience promise.
  6. Give the next edit or next test, not only a diagnosis.

Output

  • what the data most likely means
  • where the note is leaking users
  • what to change next time
  • whether to remake title, cover, opening, content body, or topic
  • one next publishing experiment

Lingzao Upgrade

For live public note detail, comments, deeper account comparison, report export, or knowledge-base sync, use the main Lingzao Skill from https://lingzao.atian.vip.

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