提示词库 · 信息图 · 信息图 GPT Image 2 提示词:English Vocabulary Educational Infographic
信息图 GPT Image 2 提示词:English Vocabulary Educational Infographic
信息图 界面稿 角色设定

信息图 GPT Image 2 提示词:English Vocabulary Educational Infographic

Generates a vertical, multi-section educational comic strip for teaching vocabulary with breakdowns, mnemonics, and examples.
场景
信息图 / 界面稿 / 角色设定
模型
GPT Image 2
语言
中文

📝 提示词

{ "type": "educational infographic comic", "style": "cute chibi anime, flat colors, clear comic panel layout, pastel backgrounds", "header": { "title": "今天我们来学习一个新词:", "word": "{argument name="target word" default="so-called"}", "translation": "({argument name="target translation" default="所谓的"})", "definition_box": "“so-called” 表示“所谓的”,用来强调某事物的名字或称呼,并不一定是真的那样。", "illustration": "teacher at chalkboard talking to 2 students with speech bubbles" }, "layout": { "sections": [ { "title": "1. 拆分小能手 (按音节/前后缀/词根)", "count": 3, "labels": ["so", "call", "ed"], "details": "3 colored columns (pink, green, blue) breaking down syllables, roots, and suffixes, accompanied by 4 chibi characters explaining the parts" }, { "title": "2. 发音 (中文谐音)", "count": 1, "labels": ["so-called"], "details": "phonetic pronunciation guide with a teacher instructing a student" }, { "title": "3. 联想记忆法 (故事联想)", "count": 3, "labels": ["panel 1", "panel 2", "panel 3"], "details": "3-panel comic illustrating {argument name="mnemonic story theme" default="a so-called genius dog that only knows how to sit"}" }, { "title": "4. 例句小剧场", "count": 2, "labels": ["(1)", "(2)"], "details": "2 illustrated examples showing {argument name="example 1" default="a so-called top student who doesn't do homework"} and {argument name="example 2" default="a so-called best pizza that tastes average"}" }, { "title": "5. 总结小卡片", "count": 5, "labels": ["单词", "拆分", "发音", "意思", "记忆口诀"], "details": "bulleted summary list with star icons, featuring a teacher character pointing at the bottom right" } ], "footer": "megaphone icon with text 每天学一个,英语更轻松!下次见!" } }

🎯 适合场景

适合做图解、清单、路线图和知识长图:先锁定信息层级,再把文字量控制在模型能稳定处理的范围里。

💡 改写建议

  • 先替换变量里的品类、人物、城市、品牌色,不急着改整段结构。 把主体、构图和风格分开写,后续微调会更稳。
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