Baoyu Comic logo

Baoyu Comic

Community
smallnest
baoyu-comic

Knowledge comic creator supporting multiple styles (Logicomix/Ligne Claire, Ohmsha manga guide). Creates original educational comics with detailed panel layouts and sequential image generation. Use when user asks to create "知识漫画", "教育漫画", "biography comic", "tutorial comic", or "Logicomix-style comic".

Overview

Publishersmallnest
Repositorylanggraphgo
Skill namebaoyu-comic
Stars
304
Forks
51
Bundled files
25
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.

  • 25 bundled files

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

  • Open source

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

Installation

Install the Baoyu Comic 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/smallnest/langgraphgo.git /tmp/langgraphgo
mkdir -p .claude/skills
cp -r /tmp/langgraphgo/examples/comic_skill_example/skills/baoyu-comic .claude/skills/baoyu-comic
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Baoyu Comic 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 Comic 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 Comic 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.

Knowledge Comic Creator

Create original knowledge comics with multiple visual styles.

Usage

bash
/baoyu-comic posts/turing-story/source.md
/baoyu-comic  # then paste content

Options

OptionValues
--styleclassic (default), dramatic, warm, sepia, vibrant, ohmsha, realistic, wuxia, shoujo, or custom description
--layoutstandard (default), cinematic, dense, splash, mixed, webtoon
--aspect3:4 (default, portrait), 4:3 (landscape), 16:9 (widescreen)
--langauto (default), zh, en, ja, etc.

Style × Layout × Aspect can be freely combined. Custom styles can be described in natural language.

Aspect ratio is consistent across all pages in a comic.

Auto Selection

Content SignalsStyleLayout
Tutorial, how-to, beginnerohmshawebtoon
Computing, AI, programmingohmshadense
Pre-1950, classical, ancientsepiacinematic
Personal story, mentorwarmstandard
Conflict, breakthroughdramaticsplash
Wine, food, business, lifestyle, professionalrealisticcinematic
Martial arts, wuxia, xianxia, Chinese historicalwuxiasplash
Romance, love, school life, friendship, emotionalshoujostandard
Biography, balancedclassicmixed

Script Directory

Important: All scripts are located in the scripts/ subdirectory of this skill.

Agent Execution Instructions:

  1. Determine this SKILL.md file's directory path as SKILL_DIR
  2. Script path = ${SKILL_DIR}/scripts/<script-name>.ts
  3. Replace all ${SKILL_DIR} in this document with the actual path

Script Reference:

ScriptPurpose
scripts/merge-to-pdf.tsMerge comic pages into PDF

File Structure

Each session creates an independent directory named by content slug:

comic/{topic-slug}/
├── source-{slug}.{ext}            # Source files (text, images, etc.)
├── analysis.md                    # Deep analysis results (YAML+MD)
├── storyboard-chronological.md    # Variant A (preserved)
├── storyboard-thematic.md         # Variant B (preserved)
├── storyboard-character.md        # Variant C (preserved)
├── characters-chronological/      # Variant A chars (preserved)
│   ├── characters.md
│   └── characters.png
├── characters-thematic/           # Variant B chars (preserved)
│   ├── characters.md
│   └── characters.png
├── characters-character/          # Variant C chars (preserved)
│   ├── characters.md
│   └── characters.png
├── storyboard.md                  # Final selected
├── characters/                    # Final selected
│   ├── characters.md
│   └── characters.png
├── prompts/
│   ├── 00-cover-[slug].md
│   └── NN-page-[slug].md
├── 00-cover-[slug].png
├── NN-page-[slug].png
└── {topic-slug}.pdf

Slug Generation:

  1. Extract main topic from content (2-4 words, kebab-case)
  2. Example: "Alan Turing Biography" → alan-turing-bio

Conflict Resolution: If comic/{topic-slug}/ already exists:

  • Append timestamp: {topic-slug}-YYYYMMDD-HHMMSS
  • Example: turing-story exists → turing-story-20260118-143052

Source Files: Copy all sources with naming source-{slug}.{ext}:

  • source-biography.md, source-portrait.jpg, source-timeline.png, 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:
    • Target audience identification
    • Value proposition for readers
    • Core themes and narrative potential
    • Key figures and their story arcs
  4. Detect source language
  5. Determine recommended page count:
    • Short story: 5-8 pages
    • Medium complexity: 9-15 pages
    • Full biography: 16-25 pages
  6. Analyze content signals for style/layout recommendations
  7. Save to analysis.md

analysis.md Format:

yaml
---
title: "Alan Turing: Father of Computing"
topic: Biography
time_span: 1912-1954
source_language: en
user_language: zh
aspect_ratio: "3:4"
recommended_page_count: 12
---

