Holiday Pretty Meals! Insanely Delicious Rice Bowl Collection 🥘 A Week Without Repeats!

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: 泰式柠檬鸡腿肉饭 — Cover · 1 of 9Original on Xiaohongshu ↗

Layers

Hook · Text layerOne line of dish name per panel
Palette · Color layerLight base with warm food colors
Mood · Atmosphere layerAbundant home-style fullness

Spec sheet

1Hook

泰式柠檬鸡腿肉饭. Write the finished dish directly as the dish name, so viewers see what they want to eat at a glance and save it right away.

Text: 泰式柠檬鸡腿肉饭
Position: Bottom left of that panel
Relative size: One line of small text

16K likes 15K saves 2.1K shares

Posted by 一只小小依👧 on Xiaohongshu, 3 Oct 2025. 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.

Make your version4 cards Stick it together

The prompt, as used

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

Refer to the content structure, first-image hook, visual pacing, and publishing tone of the case study "Holiday Pretty Meals! Insanely Delicious Rice Bowl Collection 🥘 A Week Without Repeats!" to generate a new set of viral image-text posts. New topic: {填写你要生成的主题} Reference platform: Xiaohongshu Content direction: E-commerce product promotion image-text Creation method: Keep the original case's product scenes, selling point order, trust reasons, and conversion actions, highlighting why it's worth buying or saving. Please output: 1. Cover title and subtitle; 2. 6-8 page image-text script, each page including visual description, main copy, information points, and interaction/save actions; 3. Visual prompts ready for image generation, explaining subject, scene, lighting, composition, fonts or layout; 4. Publishing suggestions: title length, tags, image ratio, and platform tone. Constraints: Do not replicate the original author, original characters, or brand logos; do not fabricate data; avoid promising effects when it involves health, metaphysics, investment, or educational outcomes.