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@intellectronica
Last active November 26, 2025 16:11
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Nano Banana Pro SKILL - Create or Edit images.

Nano Banana Pro SKILL

Use this skill to create or edit images using Nano Banana Pro.

Installation

Unzip nano-banana-pro.zip into ~/.claude/skills or ~/.skillz/ or wherever you keep skills locally. Or upload it to the Claude app.

API KEY

The skill can use an API key read from the environment (export GEMINI_API_KEY=...) or from the context (just paste the API key in the chat or add it to your instructions or a file in a project).

Usage

> Generate an image of a monkey on a pedestal juggling with tennis balls
> Generate a high resolution image of a monkey on a pedestal
> Modify @juggling-monkey.png so that the monkey is juggling with banas instead of balls

Happy image-generating!

🫶 Eleanor (@intellectronica)

#!/usr/bin/env python3
# /// script
# requires-python = ">=3.10"
# dependencies = [
# "google-genai>=1.0.0",
# "pillow>=10.0.0",
# ]
# ///
"""
Generate images using Google's Nano Banana Pro (Gemini 3 Pro Image) API.
Usage:
uv run generate_image.py --prompt "your image description" --filename "output.png" [--resolution 1K|2K|4K] [--api-key KEY]
"""
import argparse
import os
import sys
from pathlib import Path
def get_api_key(provided_key: str | None) -> str | None:
"""Get API key from argument first, then environment."""
if provided_key:
return provided_key
return os.environ.get("GEMINI_API_KEY")
def main():
parser = argparse.ArgumentParser(
description="Generate images using Nano Banana Pro (Gemini 3 Pro Image)"
)
parser.add_argument(
"--prompt", "-p",
required=True,
help="Image description/prompt"
)
parser.add_argument(
"--filename", "-f",
required=True,
help="Output filename (e.g., sunset-mountains.png)"
)
parser.add_argument(
"--input-image", "-i",
help="Optional input image path for editing/modification"
)
parser.add_argument(
"--resolution", "-r",
choices=["1K", "2K", "4K"],
default="1K",
help="Output resolution: 1K (default), 2K, or 4K"
)
parser.add_argument(
"--api-key", "-k",
help="Gemini API key (overrides GEMINI_API_KEY env var)"
)
args = parser.parse_args()
# Get API key
api_key = get_api_key(args.api_key)
if not api_key:
print("Error: No API key provided.", file=sys.stderr)
print("Please either:", file=sys.stderr)
print(" 1. Provide --api-key argument", file=sys.stderr)
print(" 2. Set GEMINI_API_KEY environment variable", file=sys.stderr)
sys.exit(1)
# Import here after checking API key to avoid slow import on error
from google import genai
from google.genai import types
from PIL import Image as PILImage
# Initialise client
client = genai.Client(api_key=api_key)
# Set up output path
output_path = Path(args.filename)
output_path.parent.mkdir(parents=True, exist_ok=True)
# Load input image if provided
input_image = None
output_resolution = args.resolution
if args.input_image:
try:
input_image = PILImage.open(args.input_image)
print(f"Loaded input image: {args.input_image}")
# Auto-detect resolution if not explicitly set by user
if args.resolution == "1K": # Default value
# Map input image size to resolution
width, height = input_image.size
max_dim = max(width, height)
if max_dim >= 3000:
output_resolution = "4K"
elif max_dim >= 1500:
output_resolution = "2K"
else:
output_resolution = "1K"
print(f"Auto-detected resolution: {output_resolution} (from input {width}x{height})")
except Exception as e:
print(f"Error loading input image: {e}", file=sys.stderr)
sys.exit(1)
# Build contents (image first if editing, prompt only if generating)
if input_image:
contents = [input_image, args.prompt]
print(f"Editing image with resolution {output_resolution}...")
else:
contents = args.prompt
print(f"Generating image with resolution {output_resolution}...")
try:
response = client.models.generate_content(
model="gemini-3-pro-image-preview",
contents=contents,
config=types.GenerateContentConfig(
response_modalities=["TEXT", "IMAGE"],
image_config=types.ImageConfig(
image_size=output_resolution
)
)
)
# Process response and convert to PNG
image_saved = False
for part in response.parts:
if part.text is not None:
print(f"Model response: {part.text}")
elif part.inline_data is not None:
# Convert inline data to PIL Image and save as PNG
from io import BytesIO
# inline_data.data is already bytes, not base64
image_data = part.inline_data.data
if isinstance(image_data, str):
# If it's a string, it might be base64
import base64
image_data = base64.b64decode(image_data)
image = PILImage.open(BytesIO(image_data))
# Ensure RGB mode for PNG (convert RGBA to RGB with white background if needed)
if image.mode == 'RGBA':
rgb_image = PILImage.new('RGB', image.size, (255, 255, 255))
rgb_image.paste(image, mask=image.split()[3])
rgb_image.save(str(output_path), 'PNG')
elif image.mode == 'RGB':
image.save(str(output_path), 'PNG')
else:
image.convert('RGB').save(str(output_path), 'PNG')
image_saved = True
if image_saved:
full_path = output_path.resolve()
print(f"\nImage saved: {full_path}")
else:
print("Error: No image was generated in the response.", file=sys.stderr)
sys.exit(1)
except Exception as e:
print(f"Error generating image: {e}", file=sys.stderr)
sys.exit(1)
if __name__ == "__main__":
main()
name description
nano-banana-pro
Generate and edit images using Google's Nano Banana Pro (Gemini 3 Pro Image) API. Use when the user asks to generate, create, edit, modify, change, alter, or update images. Also use when user references an existing image file and asks to modify it in any way (e.g., "modify this image", "change the background", "replace X with Y"). Supports both text-to-image generation and image-to-image editing with configurable resolution (1K default, 2K, or 4K for high resolution). DO NOT read the image file first - use this skill directly with the --input-image parameter.

