arcanea-book-cover

name	arcanea-book-cover
description	Design and generate premium book covers using NB2 (Nano Banana 2 / Gemini 3.1 Flash Image) with deep thinking about book tension, emotion, and genre. Pulls from top book cover design principles (Chip Kidd, Peter Mendelsund, Coralie Bickford-Smith). Auto-activates when user requests book cover, cover art, cover design, or mentions generating a cover for a book project.
triggers	book cover, cover art, cover design, book jacket, cover generation, generate cover, book cover art
model	claude-opus-4-8

Arcanea Book Cover Design Skill

Generate premium book covers by thinking deeply about the book first, then translating that thinking into a precision image prompt. NB2 is default. NB Pro only when user specifies "premium" or "hero".

The 5-Phase Method

Do NOT skip phases. The thinking is the skill. The generation is the reward.

Phase 1: READ THE BOOK (or its architecture)

Before writing any prompt, you must understand:

1. Central tension — What does the protagonist fight against? What internal conflict mirrors the external?
2. Emotional register — Is this grief-heavy? Wonder-heavy? Dread-heavy? A dark comedy? Bittersweet? Name it precisely.
3. Iconic image — What ONE visual moment defines the book? The image a reader would tattoo on themselves.
4. Genre expectations vs subversion — What do readers of this genre expect? What should you give them, and what should you withhold?
5. Color emotional key — What color (singular) carries the book's feeling?

If the book has a book.yaml or outline, read them. If the book has existing chapters, read at least one opening and one pivotal scene.

Phase 2: PULL BEST PRACTICES

Top book cover designers operate on these principles. Keep them active during prompt design:

Chip Kidd's Rules:

• One idea, one image, one emotion
• The cover is a question, not an answer — it should make readers curious, not satisfied
• Text and image are one unit — typography is 50% of the cover
• Don't illustrate the plot. Illustrate the feeling.

Peter Mendelsund's Rules:

• Covers are "visual metaphors, not visual illustrations"
• Abstraction > literalism when the book is literary
• The reader should finish the book and look at the cover and think "of course"
• White space is content

Coralie Bickford-Smith's Rules (Penguin Classics):

• Pattern + symbol > scene (for literary)
• Limited palette (2-4 colors max)
• Typography must be the hero on pattern-based covers
• Consistency within a series, uniqueness between series

Genre-specific heuristics:

Genre	What sells	What kills
Dark fantasy / grimdark	Single figure, cold color + ember accent, imposing silhouette, minimal text	Cluttered action, bright colors, generic fantasy tropes
Literary fantasy	Symbolic object, atmospheric landscape, negative space, serif typography	Characters' faces, action poses, over-illustration
Epic fantasy mashup	Dynamic composition, heroic pose, dramatic sky, bold title	Muddy color, too many elements, small title
Sci-fi	Clean geometry, singular focal point, future-tech subtlety	Cliché ships, robots, generic space
Romance	Character connection, warm palette, emotion over action	Text overload, generic stock
Thriller	High contrast, negative space, one menacing element	Too much happening, bright
Literary fiction	Photograph crop, object as metaphor, serif title	Fantasy tropes, illustration

Universal principles:

• Title first: Typography must be readable at thumbnail size (Amazon grid)
• Composition rule of thirds: Focal point on intersection, not dead center
• Depth layering: Foreground / mid-ground / background — create dimension
• One hero color: Everything else supports it
• Resist clutter: If it's not essential, delete it
• Portrait ratio: 2:3 is the book cover standard (1200x1800, 800x1200, etc.)

Phase 3: COMPOSE THE PROMPT

The prompt has a specific structure. Follow it exactly:

Generate an image: [Genre descriptor] book cover for [TITLE]. Portrait orientation, 2:3 ratio.

SCENE: [One paragraph describing the single iconic image. Concrete. Specific. No abstractions.]

COMPOSITION: [Focal point location, depth layers, what's foreground/mid/background]

LIGHTING: [Source, direction, mood. Cinematic lighting terminology.]

