Visual Note Card logo

Visual Note Card

Community
beilunyang
visual-note-card

Generate professional Chinese visual note cards (视觉笔记卡片/信息图) as single-page HTML infographics with automatic PNG export. Use this skill whenever the user asks to create a visual note, knowledge card, infographic, one-pager summary, visual summary, 知识卡片, 视觉笔记, 信息图, 一页纸总结, or any poster-style knowledge visualization. Also trigger when the user wants to summarize an article, blog post, book chapter, or concept into a structured visual card format, or when they reference an existing visual note and ask to create one in the same style. This skill produces both a self-contained HTML file and a high-quality PNG image, ready for sharing on social media or printing.

Overview

Publisherbeilunyang
Repositoryvisual-note-card-skills
Skill namevisual-note-card
Stars
84
Forks
2
Bundled files
4
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by beilunyang on GitHub. Read the source before you install it.

Installation

Install the Visual Note Card AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/beilunyang/visual-note-card-skills/tree/main
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/beilunyang/visual-note-card-skills.git \
  .claude/skills/visual-note-card
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Visual Note Card in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Visual Note Card on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Visual Note Card is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Visual Note Card Generator

Create professional, information-dense visual note cards (视觉笔记/信息图) as self-contained HTML files with automatic PNG export via Playwright. The output is a structured, poster-style infographic with modular card layout, suitable for social media sharing or printing.

Design System

Before writing any code, read the reference template at assets/template.html for the canonical HTML/CSS structure. Then adapt the content to the user's topic.

Core Visual Identity

The design follows an editorial knowledge card aesthetic — high information density with clear visual hierarchy, inspired by premium magazine layouts and structured note-taking.

Color Palette (CSS Variables):

  • --primary: Deep teal #1a7a6d — headers, badges, accent elements
  • --primary-dark: #145f54 — bottom highlight bar
  • --primary-deep: #0d3d36 — deep accent
  • --accent: Orange #e8713a — emphasis, secondary badges, important labels
  • --bg: Warm gray #f0ebe4 — page background
  • --bg-light: #f5f1ec — light panel background
  • --bg-card: #e8e3dc — framework card background
  • --black: #1a1a1a — dark panel, primary text
  • --white: #ffffff

Users may request alternate color schemes. If so, maintain the same structural contrast ratios: one warm neutral background, one strong primary color, one accent color, and black for dark panels.

Typography:

  • English display: Playfair Display (serif, 700/900) — main title
  • Chinese body: Noto Sans SC (400/500/700/900) — all Chinese text
  • Monospace: JetBrains Mono (500/700) — labels, URLs, tags
  • Import via Google Fonts in the <style> block

Layout — Fixed Poster Dimensions:

  • Container width: 1200px
  • Padding: 36px 40px 28px
  • Background: var(--bg)

Mandatory Layout Sections (Top to Bottom)

Every visual note card MUST include these sections in order:

1. Top Bar

A single-line flex row with:

  • Left: Topic label in uppercase monospace (e.g., AI PRODUCT ARCHITECTURE · SYSTEM DESIGN)
  • Right: Source label (e.g., OPENAI ENGINEERING BLOG)
2. Main Title Area

Two-column flex layout:

  • Left: Large bilingual title — English line in Playfair Display 38px, Chinese line in Noto Sans SC 40px colored with var(--primary)
  • Right: A 2–3 line thesis statement (核心观点) summarizing the card's argument, with the key phrase in <strong>. Optionally include a source URL below.
3. Framework Row (Flexible Grid, Recommended 4 Columns)

A row of equal-width cards representing the core framework/model of the topic. The number of columns is flexible — choose based on the actual content:

  • 2 columns — binary concepts, comparisons (e.g., Before vs After, Input vs Output)
  • 3 columns — triads, triangular models (e.g., People-Process-Technology)
  • 4 columns — recommended default, most common for frameworks (e.g., E-K-C-F, M-P-D-G)
  • 5 columns — five-element models (e.g., HEART metrics, Five Forces)
  • 6 columns — extended taxonomies (use sparingly, keep descriptions very short)

Analyze the topic and choose the column count that best fits the natural structure. Don't force 4 columns if the concept has 3 or 5 natural parts.

CSS implementation: Use grid-template-columns: repeat(N, 1fr) where N is the chosen column count.

Card structure (same regardless of column count):

  • Each card has a colored square letter badge (first letter of the concept) + Chinese name
  • Below the badge: 1–2 lines of description with one <strong> keyword
  • For 5–6 columns, keep descriptions to 1 line to avoid overflow

Badge color rotation (cycles through these in order):

  1. --primary (teal)
  2. --primary (teal)
  3. --accent (orange)
  4. --primary-deep (deep teal)
  5. --accent (orange) — if 5th column exists
  6. --primary (teal) — if 6th column exists

The framework should be a memorable acronym (e.g., E-K-C-F, M-P-D-G). Invent one if the source doesn't provide it.