Nano Banana Pro Image Generation & Editing

Generate new images or edit existing ones using Google's Nano Banana Pro API (Gemini 3 Pro Image).

Usage

Run the script using absolute path (do NOT cd to skill directory first):

Generate new image:

uv run ~/.claude/skills/nano-banana-pro/scripts/generate_image.py --prompt "your image description" --filename "output-name.png" [--resolution 1K|2K|4K] [--api-key KEY]

Edit existing image:

uv run ~/.claude/skills/nano-banana-pro/scripts/generate_image.py --prompt "editing instructions" --filename "output-name.png" --input-image "path/to/input.png" [--resolution 1K|2K|4K] [--api-key KEY]

Important: Always run from the user's current working directory so images are saved where the user is working, not in the skill directory.

Resolution Options

The Gemini 3 Pro Image API supports three resolutions (uppercase K required):

  • 1K (default) - ~1024px resolution
  • 2K - ~2048px resolution
  • 4K - ~4096px resolution

Map user requests to API parameters:

  • No mention of resolution → 1K
  • "low resolution", "1080", "1080p", "1K" → 1K
  • "2K", "2048", "normal", "medium resolution" → 2K
  • "high resolution", "high-res", "hi-res", "4K", "ultra" → 4K

API Key

The script checks for API key in this order:

  1. --api-key argument (use if user provided key in chat)
  2. GEMINI_API_KEY environment variable

If neither is available, the script exits with an error message.

Filename Generation

Generate filenames with the pattern: yyyy-mm-dd-hh-mm-ss-name.png

Format: {timestamp}-{descriptive-name}.png

  • Timestamp: Current date/time in format yyyy-mm-dd-hh-mm-ss (24-hour format)
  • Name: Descriptive lowercase text with hyphens
  • Keep the descriptive part concise (1-5 words typically)
  • Use context from user's prompt or conversation
  • If unclear, use random identifier (e.g., x9k2, a7b3)

Examples:

  • Prompt "A serene Japanese garden" → 2025-11-23-14-23-05-japanese-garden.png
  • Prompt "sunset over mountains" → 2025-11-23-15-30-12-sunset-mountains.png
  • Prompt "create an image of a robot" → 2025-11-23-16-45-33-robot.png
  • Unclear context → 2025-11-23-17-12-48-x9k2.png

Image Editing

When the user wants to modify an existing image:

  1. Check if they provide an image path or reference an image in the current directory
  2. Use --input-image parameter with the path to the image
  3. The prompt should contain editing instructions (e.g., "make the sky more dramatic", "remove the person", "change to cartoon style")
  4. Common editing tasks: add/remove elements, change style, adjust colors, blur background, etc.

Prompt Handling

For generation: Pass user's image description as-is to --prompt. Only rework if clearly insufficient.

For editing: Pass editing instructions in --prompt (e.g., "add a rainbow in the sky", "make it look like a watercolor painting")

Preserve user's creative intent in both cases.

Output

  • Saves PNG to current directory (or specified path if filename includes directory)
  • Script outputs the full path to the generated image
  • Do not read the image back - just inform the user of the saved path

Examples

Generate new image:

uv run ~/.claude/skills/nano-banana-pro/scripts/generate_image.py --prompt "A serene Japanese garden with cherry blossoms" --filename "2025-11-23-14-23-05-japanese-garden.png" --resolution 4K

Edit existing image:

uv run ~/.claude/skills/nano-banana-pro/scripts/generate_image.py --prompt "make the sky more dramatic with storm clouds" --filename "2025-11-23-14-25-30-dramatic-sky.png" --input-image "original-photo.jpg" --resolution 2K
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