Nano Banana Image Generator

Nano Banana Image Generator

Generate professional, non-generic images using Nano Banana Pro (Gemini API).

Workflow Overview

1. Brainstorm Concepts - Generate 4-6 high-level visual ideas
2. Select Direction - User picks the concept they like
3. Source Reference Photos - Find high-res images of real people/places (if applicable)
4. Optimize Prompt - Refine into a strong, detailed prompt
5. Style Variations - Adapt to 2-3 different visual styles
6. Generate Images - Run via Gemini API

Step 1: Brainstorm Concepts

When to Ask Clarifying Questions

Before brainstorming, assess if you have enough information. Ask 2-4 focused questions if:

• Subject is unclear or too generic
• Purpose/Context is missing (what's this for?)
• Style preferences are unspecified
• Text requirements are ambiguous

Skip questions if: The user provides a detailed brief or says "just generate it." Don't create friction when the request is already clear.

Example: > User: "Can you write me a prompt for a hero image for my landing page?" > > You: "A few quick questions: > 1. What's the product/service? > 2. Any specific mood - modern/minimal, bold/energetic, warm/approachable? > 3. Should there be text in the image itself?"

Generating Concepts

When the user provides a topic or use case, generate 4-6 high-level visual concepts. Each concept should be:

• One sentence describing the visual idea
• Concrete and immediate - you can picture it instantly
• Conceptual but not abstract - a clear object/scene with meaning
• Non-generic - avoid cliches (no lightbulbs for ideas, no books for education)

Format:

1. **[Short label]** - One sentence description of the visual concept and why it works.

2. **[Short label]** - One sentence description...

Example for "newsletter about self-directed learning":

1. **Compass with crayon needle** - A compass where the needle is a crayon, suggesting direction comes from the learner's own hand.

2. **Path that branches into many paths** - A single dirt path splitting into dozens of colorful trails, each heading somewhere different.

3. **Empty frame on an easel** - A blank canvas on an easel in a field, suggesting the learner creates their own picture.

4. **Backpack with roots** - A school backpack sitting on grass, but roots are growing out the bottom into the soil - learning that plants itself.

Wait for user to select before proceeding.

Step 2: Source Reference Photos (Person-Based Images)

When generating images that depict a real person (tribute posters, portraits, editorial illustrations featuring someone's likeness), you must source a high-resolution reference photo before generating.

Why This Matters

• Input photo resolution directly determines output quality. A 283px input produces a blurry, unusable output. A 1920px+ input produces sharp, detailed results.
• The model needs a clear, well-lit photo to capture likeness accurately.
• Photo era matters: a 1913 photo of someone will produce a young-looking result even if the prompt says "elderly."

Process

1. Search for the person using WebSearch or WebFetch. Look for:

• Official organization pages (foundations, universities, publishers)
• Wikipedia/Wikimedia Commons (check actual resolution - thumbnails are too small)
• Library of Congress, public domain archives
• Professional photography sites, press kits

1. Verify resolution before downloading. Target minimum 1000px on the longest edge, ideally 1920px+. Check the actual image dimensions, not the page thumbnail.

1. Verify the era/age. If the content discusses someone in their later years, don't use a photo from their twenties. Match the photo to the narrative.

1. Download and save to the same output directory as the final images, with a descriptive name:

• {name}-reference-hires.jpg - Primary reference photo
• {name}-reference-{year}.jpg - If era-specific (e.g., montessori-reference-1946.jpg)

1. Use with --input flag when generating:

``bash python generate_image.py "prompt describing the style..." \ --input path/to/reference-hires.jpg \ --model pro --aspect 16:9 ``

Resolution Quick Reference

| Input Resolution | Output Quality | |-----------------|---------------| | < 500px | Unusable - blurry, distorted | | 500-999px | Marginal - may work for stylized illustrations | | 1000-1920px | Good - suitable for most uses | | 1920px+ | Excellent - sharp detail, accurate likeness |

Troubleshooting Likeness

• Doesn't look like them? Try a different reference photo with clearer facial features and better lighting.
• Wrong age? Find a photo from the correct era.
• Wikimedia rate-limiting (429)? Use alternative sources (LOC, official sites, press kits).

Step 3: Optimize the Prompt

Once the user selects a concept, develop it into a full prompt. Structure:

Create a [style type] illustration of [subject].

