JimLiu-baoyu-skills/skills/baoyu-xhs-images/SKILL.md

name	description
baoyu-xhs-images	Xiaohongshu (Little Red Book) infographic series generator with multiple style options. Breaks down content into 1-10 cartoon-style infographics. Use when user asks to create "小红书图片", "XHS images", or "RedNote infographics".

Xiaohongshu Infographic Series Generator

Break down complex content into eye-catching infographic series for Xiaohongshu with multiple style options.

Usage

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

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

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

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

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

# Direct input with options
/baoyu-xhs-images --style bold --layout comparison
[paste content]

Options

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

Two Dimensions

Dimension	Controls	Options
Style	Visual aesthetics: colors, lines, decorations	cute, fresh, tech, warm, bold, minimal, retro, pop, notion
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

Style	Description
cute (Default)	Sweet, adorable, girly - classic Xiaohongshu aesthetic
fresh	Clean, refreshing, natural
tech	Modern, smart, digital
warm	Cozy, friendly, approachable
bold	High impact, attention-grabbing
minimal	Ultra-clean, sophisticated
retro	Vintage, nostalgic, trendy
pop	Vibrant, energetic, eye-catching
notion	Minimalist hand-drawn line art, intellectual

Detailed style definitions: references/styles/<style>.md

Layout Gallery

Layout	Description
sparse (Default)	Minimal information, maximum impact (1-2 points)
balanced	Standard content layout (3-4 points)
dense	High information density, knowledge card style (5-8 points)
list	Enumeration and ranking format (4-7 items)
comparison	Side-by-side contrast layout
flow	Process and timeline layout (3-6 steps)

Detailed layout definitions: references/layouts/<layout>.md

Auto Style Selection

When no --style is specified, analyze content to select:

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

Auto Layout Selection

When no --layout is specified, analyze content structure to select:

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

Layout by Position:

Position	Recommended Layout
Cover	sparse
Content	balanced or 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
    │   ├── 02-content-1.md
    │   └── ...
    ├── 01-cover.png
    ├── 02-content-1.png
    └── 03-ending.png

Without Article Path

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

xhs-outputs/
└── 2026-01-13/
    └── ai-agent-guide/
        ├── outline.md
        ├── prompts/
        │   ├── 01-cover.md
        │   └── ...
        ├── 01-cover.png
        └── 02-ending.png

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 based on content complexity:

Content Type	Image Count
Simple opinion / single topic	2-3
Medium complexity / tutorial	4-6
Deep dive / multi-dimensional	7-10

Note: Layout can vary per image in a series. Cover typically uses sparse, content pages use balanced/dense/list as appropriate.

Step 2: Generate Outline

Plan for each image with style and layout specifications:

# Xiaohongshu Infographic Series Outline

**Topic**: [topic description]
**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]

---

## Image 2 of N

**Position**: Content
**Layout**: [balanced/dense/list/comparison/flow]
**Core Message**: [one-liner]
**Filename**: 02-xxx.png

**Text Content**:
- Title: xxx
- Points: [list based on layout density]

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

---
...

Step 3: Save Outline

Save outline as outline.md.

Step 4: Generate Images One by One

For each image, create a prompt file with style and layout specifications.

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: [style primary color]
- Background: [style background color]
- Accent: [style accent color]

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

Layout instructions: [layout-specific guidance]
Style notes: [style-specific characteristics]

Layout-Specific Instructions:

Layout	Arrangement Instructions
sparse	Single focal point centered, 1-2 text elements, maximum breathing room
balanced	Title at top, 3-4 points in clear sections, moderate spacing
dense	Grid or multi-section layout, 5-8 points, compact but organized
list	Vertical numbered/bulleted list, consistent item spacing, clear hierarchy
comparison	Two-column split, clear divider, mirrored structure left/right
flow	Horizontal or vertical flow with arrows, connected nodes/steps

Image Generation Skill Selection:

1. Check available image generation skills
2. If multiple skills available, ask user to choose

Session Management: If the image generation skill supports --sessionId:

1. Generate a unique session ID at the start (e.g., xhs-{topic-slug}-{timestamp})
2. Use the same session ID for all images in the series
3. This ensures style consistency across all generated images

Generation Flow:

1. Call selected image generation skill with prompt file, output path, and session ID
2. Confirm generation success
3. Report progress: "Generated X/N"
4. Continue to next

Step 5: 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-content-2.png ✓ Content (dense)
- 04-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 → balanced/dense/list/comparison/flow
3. Ending (Last): Summary / call-to-action / memorable quote → sparse or balanced

Style × Layout Matrix (recommended combinations):

	sparse	balanced	dense	list	comparison	flow
cute	✓✓	✓✓	✓	✓✓	✓	✓
fresh	✓✓	✓✓	✓	✓	✓	✓✓
tech	✓	✓✓	✓✓	✓✓	✓✓	✓✓
warm	✓✓	✓✓	✓	✓	✓✓	✓
bold	✓✓	✓	✓	✓✓	✓✓	✓
minimal	✓✓	✓✓	✓✓	✓	✓	✓
retro	✓✓	✓✓	✓	✓✓	✓	✓
pop	✓✓	✓✓	✓	✓✓	✓✓	✓
notion	✓✓	✓✓	✓✓	✓✓	✓✓	✓✓

✓✓ = highly recommended, ✓ = works well

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