Xiaohongshu Infographic Series Generator

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

Usage

bash

# 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 Selection

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

File Structure

Each session creates an independent directory named by content slug:

xhs-images/{topic-slug}/
├── source-{slug}.{ext}             # Source files (text, images, etc.)
├── analysis.md                     # Deep analysis results
├── outline-style-[slug].md         # Variant A (e.g., outline-style-tech.md)
├── outline-style-[slug].md         # Variant B (e.g., outline-style-notion.md)
├── outline-style-[slug].md         # Variant C (e.g., outline-style-minimal.md)
├── outline.md                      # Final selected
├── prompts/
│   ├── 01-cover-[slug].md
│   ├── 02-content-[slug].md
│   └── ...
├── 01-cover-[slug].png
├── 02-content-[slug].png
└── NN-ending-[slug].png

Slug Generation:

Extract main topic from content (2-4 words, kebab-case)
Example: "AI工具推荐" →
```
ai-tools-recommend
```

Conflict Resolution: If

xhs-images/{topic-slug}/

already exists:

Append timestamp:
```
{topic-slug}-YYYYMMDD-HHMMSS
```
Example:
```
ai-tools
```
exists →
```
ai-tools-20260118-143052
```

Source Files: Copy all sources with naming

source-{slug}.{ext}

```
source-article.md
```
,
```
source-photo.jpg
```
, etc.
Multiple sources supported: text, images, files from conversation

Workflow

Step 1: Analyze Content →

analysis.md

Read source content, save it if needed, and perform deep analysis.

Actions:

Save source content (if not already a file):
- If user provides a file path: use as-is
- If user pastes content: save to
```
source.md
```
  in target directory
Read source content
Deep analysis following
```
references/analysis-framework.md
```
:
- Content type classification (种草/干货/测评/教程/避坑...)
- Hook analysis (爆款标题潜力)
- Target audience identification
- Engagement potential (收藏/分享/评论)
- Visual opportunity mapping
- Swipe flow design
Detect source language
Determine recommended image count (2-10)
Select 3 style+layout combinations
Save to
analysis.md

Step 2: Generate 3 Outline Variants

Based on analysis, create three distinct style variants.

For each variant:

Generate outline (
```
outline-style-[slug].md
```
):
- YAML front matter with style, layout, image_count
- Cover design with hook
- Each image: layout, core message, text content, visual concept
- Written in user's preferred language
- Reference:
```
references/outline-template.md
```

Variant	Selection Logic	Example Filename
A	Primary recommendation	`outline-style-tech.md`
B	Alternative style	`outline-style-notion.md`
C	Different audience/mood	`outline-style-minimal.md`

All variants are preserved after selection for reference.

Step 3: User Confirms All Options

IMPORTANT: Present ALL options in a single confirmation step using AskUserQuestion. Do NOT interrupt workflow with multiple separate confirmations.

Determine which questions to ask:

Question	When to Ask
Style variant	Always (required)
Default layout	Only if user might want to override
Language	Only if `source_language ≠ user_language`

Language handling:

If source language = user language: Just inform user (e.g., "Images will be in Chinese")
If different: Ask which language to use

AskUserQuestion format:

Question 1 (Style): Which style variant?
- A: tech + dense (Recommended) - 专业科技感，适合干货
- B: notion + list - 清爽知识卡片
- C: minimal + balanced - 简约高端风格
- Custom: 自定义风格描述

Question 2 (Layout) - only if relevant:
- Keep variant default (Recommended)
- sparse / balanced / dense / list / comparison / flow

Question 3 (Language) - only if mismatch:
- 中文 (匹配原文)
- English (your preference)

After confirmation:

Copy selected
```
outline-style-[slug].md
```
→
```
outline.md
```
Update YAML front matter with confirmed options
If custom style: regenerate outline with that style
User may edit
```
outline.md
```
directly for fine-tuning

Step 4: Generate Images

With confirmed outline + style + layout:

For each image (cover + content + ending):

Save prompt to
```
prompts/NN-{type}-[slug].md
```
(in user's preferred language)
Generate image using confirmed style and layout
Report progress after each generation

Image Generation Skill Selection:

Check available image generation skills
If multiple skills available, ask user preference

Session Management: If image generation skill supports

--sessionId

Generate unique session ID:
```
xhs-{topic-slug}-{timestamp}
```
Use same session ID for all images
Ensures visual consistency across generated images

Step 5: Completion Report

Xiaohongshu Infographic Series Complete!

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

✓ analysis.md
✓ outline-style-tech.md
✓ outline-style-notion.md
✓ outline-style-minimal.md
✓ outline.md (selected: tech + dense)

Files:
- 01-cover-[slug].png ✓ Cover (sparse)
- 02-content-[slug].png ✓ Content (balanced)
- 03-content-[slug].png ✓ Content (dense)
- 04-ending-[slug].png ✓ Ending (sparse)

Image Modification

Edit Single Image

Identify image to edit (e.g.,
```
03-content-chatgpt.png
```
)
Update prompt in
```
prompts/03-content-chatgpt.md
```
if needed
Regenerate image using same session ID

Add New Image

Specify insertion position (e.g., after image 3)
Create new prompt with appropriate slug
Generate new image
Renumber files: All subsequent images increment NN by 1
Update
```
outline.md
```
with new image entry

Delete Image

Remove image file and prompt file
Renumber files: All subsequent images decrement NN by 1
Update
```
outline.md
```
to remove image entry

Content Breakdown Principles

Cover (Image 1): Hook + visual impact →
```
sparse
```
layout
Content (Middle): Core value per image →
```
balanced
```
/
```
dense
```
/
```
list
```
/
```
comparison
```
/
```
flow
```
Ending (Last): CTA / summary →
```
sparse
```
or
```
balanced
```

Style × Layout Matrix (✓✓ = highly recommended, ✓ = works well):

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

References

Detailed templates and guidelines in

references/

directory:

```
analysis-framework.md
```
- XHS-specific content analysis
```
outline-template.md
```
- Outline format and examples
```
styles/<style>.md
```
- Detailed style definitions
```
layouts/<layout>.md
```
- Detailed layout definitions
```
base-prompt.md
```
- Base prompt template

Notes

Image generation typically takes 10-30 seconds per image
Auto-retry once on generation failure
Use cartoon alternatives for sensitive public figures
All prompts and text use confirmed language preference
Maintain style consistency across all images in series

Extension Support

Custom styles and configurations via EXTEND.md.

Check paths (priority order):

.baoyu-skills/baoyu-xhs-images/EXTEND.md

(project)

~/.baoyu-skills/baoyu-xhs-images/EXTEND.md

(user)

If found, load before Step 1. Extension content overrides defaults.

baoyu-xhs-images

NPX Install

Tags

SKILL.md Content