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  4. 老D20几岁的时候,一个人去拉脱维亚旅行。
Education · Douyin carousel · potential 82 · Machine-translated

English toys with every non-native speaker equally

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: 老D20几岁的时候,一个人去拉脱维亚旅行。
Cover · 1 of 9Original on Douyin carousel ↗
Layers
Spec sheet

1Hook

老D20几岁的时候,一个人去拉脱维亚旅行。. Start a story with a specific age and an unfamiliar country name, making people want to know what embarrassing thing happened later.

Text
老D20几岁的时候,一个人去拉脱维亚旅行。
Position
Top of the image, arranged in two centered lines
Relative size
The largest text in the whole image, spanning most of the image width
45.3K likes 1.2K saves 2.5K shares

Posted by 猫未未 on Douyin carousel, 9 Mar 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.

The prompt, as used

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

Referencing the content structure, opening hook, visual pacing, and posting tone of the case study "English toys with every non-native speaker equally," generate a new set of viral image-text content. New topic: {enter the topic you want to generate} Reference platform: Douyin Content direction: English learning image-text Creation method: Keep the original case's learning scenarios, short-sentence density, and memory rhythm, and break the knowledge points into cards that can be saved for review. 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 action; 3. Visual prompts that can be used directly for image generation, explaining the subject, scene, lighting, composition, font, or layout; 4. Posting 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; when involving health, metaphysics, investment, or educational outcomes, avoid promising results.

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