4. Two-Column Content Area

A grid-template-columns: 1fr 1fr layout:

Left: Dark Panel (background: var(--black), white text)

  • Section title with emoji icon (⚡, 🔥, 🛠, etc.)
  • 2 sub-blocks, each with an orange title (var(--accent)) and a bulleted list (custom ■ bullets in teal)
  • List items use <strong> for key phrases (white color)
  • A bottom "conclusion" block with a divider line and a memorable quote/insight (key phrase in #5ee6d0 mint color)

Right: Light Panel (background: var(--bg-light))

  • Section title with star icon (★)
  • 3–4 numbered insight items, each with:
    • A large serif number (Playfair Display 36px, teal)
    • Bold title line
    • 1–2 lines of description with <strong> keywords
5. Bottom Highlight Bar

Full-width bar with background: var(--primary-dark):

  • Left: The framework formula (e.g., Architecture = M × P × D × G) in mint highlight color #5ee6d0
  • Right: A closing thought in lighter text
6. Footer

Flex row:

  • Left: Framework label in monospace
  • Right: Brand / framework name with a small teal dot separator

Content Strategy

When the user provides a topic (or an article URL/text):

  1. Extract or synthesize a 4-part framework — find the core structural model. If one doesn't exist, create a meaningful decomposition with a memorable acronym.
  2. Write a provocative thesis — the right-side subtitle should be a strong, opinionated claim, not a bland description.
  3. Dark panel = "Story + Transformation" — use this for narrative content: problems, transitions, role changes, paradigm shifts.
  4. Light panel = "Pitfalls or Insights" — use this for actionable numbered takeaways.
  5. Bottom formula — distill the entire card into one equation-style summary.
  6. All text is Chinese except for: the main English title line, technical terms, framework acronyms, and footer labels.

Output

Default: HTML + PNG

By default, generate both an HTML file and a PNG image:

  1. Generate the HTML — single self-contained .html file with all CSS inline. No external dependencies except Google Fonts and html2canvas CDN. Save to /mnt/user-data/outputs/.
  2. Generate the PNG — run the bundled scripts/html2png.py script to render the HTML into a high-quality PNG image.
bash
python <skill-path>/scripts/html2png.py /mnt/user-data/outputs/card.html /mnt/user-data/outputs/card.png --scale=1.5

Present both files to the user (PNG first, then HTML). The PNG is the primary deliverable for sharing; the HTML enables further browser-based export or editing.

If the user explicitly asks for "只要 HTML" or "HTML only", skip the PNG step.

PNG Generation Script: scripts/html2png.py

A Playwright-based headless renderer. It opens the HTML in Chromium, waits for Google Fonts to load, hides the FAB button, then screenshots the .poster element.

Usage:

bash
python html2png.py <input.html> [output.png] [--scale=N]

Scale options:

  • --scale=1 — standard (1200px wide), smallest file
  • --scale=1.5 — default, recommended for social media (1800px wide)
  • --scale=2 — print quality (2400px wide)

Dependencies: playwright (pip install playwright && playwright install chromium). Pre-installed on Claude's compute environment.

Download Button (Mandatory in HTML)

Every generated HTML card MUST include a floating action button (FAB) in the bottom-right corner with a dropdown menu for export options:

  • 标准 PNG — 1× scale, quick sharing
  • 高清 PNG — 1.5× scale, social media recommended
  • 超清 PNG — 2× scale, for printing
  • JPEG — 1.5× scale, smaller file size

Implementation:

  1. Add <script src="https://cdnjs.cloudflare.com/ajax/libs/html2canvas/1.4.1/html2canvas.min.js"></script> before </body>
  2. The FAB (div.fab-wrap) is placed OUTSIDE .poster so it won't appear in the exported image
  3. Clicking the FAB toggles a dropdown menu upward; clicking outside closes it
  4. During capture, the FAB is hidden and a toast spinner ("正在导出…") is shown
  5. The FAB icon toggles between a download arrow and a close ×
  6. The exported filename is derived from document.title + scale suffix

See assets/template.html for the complete FAB HTML, CSS, and JS.

Copyright (Mandatory)

Every card MUST include a copyright bar inside the .poster div (below the footer, separated by a thin border-top), so it appears in both the HTML page and the exported PNG:

html
<div class="copyright-bar">
  <svg><!-- GitHub icon --></svg>
  <span>Generated by <a href="https://github.com/beilunyang/visual-note-card-skills">https://github.com/beilunyang/visual-note-card-skills</a></span>
</div>

Example Prompts → Expected Behavior

User SaysAction
"帮我做一张关于 RAG 架构的视觉笔记"Generate HTML + PNG about RAG architecture
"把这篇文章做成信息图" + article textExtract key ideas, synthesize framework, generate HTML + PNG
"生成一张同风格的卡片,主题是微服务"Generate HTML + PNG about microservices
"Create a visual note about product-market fit"Generate bilingual HTML + PNG about PMF
"只要 HTML,不要图片"Generate HTML only, skip PNG
"生成一张 2x 高清的 PNG"Generate HTML + PNG with --scale=2

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Visual Note Card AI skill do?

Generate professional Chinese visual note cards (视觉笔记卡片/信息图) as single-page HTML infographics with automatic PNG export. Use this skill whenever the user asks to create a visual note, knowledge card, infographic, one-pager summary, visual summary, 知识卡片, 视觉笔记, 信息图, 一页纸总结, or any poster-style knowledge visualization. Also trigger when the user wants to summarize an article, blog post, book chapter, or concept into a structured visual card format, or when they reference an existing visual note and ask to create one in the same style. This skill produces both a self-contained HTML file and a hi...

Why use Visual Note Card on TypingMind?

Because you install it once and use it with any model. Visual Note Card is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Visual Note Card in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/beilunyang/visual-note-card-skills/tree/main. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Visual Note Card?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Visual Note Card?

As many as you like. As long as a model supports skills, you can use Visual Note Card with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Visual Note Card AI skill free?

Yes. It is published on GitHub by beilunyang under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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