Xiaohongshu Infographic Series Generator

Break down complex content into eye-catching infographic series for Xiaohongshu.

Usage

# Auto-select style and layout based on content
/xhs-images posts/ai-future/article.md

# Specify style
/xhs-images posts/ai-future/article.md --style notion

# Specify layout
/xhs-images posts/ai-future/article.md --layout dense

# Combine style and layout
/xhs-images posts/ai-future/article.md --style tech --layout list

# Direct content input
/xhs-images
[paste content]

Options

Option	Description
--style <name>	Visual style (see Style Gallery below)
--layout <name>	Information layout (see Layout Gallery below)

Two Dimensions

Dimension	Controls	Options
Style	Visual aesthetics: colors, lines, decorations	cute, fresh, tech, warm, bold, minimal, retro, pop, notion, productivity, insight
Layout	Information structure: density, arrangement	sparse, balanced, dense, list, comparison, flow

Style × Layout can be freely combined. Example: --style notion --layout dense creates an intellectual-looking knowledge card with high information density.

Style Gallery (Quick Reference)

Style	Description	Best For
cute	Sweet, adorable, girly - classic XHS aesthetic	Lifestyle, beauty, fashion
fresh	Clean, refreshing, natural	Health, wellness, self-care
tech	Modern, smart, digital	Tech tutorials, AI content
warm	Cozy, friendly, approachable	Personal stories, life lessons
bold	High impact, attention-grabbing	Important tips, warnings
minimal	Ultra-clean, sophisticated	Professional content
retro	Vintage, nostalgic, trendy	Throwback, classic tips
pop	Vibrant, energetic, eye-catching	Fun facts, announcements
notion	Minimalist hand-drawn line art	Knowledge sharing, SaaS
productivity	Structured, light mode, clean UI	How-to tutorials, tools
insight	High clarity, dark mode, premium	Mental models, deep thoughts

For detailed style specs (colors, elements, typography): See references/styles.md

Layout Gallery (Quick Reference)

Layout	Density	Best For
sparse	1-2 points, 60-70% whitespace	Covers, quotes, impactful statements
balanced	3-4 points, 40-50% whitespace	Regular content, tutorials
dense	5-8 points, 20-30% whitespace	Summary cards, cheat sheets
list	4-7 items, 30-40% whitespace	Top N lists, checklists
comparison	2×2-4 points, 30-40% whitespace	Before/After, pros/cons
flow	3-6 steps, 30-40% whitespace	Processes, timelines

For detailed layout specs and Style×Layout matrix: See references/layouts.md

Auto Selection Logic

Auto Style Selection

Content Signals	Selected Style
Beauty, fashion, cute, girl, pink	cute
Health, nature, clean, fresh	fresh
Tech, AI, code, digital, app, tool	tech
Life, story, emotion, feeling	warm
Warning, important, must, critical	bold
Professional, business, elegant	minimal
Classic, vintage, old, traditional	retro
Fun, exciting, wow, amazing	pop
Knowledge, concept, productivity, SaaS	notion
How-to, tutorial, tool recommendation	productivity
Mental model, deep thought, insight	insight

Auto Layout Selection

Content Signals	Selected Layout
Single quote, one key point, cover	sparse
3-4 points, explanation, tutorial	balanced
5+ points, summary, cheat sheet	dense
Numbered items, top N, checklist	list
vs, compare, before/after, pros/cons	comparison
Process, flow, timeline, ordered steps	flow

Layout by Position

Position	Recommended Layout
Cover	sparse
Content	balanced / dense / list (content-appropriate)
Ending	sparse or balanced

File Management

With Article Path

Save to xhs-images/ subdirectory in the same folder as the article:

posts/ai-future/
├── article.md
└── xhs-images/
    ├── outline.md
    ├── prompts/
    │   ├── 01-cover.md
    │   └── ...
    ├── 01-cover.png
    └── 02-ending.png

Without Article Path

Save to xhs-outputs/YYYY-MM-DD/[topic-slug]/

Workflow

Step 1: Analyze Content & Select Style/Layout

1. Read content
2. If --style specified, use that style; otherwise auto-select
3. If --layout specified, use that layout; otherwise auto-select per image
4. Determine image count:
   • Simple topic: 2-3 images
   • Medium complexity: 4-6 images
   • Deep dive: 7-10 images

Step 2: Generate Outline

Plan for each image with style and layout specifications. Save as outline.md:

# Xiaohongshu Infographic Series Outline

**Topic**: [topic]
**Style**: [selected style]
**Default Layout**: [selected layout or "varies"]
**Image Count**: N
**Generated**: YYYY-MM-DD HH:mm

---

## Image 1 of N

**Position**: Cover
**Layout**: sparse
**Core Message**: [one-liner]
**Filename**: 01-cover.png

**Text Content**:
- Title: xxx
- Subtitle: xxx

**Visual Concept**: [style + layout appropriate description]

---
...

Step 3: Generate Images One by One

For each image:

1. Read style details from references/styles.md (load target style section only)
2. Read layout details from references/layouts.md (load target layout section only)
3. Create prompt file in prompts/ directory
4. Generate using:

/gemini-web --promptfiles [SKILL_ROOT]/prompts/system.md [TARGET_DIR]/prompts/01-cover.md --image [TARGET_DIR]/01-cover.png

Prompt Format:

Infographic theme: [topic]
Style: [style name]
Layout: [layout name]
Position: [cover/content/ending]

Visual composition:
- Main visual: [style-appropriate description]
- Arrangement: [layout-specific structure]
- Decorative elements: [style-specific decorations]

Color scheme:
- Primary: [from style spec]
- Background: [from style spec]
- Accent: [from style spec]

Text content:
- Title: 「xxx」(large, prominent)
- Key points: [based on layout density]

Layout instructions: [from layout spec]
Style notes: [from style spec]

Step 4: Completion Report

Xiaohongshu Infographic Series Complete!

Topic: [topic]
Style: [style name]
Layout: [layout name or "varies"]
Location: [directory path]
Images: N total

- 01-cover.png ✓ Cover (sparse)
- 02-content-1.png ✓ Content (balanced)
- 03-ending.png ✓ Ending (sparse)

Outline: outline.md

Content Breakdown Principles

1. Cover (Image 1): Strong visual impact, core title, attention hook → sparse layout
2. Content (Middle): Core points per image, density varies by content
3. Ending (Last): Summary / call-to-action / memorable quote → sparse or balanced

Notes

• Image generation typically takes 10-30 seconds per image
• Auto-retry once on generation failure
• Use cartoon alternatives for sensitive public figures
• Output language matches input content language
• Maintain selected style consistency across all images in series