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Baoyu Xhs Images

Community
ynulihao
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".

Overview

Publisherynulihao
RepositoryAgentSkillOS
Skill namebaoyu-xhs-images
Stars
612
Forks
76
Bundled files
18
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.

  • 18 bundled files

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

  • Open source

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

Installation

Install the Baoyu Xhs Images 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.
  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/ynulihao/AgentSkillOS.git /tmp/AgentSkillOS
mkdir -p .claude/skills
cp -r /tmp/AgentSkillOS/data/skill_seeds/baoyu-xhs-images .claude/skills/baoyu-xhs-images
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Baoyu Xhs Images 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 Baoyu Xhs Images 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 Baoyu Xhs Images 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.

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

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

Two Dimensions

DimensionControlsOptions
StyleVisual aesthetics: colors, lines, decorationscute, fresh, tech, warm, bold, minimal, retro, pop, notion
LayoutInformation structure: density, arrangementsparse, 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

StyleDescription
cute (Default)Sweet, adorable, girly - classic Xiaohongshu aesthetic
freshClean, refreshing, natural
techModern, smart, digital
warmCozy, friendly, approachable
boldHigh impact, attention-grabbing
minimalUltra-clean, sophisticated
retroVintage, nostalgic, trendy
popVibrant, energetic, eye-catching
notionMinimalist hand-drawn line art, intellectual

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

Layout Gallery

LayoutDescription
sparse (Default)Minimal information, maximum impact (1-2 points)
balancedStandard content layout (3-4 points)
denseHigh information density, knowledge card style (5-8 points)
listEnumeration and ranking format (4-7 items)
comparisonSide-by-side contrast layout
flowProcess and timeline layout (3-6 steps)

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

Auto Selection

Content SignalsStyleLayout
Beauty, fashion, cute, girl, pinkcutesparse/balanced
Health, nature, clean, fresh, organicfreshbalanced/flow
Tech, AI, code, digital, app, tooltechdense/list
Life, story, emotion, feeling, warmwarmbalanced
Warning, important, must, criticalboldlist/comparison
Professional, business, elegant, simpleminimalsparse/balanced
Classic, vintage, old, traditionalretrobalanced
Fun, exciting, wow, amazingpopsparse/list
Knowledge, concept, productivity, SaaSnotiondense/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:

  1. Extract main topic from content (2-4 words, kebab-case)
  2. 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:

  1. 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
  2. Read source content
  3. 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
  4. Detect source language
  5. Determine recommended image count (2-10)
  6. Select 3 style+layout combinations
  7. Save to analysis.md

Step 2: Generate 3 Outline Variants

Based on analysis, create three distinct style variants.

For each variant:

  1. 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
VariantSelection LogicExample Filename
APrimary recommendationoutline-style-tech.md
BAlternative styleoutline-style-notion.md
CDifferent audience/moodoutline-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:

QuestionWhen to Ask
Style variantAlways (required)
Default layoutOnly if user might want to override
LanguageOnly 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:

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

Step 4: Generate Images

With confirmed outline + style + layout:

For each image (cover + content + ending):

  1. Save prompt to prompts/NN-{type}-[slug].md (in user's preferred language)
  2. Generate image using confirmed style and layout
  3. 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:

  1. Generate unique session ID: xhs-{topic-slug}-{timestamp}
  2. Use same session ID for all images
  3. 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

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

Add New Image

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

Delete Image

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

Content Breakdown Principles

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

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

sparsebalanceddenselistcomparisonflow
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):

  1. .baoyu-skills/baoyu-xhs-images/EXTEND.md (project)
  2. ~/.baoyu-skills/baoyu-xhs-images/EXTEND.md (user)

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

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 Baoyu Xhs Images AI skill do?

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".

Why use Baoyu Xhs Images on TypingMind?

Because you install it once and use it with any model. Baoyu Xhs Images 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 Baoyu Xhs Images in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ynulihao/AgentSkillOS/tree/main/data/skill_seeds/baoyu-xhs-images. 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 Baoyu Xhs Images?

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 Baoyu Xhs Images?

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

Is the Baoyu Xhs Images AI skill free?

It is published on GitHub by ynulihao. Check the repository for licensing terms. 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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