## Target Audience

- **Primary**: Tech enthusiasts curious about computing history
- **Secondary**: Students learning about scientific breakthroughs
- **Tertiary**: General readers interested in biographical stories

## Value Proposition

What readers will gain:
1. Understanding of how modern computing was born
2. Emotional connection to a brilliant but tragic figure
3. Appreciation for the human cost of innovation

## Core Themes

| Theme | Narrative Potential | Visual Opportunity |
|-------|--------------------|--------------------|
| Genius vs. Society | High conflict, dramatic arcs | Contrast scenes |
| Code-breaking | Mystery, tension | Technical diagrams as art |
| Personal tragedy | Emotional depth | Intimate, somber panels |

## Key Figures & Story Arcs

### Alan Turing (Protagonist)
- **Arc**: Misunderstood genius → War hero → Tragic end
- **Visual identity**: Disheveled academic, intense eyes
- **Key moments**: Enigma breakthrough, arrest, final days

### Christopher Morcom (Catalyst)
- **Role**: Early friend whose death shaped Turing
- **Visual identity**: Youthful, bright
- **Key moments**: School friendship, sudden death

## Content Signals

- "biography" → classic + mixed
- "computing history" → ohmsha + dense
- "personal tragedy" → dramatic + splash

## Recommended Approaches

1. **Chronological** - follow life timeline (recommended for biography)
2. **Thematic** - organize by contributions (good for educational focus)
3. **Character-focused** - relationships drive narrative (good for emotional impact)

Step 2: Generate 3 Storyboard Variants

Create three distinct variants, each combining a narrative approach with a recommended style.

VariantNarrative ApproachRecommended StyleLayout
AChronologicalsepiacinematic
BThematicohmshadense
CCharacter-focusedwarmstandard

For each variant:

  1. Generate storyboard (storyboard-{approach}.md):

    • YAML front matter with narrative_approach, recommended_style, recommended_layout, aspect_ratio
    • Cover design
    • Each page: layout, panel breakdown, visual prompts
    • Written in user's preferred language
    • Reference: references/storyboard-template.md
  2. Generate matching characters (characters-{approach}/):

    • characters.md - visual specs matching the recommended style (in user's preferred language)
    • characters.png - character reference sheet
    • Reference: references/character-template.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
Storyboard variantAlways (required)
Visual styleAlways (required)
LanguageOnly if source_language ≠ user_language
Aspect ratioOnly if user might prefer non-default (e.g., landscape content)

Language handling:

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

All storyboards and prompts are generated in the user's selected/preferred language.

Aspect ratio handling:

  • Default: 3:4 (portrait) - standard comic format
  • Offer 4:3 (landscape) if content suits it (e.g., panoramic scenes, technical diagrams)
  • Offer 16:9 (widescreen) for cinematic content

AskUserQuestion format (example with all questions):

Question 1 (Storyboard): Which storyboard variant?
- A: Chronological + sepia (Recommended)
- B: Thematic + ohmsha
- C: Character-focused + warm
- Custom

Question 2 (Style): Which visual style?
- sepia (Recommended from variant)
- classic / dramatic / warm / sepia / vibrant / ohmsha / realistic / wuxia
- Custom description

Question 3 (Language) - only if mismatch:
- Chinese (source material language)
- English (your preference)

Question 4 (Aspect) - only if relevant:
- 3:4 Portrait (Recommended)
- 4:3 Landscape
- 16:9 Widescreen

After confirmation:

  1. Copy selected storyboard → storyboard.md
  2. Copy selected characters → characters/
  3. Update YAML front matter with confirmed style, language, aspect_ratio
  4. If style differs from variant's recommended: regenerate characters/characters.png
  5. User may edit files directly for fine-tuning

Step 4: Generate Images

With confirmed storyboard + style + aspect ratio:

For each page (cover + pages):

  1. Save prompt to prompts/NN-{cover|page}-[slug].md (in user's preferred language)
  2. Generate image using confirmed style and aspect ratio
  3. Report progress after each generation

Image Generation Skill Selection:

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

Character Reference Handling:

  • If skill supports reference image: pass characters/characters.png
  • If skill does NOT support reference image: include characters/characters.md content in prompt

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

  1. Generate unique session ID: comic-{topic-slug}-{timestamp}
  2. Use same session ID for all pages
  3. Ensures visual consistency across generated images

Step 5: Merge to PDF

After all images generated:

bash
npx -y bun ${SKILL_DIR}/scripts/merge-to-pdf.ts <comic-dir>

Creates {topic-slug}.pdf with all pages as full-page images.