CONCEPT: [Expand the one-sentence idea into a clear visual description]

STYLE: [Artistic approach - load from references/styles/ if brand-specific]

COMPOSITION: [Framing, focal point, negative space, balance]

COLORS: [Palette - describe by name, not hex codes which may render as text]

TEXTURE: [Surface qualities, analog/digital feel]

AVOID: [What should NOT appear - be specific]

FORMAT: [Aspect ratio]

Key principles:

• Natural language, full sentences - no tag soup
• Describe colors by name (burnt orange, sky blue, near-black) not hex codes
• Maximum 2-3 elements - if it feels busy, remove something
• Favor metaphor over literal depiction

Step 3: Style Variations

Adapt the optimized prompt to 2-3 different styles from references/styles/:

• watercolor-line.md - Ink linework with watercolor washes, warm (DEFAULT for thumbnails)
• opened-editorial.md - Conceptual, brand colors, editorial wit
• minimalist-ink.md - High-contrast black and white, crosshatching
• newyorker-cartoon.md - Single-panel observational humor, crosshatching, italic serif caption (for editorial commentary)

Default behavior: For blog thumbnails and article headers, use watercolor-line style unless otherwise specified. This style provides warmth and approachability while maintaining editorial quality.

New Yorker style: When user asks for "New Yorker cartoon," "editorial cartoon," or observational humor illustrations, load references/styles/newyorker-cartoon.md for the full style guide including caption formulas, humor principles, and prompt template.

For comic ideation: Use the single-panel-comic skill first to generate concepts and captions using Elijah's formula library, then return here for image generation. The workflow is:

single-panel-comic (ideation + caption) → nano-banana-image-generator (visual)

Present all variations to user so they can choose which to generate, or generate all.

Step 4: Generate via API

Setup

The Gemini API key is stored in the vault root .env file. The script looks for GEMINI_API_KEY or GOOGLE_API_KEY.

Requirements: pip install google-genai pillow

Running the Script

The script lives at .claude/skills/nano-banana-image-generator/scripts/generate_image.py.

# From the OpenEd Vault root directory:
cd "/Users/charliedeist/Library/Mobile Documents/com~apple~CloudDocs/Root Docs/OpenEd Vault"

# Set the API key and run
export GEMINI_API_KEY=$(grep GEMINI_API_KEY .env | cut -d'=' -f2) && \
python ".claude/skills/nano-banana-image-generator/scripts/generate_image.py" \
  "Your prompt here" \
  --model pro \
  --aspect 16:9 \
  --output "Studio/Content Engine Deck" \
  --name "my-image"

Options:

• --model pro (higher quality, supports aspect ratio) or --model flash (faster, cheaper)
• --aspect 16:9, 1:1, 9:16, 3:4, 4:3 (only works with pro model)
• --variations N - generate N versions
• --output ./path - save location (default: current directory)
• --name prefix - filename prefix (legacy, prefer --seo-name)
• --input path/to/image.png - use a reference image for rework/edit mode
• --seo-name slug - SEO-friendly filename (e.g. john-taylor-gatto-education-reformer). Output: {slug}-gen.jpg
• --context "Article title or topic" - generates alt text suggestion in the metadata sidecar

Format detection: The script detects the actual image format (JPEG vs PNG) from Gemini's response bytes and saves with the correct extension. No more .png files containing JPEG data.

Metadata sidecar: Every generated image gets a .meta.json file alongside it containing:

• alt_text - Auto-generated from prompt + context
• keywords - Extracted from context
• original_format - Detected format (jpeg/png)
• dimensions - Width and height in pixels
• aspect_ratio - The requested ratio
• prompt_summary - First 200 chars of the prompt
• suggested_seo_name - The seo-name if provided

Note: For flash model, aspect ratio config is ignored - include the ratio in your prompt text instead.

SEO Workflow (Recommended for Blog Content)

For any blog article or SEO content, use the full SEO workflow:

# 1. Generate with SEO name and context
export GEMINI_API_KEY=$(grep GEMINI_API_KEY .env | cut -d'=' -f2) && \
python3 ".claude/skills/nano-banana-image-generator/scripts/generate_image.py" \
  "A watercolor illustration of a child building a treehouse" \
  --model pro --aspect 16:9 \
  --seo-name "project-based-learning-treehouse" \
  --context "How Project-Based Learning Transforms Homeschool Education" \
  --output "Studio/SEO Content Production/project-based-learning/"

# 2. Convert to WebP for web delivery
python3 ".claude/skills/nano-banana-image-generator/scripts/image_optimizer.py" \
  "Studio/SEO Content Production/project-based-learning/project-based-learning-treehouse-gen.jpg" \
  --use thumbnail

# Result: project-based-learning-treehouse-gen-thumbnail.webp (1200x675)
# Plus updated .meta.json with WebP path and dimensions

Image Optimizer

The image_optimizer.py script converts images to WebP with target dimension presets. It keeps the original file intact (edit/rework needs the lossless source).

python3 ".claude/skills/nano-banana-image-generator/scripts/image_optimizer.py" \
  path/to/image.jpg --use thumbnail

Presets:

| Preset | Dimensions | Use Case | |--------|-----------|----------| | thumbnail | 1200x675 | Webflow blog thumbnails (16:9) | | social-square | 1080x1080 | Instagram, LinkedIn square | | social-portrait | 1080x1350 | Instagram portrait (4:5) | | inline | max-width 800px | In-article images |

Options:

• --quality N - WebP quality 1-100 (default: 85)
• --output ./path - output directory (default: same as input)

The optimizer updates the .meta.json sidecar with webp_path, webp_dimensions, and webp_preset.

