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    smallnest

    baoyu-comic

    smallnest/baoyu-comic
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    About

    SKILL.md

    Install

    Install via Skills CLI

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    ├─
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    About

    Knowledge comic creator supporting multiple styles (Logicomix/Ligne Claire, Ohmsha manga guide). Creates original educational comics with detailed panel layouts and sequential image generation...

    SKILL.md

    Knowledge Comic Creator

    Create original knowledge comics with multiple visual styles.

    Usage

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

    Options

    Option Values
    --style classic (default), dramatic, warm, sepia, vibrant, ohmsha, realistic, wuxia, shoujo, or custom description
    --layout standard (default), cinematic, dense, splash, mixed, webtoon
    --aspect 3:4 (default, portrait), 4:3 (landscape), 16:9 (widescreen)
    --lang auto (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 Signals Style Layout
    Tutorial, how-to, beginner ohmsha webtoon
    Computing, AI, programming ohmsha dense
    Pre-1950, classical, ancient sepia cinematic
    Personal story, mentor warm standard
    Conflict, breakthrough dramatic splash
    Wine, food, business, lifestyle, professional realistic cinematic
    Martial arts, wuxia, xianxia, Chinese historical wuxia splash
    Romance, love, school life, friendship, emotional shoujo standard
    Biography, balanced classic mixed

    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:

    Script Purpose
    scripts/merge-to-pdf.ts Merge 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:

    ---
    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.

    Variant Narrative Approach Recommended Style Layout
    A Chronological sepia cinematic
    B Thematic ohmsha dense
    C Character-focused warm standard

    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:

    Question When to Ask
    Storyboard variant Always (required)
    Visual style Always (required)
    Language Only if source_language ≠ user_language
    Aspect ratio Only 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:

    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.png → 05-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.png → 03-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.

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    Files