Comic

Knowledge Comic Creator

Create original knowledge comics with multiple visual styles.

Usage

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

Options

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

Script Directory

Important: All scripts are located in 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 actual path

Script Reference:

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 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.

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 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:

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 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 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. .content-gen-skills/comic/EXTEND.md (project)
2. ~/.content-gen-skills/comic/EXTEND.md (user)

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

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