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snapdesign-rednoteSnapDesign 红笔记

Agent Skill

snapdesign-rednote 用于整理文档、README、Markdown 和说明材料,适合在 OpenClaw 中需要把零散信息整理成结构清晰的文档时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

13,735

周安装

590

GitHub Stars

公开资料未说明

下载量

4,814
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:snapdesign-rednote(SnapDesign 红笔记)
来源仓库:https://github.com/horisony/snapdesign-rednote
安装命令:
openclaw skills install snapdesign-rednote
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install snapdesign-rednote

简介

将文本内容转换为小红书风格轮播卡 HTML 布局,适配移动端阅读体验。

  • 适用于电商运营、内容创作者快速产出美观图文卡片的需求。
  • 输入标题与正文后自动生成带渐变背景与图标的自适应网页组件。
  • 样式模板有限,个性化定制需修改源码或联系作者扩展功能。
  • 安装命令:openclaw skills install snapdesign-rednote

SKILL.md

name
rednote-card-generator
description
Use when you need to generate Xiaohongshu (小红书 / RedNote) carousel card HTML layouts. Given a piece of text content, this skill produces a complete, self-contained HTML document containing multiple vertical 450×600px cards styled for the RedNote / Xiaohongshu platform.

RedNote Card Generator

Overview

Use rednote-card-generator to turn any text content into a beautifully styled Xiaohongshu (小红书) carousel post. The output is a single, self-contained HTML string that renders multiple vertical cards (each 450×600 px) stacked vertically with a 20 px gap.

The skill calls the OpenRouter API (model: google/gemini-2.5-flash with fallback to google/gemini-2.5-flash-lite) and streams the HTML response back.

Inputs to collect

FieldRequiredDescription
contentYesThe text content to turn into RedNote cards. Can be plain text or light HTML.
colorSchemeNoOne of: auto (default), warm-brown, sunset, ocean, forest, lavender, monochrome. Controls the dominant palette.
openrouterApiKeyYesA valid OpenRouter API key (Bearer token).

Output

Returns a JSON object:

{
  "html": "<!DOCTYPE html>...",
  "cardCount": 5
}
  • html: Complete self-contained HTML document. Render this inside an iframe or a sandboxed div.
  • cardCount: Estimated number of cards generated.

Actions

Generate cards

{
  "action": "generate",
  "content": "今天分享三个提升专注力的方法...",
  "colorScheme": "warm-brown",
  "openrouterApiKey": "sk-or-..."
}

Color scheme options

idDescription
autoAI picks colors based on content mood
warm-brownPrimary #3E2723, background #FFFCF8 — cozy editorial
sunsetPrimary #FF6B6B, secondary #FFD93D — vibrant warm
oceanPrimary #4A90E2, secondary #50C9CE — fresh cool
forestPrimary #2D6A4F, secondary #52B788 — natural green
lavenderPrimary #9D84B7, secondary #C8B6E2 — soft purple
monochromePrimary #2C3E50, accent #E74C3C — clean minimal

Card layout specification

The generated HTML follows these rules so downstream renderers can reliably parse it:

  • Outer container: div with display:flex; flex-direction:column; gap:20px
  • Each card: div with width:450px; height:600px; position:relative; overflow:hidden
  • Card backgrounds: warm paper tones — #FDF8F3, #F5EFE6, #FFFBF5, #F0EBE3 — varied per card
  • Top accent strip: div with height:8px; width:100% in a warm accent color
  • Typography:

- Card title / section number: 30–38 px, font-weight:700, Playfair Display or Space Grotesk - Body text: 15–17 px, line-height:1.75, Noto Sans SC or Inter - Labels / captions: 12–13 px, muted color

  • Text colors: coffee-brown tones #3E2723, #664A42, #5D4037
  • Accent shapes: left-border bars (6 px wide), bullet circles (10×10 px), number badges (32×32 px, border-radius 16 px)
  • NO emojis in generated content
  • Fonts imported via @import inside <style> — never via <link> tags

Card types

The AI selects the best card type for each section of the content:

Card typeWhen to use
Title card (first)Large decorative title + subtitle + author/tag label
Section headerBold large number (01, 02…) + section heading + 1-sentence teaser
Text blockBody paragraphs with colored left-accent bar
Bullet listKey points as rows with filled-circle bullet shapes
Numbered stepsStep-by-step instructions with rounded number badges
Quote / highlightOne key sentence enlarged (28–34 px), centered, with decorative quote marks
Summary (last)Recap of core message + thin decorative bottom strip

System prompt used

When calling the LLM, the following system instruction is used:

You are an expert graphic designer who generates production-ready HTML layouts with embedded CSS. Your output is a complete, self-contained HTML document that can be rendered directly in a browser. Output ONLY valid HTML. No markdown, no code fences, no explanation. Include a <style> tag with all CSS. Do NOT use Noto Sans SC. Do NOT set margin or padding on html or body tags. Do NOT use global CSS resets.

User prompt template

The user message sent to the LLM is constructed as follows:

This is a Xiaohongshu (小红书) carousel post. Generate MULTIPLE vertical cards (each 450×600px) stacked vertically with 20px gap between them.

CONTENT FIDELITY — INCLUDE EVERYTHING:
- Cover ALL of the user's text. Do NOT omit, summarize, or skip any sentence.
- Distribute content logically across cards: one topic or section per card.
- Generate as many cards as needed to fit all content (typically 3–10 cards).

Content to include:
"<USER_CONTENT>"

<COLOR_INSTRUCTION>

Return ONLY valid HTML with embedded CSS. No markdown, no code fences, no explanation.

Where <COLOR_INSTRUCTION> is:

  • If colorScheme is auto: Analyze the content and choose bold, contextually appropriate colors and modern typography.
  • Otherwise: Color Palette — foundation colors are: "<primary>" (primary) and "<secondary>" (secondary). Use them as the dominant palette with tints and shades for depth. Do NOT apply them flatly.

API call details

POST https://openrouter.ai/api/v1/chat/completions
Authorization: Bearer <openrouterApiKey>
Content-Type: application/json

{
  "model": "google/gemini-2.5-flash",
  "messages": [
    { "role": "system", "content": "<SYSTEM_PROMPT>" },
    { "role": "user",   "content": "<USER_PROMPT>" }
  ],
  "stream": true,
  "temperature": 0.4
}

Fallback model order: google/gemini-2.5-flashgoogle/gemini-2.5-flash-lite

Post-processing steps

After receiving the full streamed HTML, apply these cleanup steps in order:

  1. Strip leading/trailing markdown fences ( `html ` ) if present.
  2. Fix broken <img> tags — collapse internal whitespace/newlines to a single space.
  3. If the output does not contain <html or <!DOCTYPE, wrap it:
   <!DOCTYPE html><html lang="zh-CN"><head><meta charset="UTF-8"><title>RedNote</title></head><body>…</body></html>
  1. Count the number of card div elements to populate cardCount in the response.

Ideas to try

  • Paste a WeChat article and get a ready-to-publish 小红书 carousel.
  • Summarize a product review into a 5-card visual post.
  • Turn meeting notes into a step-by-step visual guide.
  • Convert a recipe into numbered-step cards with a title cover.

适合场景

01

调用多模型

02

代码和文本生成

03

Agent 推理流程

04

OpenRouter 模型接入

能力概览

能力 1

统一调用多种 LLM

能力 2

支持 Claude、Gemini、Kimi 等模型

能力 3

适合聊天、代码和推理任务

能力 4

可作为 Agent 模型调用入口

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

72.83%
按下载量换算3,506

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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