Step 6: Completion Report

Comic Complete!
Title: [title] | Style: [style] | Pages: [count] | Aspect: [ratio] | Language: [lang]
Location: [path]
✓ analysis.md
✓ characters.png
✓ 00-cover-[slug].png ... NN-page-[slug].png
✓ {topic-slug}.pdf

Page Modification

Support for modifying individual pages after initial generation.

Edit Single Page

Regenerate a specific page with modified prompt:

  1. Identify page to edit (e.g., 03-page-enigma-machine.png)
  2. Update prompt in prompts/03-page-enigma-machine.md if needed
  3. If content changes significantly, update slug in filename
  4. Regenerate image using same session ID and aspect ratio
  5. Regenerate PDF

Add New Page

Insert a new page at specified position:

  1. Specify insertion position (e.g., after page 3)
  2. Create new prompt with appropriate slug (e.g., 04-page-bletchley-park.md)
  3. Generate new page image (same aspect ratio)
  4. Renumber files: All subsequent pages increment NN by 1
    • 04-page-tragedy.png05-page-tragedy.png
    • Slugs remain unchanged
  5. Update storyboard.md with new page entry
  6. Regenerate PDF

Delete Page

Remove a page and renumber:

  1. Identify page to delete (e.g., 03-page-enigma-machine.png)
  2. Remove image file and prompt file
  3. Renumber files: All subsequent pages decrement NN by 1
    • 04-page-tragedy.png03-page-tragedy.png
    • Slugs remain unchanged
  4. Update storyboard.md to remove page entry
  5. Regenerate PDF

File Naming Convention

Files use meaningful slugs for better readability:

NN-cover-[slug].png / NN-page-[slug].png
NN-cover-[slug].md / NN-page-[slug].md (in prompts/)

Examples:

  • 00-cover-turing-story.png
  • 01-page-early-life.png
  • 02-page-cambridge-years.png
  • 03-page-enigma-machine.png

Slug rules:

  • Derived from page title/content (kebab-case)
  • Must be unique within the comic
  • When page content changes significantly, update slug accordingly

Renumbering:

  • After add/delete, update NN prefix for affected pages
  • Slug remains unchanged unless content changes
  • Maintain sequential numbering with no gaps

Style-Specific Guidelines

Ohmsha Style (--style ohmsha)

Additional requirements for educational manga:

  • Default: Use Doraemon characters directly - No need to create new characters
    • 大雄 (Nobita): Student role, curious learner
    • 哆啦A梦 (Doraemon): Mentor role, explains concepts with gadgets
    • 胖虎 (Gian): Antagonist/challenge role, represents obstacles or misconceptions
    • 静香 (Shizuka): Supporting role, asks clarifying questions
  • Custom characters only if explicitly requested: --characters "Student:小明,Mentor:教授"
  • Must use visual metaphors (gadgets, action scenes) - NO talking heads
  • Page titles: narrative style, not "Page X: Topic"

Reference: references/ohmsha-guide.md for detailed guidelines.

References

Detailed templates and guidelines in references/ directory:

  • analysis-framework.md - Deep content analysis for comic adaptation
  • character-template.md - Character definition format and examples
  • storyboard-template.md - Storyboard structure and panel breakdown
  • ohmsha-guide.md - Ohmsha manga style specifics
  • styles/ - Detailed style definitions
  • layouts/ - Detailed layout definitions

Extension Support

Custom styles and configurations via EXTEND.md.

Check paths (priority order):

  1. .baoyu-skills/baoyu-comic/EXTEND.md (project)
  2. ~/.baoyu-skills/baoyu-comic/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 Comic AI skill do?

Knowledge comic creator supporting multiple styles (Logicomix/Ligne Claire, Ohmsha manga guide). Creates original educational comics with detailed panel layouts and sequential image generation. Use when user asks to create "知识漫画", "教育漫画", "biography comic", "tutorial comic", or "Logicomix-style comic".

Why use Baoyu Comic on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/smallnest/langgraphgo/tree/master/examples/comic_skill_example/skills/baoyu-comic. 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 Comic?

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 Comic?

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

Is the Baoyu Comic AI skill free?

Yes. It is published on GitHub by smallnest 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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