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Career · Xiaohongshu 3:4 carousel · potential 35 · Machine-translated

Teamwork Test: "If Tang Monk Had to Lay Off One Person, Who Would It Be?"

Put the cover under the lamp. Each of the five things that made it work is a layer you can switch on: the words, the grid it sits on, the colours it uses, the subject, the light.

Cover of the original post: 如果唐僧要裁一个人,裁谁?
Cover · 1 of 4Original on Xiaohongshu ↗
Layers
Spec sheet

1Hook

如果唐僧要裁一个人,裁谁?. Use familiar team roles to pose a pick-one dilemma, making people eager to take sides in the comments.

Text
如果唐僧要裁一个人,裁谁?
Position
Centered inside the white speech bubble at the top
Size
The largest text in the image, about one third of the image width
11 likes 9 saves 15 shares

Posted by Lisa灵雯 on Xiaohongshu, 21 Apr 2026. Shown with credit and a link back.

Keep all five layers and swap what’s under them: your shop, your budget, your city. You get four covers and the post text.

The prompt, as used

Verbatim. Copy it, or let Queenie swap in your own details.

Refer to the case study "Teamwork Test: 'If Tang Monk Had to Lay Off One Person, Who Would It Be?'" for its content structure, cover hook, visual pacing, and publishing tone, and generate a new set of viral image-text content. New topic: {fill in the topic you want to generate} Reference platform: Xiaohongshu Content direction: Workplace growth image-text Creation method: Keep the original case's workplace hooks, pain-point scenarios, and conclusion rhythm, and reorganize with more specific personas, conflicts, methods, and actionable steps. Please output: 1. Cover title and subtitle; 2. 6-8 page image-text script, each page including visual description, main copy, key information points, and interaction/save action; 3. Visual prompts that can be used directly for image generation, specifying subject, scene, lighting, composition, font or layout; 4. Publishing suggestions: title length, tags, image ratio, and platform tone. Constraints: Do not replicate the original author, original characters, or brand identifiers; do not fabricate data; avoid promising results when it involves health, metaphysics, investment, or educational outcomes.

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