PALETTE: [Hero color + 2-4 supporting colors as hex codes or named precisely]

TYPOGRAPHY: [Title at top/bottom, font style: serif/sans/display, weight: bold/thin]

STYLE REFERENCES: [2-3 specific references. Real designers, movies, or artists.]

MOOD: [One sentence on the emotional register the cover should evoke]

TECHNICAL: 4K resolution, portrait ratio, book cover composition, cinematic depth of field, readable typography.

Phase 4: GENERATE

Model routing:

• DEFAULT: NB2 (gemini-3.1-flash-image-preview) — $0.02, portrait-native, best for covers
• PREMIUM (only when user says "premium", "hero", "final", or "launch"): NB Pro (nano-banana-pro-preview) — $0.04

API call template:

# Load key from MCP config or env
# export GEMINI_API_KEY="your-key-from-aistudio.google.com"

MODEL="gemini-3.1-flash-image-preview"  # NB2 default
# MODEL="nano-banana-pro-preview"        # NB Pro (premium only)

curl -s "https://generativelanguage.googleapis.com/v1beta/models/$MODEL:generateContent?key=$GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"contents":[{"parts":[{"text":"PROMPT_HERE"}]}],"generationConfig":{"responseModalities":["TEXT","IMAGE"]}}' \
  | python3 -c "
import json,base64,sys
data=json.load(sys.stdin)
for p in data.get('candidates',[{}])[0].get('content',{}).get('parts',[]):
    if 'inlineData' in p:
        d=base64.b64decode(p['inlineData']['data'])
        out='apps/web/public/images/books/SLUG-cover.png'
        open(out,'wb').write(d)
        print(f'OK: {len(d)} bytes -> {out}')
    elif 'text' in p:
        print('Text:',p['text'][:200])
"

Save path convention: apps/web/public/images/books/[slug]-cover.png (Add -nb2 or -nbpro suffix if generating multiple for comparison.)

Phase 5: VALIDATE

Before declaring the cover done, check:

• Title is readable — Can you read it at 200px wide (thumbnail size)?
• Genre signal is clear — Would a reader in 1 second know the genre?
• One hero color dominates — Not competing palettes
• Focal point is intentional — Rule of thirds or centered deliberately
• No AI artifacts — Hands, text garbling, extra limbs, muddy areas
• Portrait ratio — Not square, not landscape
• Matches book tension — Would someone who read the book nod in recognition?
• Mood is precise — Not generic "epic" or "dark" — the SPECIFIC mood

If any fail, iterate. One re-generation is fine. Beyond that, revise the prompt.

Quality Tiers

• Draft cover — NB2, one generation, basic validation. Good enough for book-in-progress.
• Production cover — NB2, 2-3 generations, full validation, pick best. Default for published works.
• Premium cover — NB Pro, multiple angles, hero-quality. For launches, featured tier, or when user specifies.

Anti-Patterns (Never Do)

• Generic "fantasy book cover" prompts with no specificity
• Character faces unless specifically required (faces are the hardest AI generation)
• More than one human figure on the cover (crowd scenes fail)
• Trying to illustrate the entire plot in one image
• Using NB Pro by default (costs 2x with marginal benefit for most covers)
• Skipping Phase 1 (reading the book) to save time
• Bright neon palettes on literary books
• Embedded text longer than the title (taglines often fail in generation)

Integration with Arcanea Ecosystem

• Save covers to apps/web/public/images/books/[slug]-cover.png
• Update COVER_MAP in apps/web/app/books/drafts/[slug]/page.tsx
• Update COVER_MAP in apps/web/app/books/drafts/page.tsx
• Log the cover generation in the book's book.yaml under ai_transparency.models_used
• For featured tier books: also register in the book reader's metadata

Output Format

When using this skill, produce:

1. The thinking — A brief (150-250 word) analysis of the book's tension, emotion, iconic image, genre expectations
2. The prompt — The composed prompt with all 7 structural sections
3. The generation — Execute the curl command, save to correct path
4. The validation — Run the checklist, report pass/fail per item
5. The result — Read the generated image and confirm visually

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"A cover is a haiku. One image, one emotion, one question that makes you turn the book over to read the back." — The Arcanea Book Cover Method