{"id":"28993","prompt":"Input an article, go through three rounds of Q&A, and it directly outputs cover prompts that can be used for image generation. No need to understand design, no need to write prompts yourself, the aspect ratio is fixed at 3:4, and facial consistency can be maintained.👇 👹 The entire workflow is as follows: 1. Skill installation and first-time configuration (save a photo of your own face + confirm the image generation model) 2. Give the article content to the agent, which automatically reads and refines it 3. Round 1: Recommend composition styles based on content (10 options to choose from) + automatically come up with candidate titles 4. Round 2: Face reference images + materials such as UI screenshots/product images 5. Round 3: Choose expressions, background tones, fonts, and font colors all at once, or leave it all to the model if you're lazy 6. Output complete prompts: 3:4 composition, safety zone, multi-reference image writing for Image 1 (face) + Image 2 (materials) are all included 7. Take it to Jimeng / Nano Banana / GPT-Image to generate images (if your agent has an image generation API configured, you can have it generate directly in the conversation) 8. Check if the titles have typos, and regenerate any parts you're unhappy with. 🧐 Tips: You must choose an image generation model that supports multiple reference images, otherwise facial consistency cannot be guaranteed. The skill has 8 built-in sets of example prompts reverse-engineered from real trending covers, and the model will automatically use them as references, pushing the image detail to the maximum.","promptEn":"Input an article, go through three rounds of Q&A, and it directly outputs cover prompts that can be used for image generation. No need to understand design, no need to write prompts yourself, the aspect ratio is fixed at 3:4, and facial consistency can be maintained.👇 👹 The entire workflow is as follows: 1. Skill installation and first-time configuration (save a photo of your own face + confirm the image generation model) 2. Give the article content to the agent, which automatically reads and refines it 3. Round 1: Recommend composition styles based on content (10 options to choose from) + automatically come up with candidate titles 4. Round 2: Face reference images + materials such as UI screenshots/product images 5. Round 3: Choose expressions, background tones, fonts, and font colors all at once, or leave it all to the model if you're lazy 6. Output complete prompts: 3:4 composition, safety zone, multi-reference image writing for Image 1 (face) + Image 2 (materials) are all included 7. Take it to Jimeng / Nano Banana / GPT-Image to generate images (if your agent has an image generation API configured, you can have it generate directly in the conversation) 8. Check if the titles have typos, and regenerate any parts you're unhappy with. 🧐 Tips: You must choose an image generation model that supports multiple reference images, otherwise facial consistency cannot be guaranteed. The skill has 8 built-in sets of example prompts reverse-engineered from real trending covers, and the model will automatically use them as references, pushing the image detail to the maximum.","promptZh":"输入文章，经过三轮问答，直接输出可用于图像生成的封面提示词。无需懂设计，无需自己写提示词，比例固定为 3:4，且能保持人脸一致性。👇 👹 完整工作流如下：1. 技能安装与首次配置（保存一张你自己的脸部照片 + 确认图像生成模型） 2. 将文章内容交给 Agent，它会自动阅读并提炼 3. 第一轮：根据内容推荐构图风格（10 种可选）+ 自动构思候选标题 4. 第二轮：上传人脸参考图 + UI 截图/产品图等素材 5. 第三轮：一次性选定表情、背景色调、字体及字体颜色，或者如果你想偷懒，直接交给模型决定 6. 输出完整提示词：包含 3:4 构图、安全区、Image 1（人脸）+ Image 2（素材）的多参考图写法 7. 拿到即梦 / 纳豆 / GPT-Image 中生成图片（如果你的 Agent 配置了图像生成 API，可直接在对话中生成） 8. 检查标题是否有错别字，对不满意的部分进行重新生成。🧐 小贴士：必须选择支持多参考图的图像生成模型，否则无法保证人脸一致性。该技能内置了 8 组从真实热门封面中反向工程得到的示例提示词，模型会自动将其作为参考，将图像细节拉满。"}