Editing Existing Images

To modify an existing image, use the --input flag with a path to the source image:

export GEMINI_API_KEY=$(grep GEMINI_API_KEY .env | cut -d'=' -f2) && \
python ".claude/skills/nano-banana-image-generator/scripts/generate_image.py" \
  "Add a striped shirt to the child. Remove the signature from the bottom right corner." \
  --input "Studio/Social Media/original-image.png" \
  --model pro \
  --aspect 1:1 \
  --output "Studio/Social Media" \
  --name "edited-image"

Editing capabilities:

• Add, remove, or modify visual elements
• Change clothing, backgrounds, or objects
• Remove unwanted text, signatures, or watermarks
• Adjust colors or style elements
• Keep specific elements while changing others

Best practices for edit prompts:

• Be explicit about what to change AND what to keep
• List changes as numbered items for clarity
• Say "Keep everything else exactly the same" to preserve other elements
• Use "Remove X" for deletions, "Change X to Y" for modifications

Output location: ALWAYS save images in the same folder as the content they belong to - not a generic images dump. This is critical for organization.

Routing by content type:

| Content Type | Output Location | |--------------|-----------------| | Newsletter | Studio/OpenEd Daily Studio/[date-folder]/ | | Podcast episode | Studio/Podcast Studio/[episode-folder]/ | | Blog article | Studio/SEO Content Production/[article-folder]/ | | Guest contributor | Studio/SEO Content Production/Guest Contributors/[name]/ | | Social media | Studio/Social Media Transformation/[campaign]/ | | Hub page | Content/Open Education Hub/[topic]/ |

Before generating: Identify the content context and determine the correct output path. If a project folder exists, route there. If not, create the folder first.

Naming convention: Use descriptive prefixes that indicate purpose:

• thumbnail-draft.png - Working thumbnail
• thumbnail-final.png - Approved thumbnail
• header-[concept].png - Article header
• social-[platform].png - Platform-specific social image

Step 6: Iterate

After user reviews generated images:

• 80% good? Use --input flag to make targeted changes to the existing image
• Composition off? Adjust framing or element placement in prompt
• Wrong style? Try a different style reference
• Too busy? Simplify to fewer elements
• Colors wrong? Be more explicit about palette

When to regenerate vs. edit:

• Edit when the image is mostly right but needs specific fixes (remove element, change clothing, fix text)
• Regenerate when the composition, style, or concept needs a complete rethink

Prompting Principles

Write Like a Creative Director

Brief the model like a human artist. Use proper grammar, full sentences, and descriptive adjectives.

| Don't | Do | |-------|-----| | "Cool car, neon, city, night, 8k" | "A cinematic wide shot of a futuristic sports car speeding through a rainy Tokyo street at night. The neon signs reflect off the wet pavement and the car's metallic chassis." |

Be specific about:

• Subject: Instead of "a woman," say "a sophisticated elderly woman wearing a vintage chanel-style suit"
• Materiality: Describe textures - "matte finish," "brushed steel," "soft velvet," "crumpled paper"
• Setting: Define location, time of day, weather
• Lighting: Specify mood and light source
• Mood: Emotional tone of the image

Provide Context

Context helps the model make logical artistic decisions. Include the "why" or "for whom."

Example: "Create an image of a sandwich for a Brazilian high-end gourmet cookbook." (Model infers: professional plating, shallow depth of field, perfect lighting)

Keep It Simple

• One clear focal point
• Maximum 2-3 elements total
• Generous negative space
• If it feels busy, remove something

Avoid the Generic

• No lightbulbs for "ideas"
• No stacks of books for "education"
• No happy children raising hands
• No glossy AI aesthetic

Resources

references/styles/

Brand and aesthetic style definitions:

• opened-editorial.md - OpenEd brand style
• minimalist-ink.md - Black and white ink illustration
• watercolor-line.md - Ink with watercolor washes
• newyorker-cartoon.md - New Yorker single-panel cartoon (crosshatching, understated humor, italic serif caption)

references/concepts/

Saved prompts for reusable images:

• paper-airplane-newsletter.md - Newsletter header variations
• ed-horse-error.md - Ed mascot for error states
• dual-exposure-tribute.md - Photo-grid composite tribute posters (Instagram 1:1 + thumbnail 16:9)

scripts/ (in this skill folder)

• generate_image.py - Gemini API image generation (Nano Banana / Nano Banana Pro)

Prompt Modifiers Reference

| Category | Examples | |----------|----------| | Lighting | golden hour, dramatic shadows, soft diffused light, neon glow, overcast | | Style | cinematic, editorial, technical diagram, hand-drawn, photorealistic | | **T

…

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: cdeistopened
• Source: cdeistopened/content-os
• License: MIT

Install and usage instructions live in the source repository linked above.