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muapi-rednote-cover

@samuraigpt · 收录于 1 周前 · 上游提交 3 周前

Create a Xiaohongshu (RedNote/小红书) style cover image — vibrant, lifestyle-focused, with aesthetic typography overlay suitable for the Chinese social platform.

场景小红书发帖封面设计

适合你，如果你需要为小红书笔记制作吸引眼球的封面图

/ 下载安装
muapi-rednote-cover.skill双击,或拖进 Claude 桌面版 / Cowork,即完成安装↓ .skill↓ .zip
用别的 agent?下载 .zip 解压,把文件夹放进它的技能目录
Claude Code~/.claude/skills/(项目级 .claude/skills/)
Codex CLI~/.codex/skills/
Cursor自动读取上面两处目录
其他工具见其文档的「skills」目录;两个下载是同一份文件,只是名字不同
/ 通过 npx 安装 校验哈希
npx oh-my-skill add samuraigpt/generative-media-skills/muapi-rednote-cover
/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- samuraigpt/generative-media-skills/muapi-rednote-cover
/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify samuraigpt/generative-media-skills/muapi-rednote-cover
安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。
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怎么用

商店整理自技能原文 · 版本 a1c4c98 · 表述以原文为准
它做什么

装上后，Claude 能根据你提供的主题、风格和文字，生成一张小红书风格的封面图。图片会带有柔和光线、生活感构图和美观的文字排版，适合发在小红书等中文社交平台。

什么时候触发

当你提到“小红书”、“rednote”、“xhs cover”等关键词，或要求制作小红书封面图时触发。

装好后可以这样说
Claude 会生成一张暖色调的护肤主题封面图。
Claude 会生成一张方形封面，并加上指定文字。
Claude 会生成暖、冷、中性三种色调的封面。
技能原文 SKILL.md作者撰写 · MIT · a1c4c98

RedNote Cover

Create a Xiaohongshu (RedNote/小红书) style cover image — vibrant, lifestyle-focused, with aesthetic typography overlay suitable for the Chinese social platform.

Inputs

| Name | Type | Required | Default | Description | |:---|:---|:---|:---|:---| | topic | text | yes | — | The post topic (e.g. "morning skincare routine", "cozy café study vlog", "ootd autumn fashion"). | | style | text | no | aesthetic, warm tones, lifestyle photography | Visual style (e.g. "minimalist Korean aesthetic", "cottagecore", "dark moody luxe", "bright Taiwanese street style"). | | text_overlay | text | no | — | Optional Chinese or English text to appear in the cover design (e.g. "今日穿搭✨" or "Morning Glow"). | | orientation | text | no | portrait | Image orientation — "portrait" (3:4) for feed, "square" (1:1) for grid. | | reference_image | image_url | no | — | Optional reference photo of the subject or product. |

Steps
Phase A — Cover Image

Submit the plan with ONE or TWO steps:

  1. Cover image — If {{reference_image}} is provided, use muapi image edit (model=bytedance-seedream-v4.5-edit); otherwise use muapi image generate (model=bytedance-seedream-v4.5).
  2. Prompt: Xiaohongshu (RedNote/小红书) style cover photo for {{topic}} post. {{style}}. Aesthetic lifestyle photography, soft natural lighting, visually appealing composition, clean and airy feel. High engagement social media cover, editorial quality. Platform optimized for Chinese lifestyle app.
  3. If {{text_overlay}} is provided, append: Include elegant text overlay saying "{{text_overlay}}" in a stylish font, placed at top or bottom third of image.
  4. Aspect ratio: 3:4 if orientation is portrait, 1:1 if square

After generation, present the cover and offer:

  • A set of 3 variations with different color moods (warm / cool / neutral)
  • A carousel set (3 images for a RedNote carousel post)
  • Upscaling for print/export quality
Notes
  • RedNote covers perform best with: soft bokeh backgrounds, centered subjects, warm or pastel tones, and clear visual hierarchy.
  • If topic is fashion/outfit, suggest ugc-lifestyle-try-on skill for wearable product shots.
  • Korean/Japanese aesthetic filters (soft, matte, film grain) trend highly on the platform.
Trigger Keywords

rednote, xiaohongshu, 小红书, red note, rednote cover, xhs cover, chinese social, lifestyle cover

Notes for the Executing Agent
  • This recipe is LLM-orchestrated: read each phase, gather any missing inputs from the user, then call muapi CLI commands. Use muapi auth configure first if MUAPI_API_KEY is unset.
  • For model IDs without a CLI alias yet, fall back to the raw endpoint via curl -X POST https://api.muapi.ai/api/v1/<endpoint> -H "x-api-key: $MUAPI_API_KEY" -H 'content-type: application/json' -d '{...}' and poll with muapi predict wait <request_id>.
  • Substitute {{input_name}} placeholders with the user's actual inputs before issuing each call.
按 MIT 许可原样转载,未经改动 · 在 GitHub 查看 →

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