Nano Banana Skill

Python scripting with Gemini image generation using uv. Write small, focused scripts using heredocs for quick tasks—no files needed for one-off operations.

Choosing Your Approach

Quick image generation: Use heredoc with inline Python for one-off image requests.

Complex workflows: When multiple steps are needed (generate -> refine -> save), break into separate scripts and iterate.

Scripting tasks: For non-image Python tasks, use the same heredoc pattern with uv run .

Writing Scripts

Execute Python inline using heredocs with inline script metadata for dependencies:

uv run - << 'EOF'

/// script

dependencies = ["google-genai", "pillow"]

///

from google import genai from google.genai import types

client = genai.Client()

response = client.models.generate_content( model="gemini-3-pro-image-preview", contents=["A cute banana character with sunglasses"], config=types.GenerateContentConfig( response_modalities=['IMAGE'] ) )

for part in response.parts: if part.inline_data is not None: image = part.as_image() image.save("tmp/generated.png") print("Image saved to tmp/generated.png") EOF

The # /// script block declares dependencies inline using TOML syntax. This makes scripts self-contained and reproducible.

Why these dependencies:

• google-genai

• Gemini API client

• pillow

• Required for .as_image() method (converts base64 to PIL Image) and saving images

Only write to files when:

• The script needs to be reused multiple times

• The script is complex and requires iteration

• The user explicitly asks for a saved script

Basic Template

uv run - << 'EOF'

/// script

dependencies = ["google-genai", "pillow"]

///

from google import genai from google.genai import types

client = genai.Client()

Generate image

response = client.models.generate_content( model="gemini-3-pro-image-preview", contents=["YOUR PROMPT HERE"], config=types.GenerateContentConfig( response_modalities=['IMAGE'] ) )

Save result

for part in response.parts: if part.text is not None: print(part.text) elif part.inline_data is not None: image = part.as_image() image.save("tmp/output.png") print("Saved: tmp/output.png") EOF

Key Principles

• Small scripts: Each script should do ONE thing (generate, refine, save)

• Evaluate output: Always save images and print status to decide next steps

• Use tmp/: Save generated images to tmp/ directory by default

• Stateless execution: Each script runs independently, no cleanup needed

Workflow Loop

Follow this pattern for complex tasks:

• Write a script to generate/process one image

• Run it and observe the output

• Evaluate - did it work? Check the saved image

• Decide - refine prompt or task complete?

• Repeat until satisfied

Image Configuration

Configure aspect ratio and resolution:

config=types.GenerateContentConfig( response_modalities=['IMAGE'], image_config=types.ImageConfig( aspect_ratio="16:9", # "1:1", "16:9", "9:16", "4:3", "3:4" image_size="2K" # "1K", "2K", "4K" (uppercase required) ) )

Models

• gemini-3-pro-image-preview

• Fast, general purpose image generation

• gemini-3-pro-image-preview

• Advanced, professional asset production (Nano Banana Pro)

Default to gemini-3-pro-image-preview (Nano Banana Pro) for all image generation unless:

• The user explicitly requests a different model

• The user wants to save budget/costs

• The user specifies a simpler or quick generation task

Nano Banana Pro provides higher quality results and should be the recommended choice.

Text + Image Output

To receive both text explanation and image:

config=types.GenerateContentConfig( response_modalities=['TEXT', 'IMAGE'] )

Image Editing

Edit existing images by including them in the request:

uv run - << 'EOF'

/// script

dependencies = ["google-genai", "pillow"]

///

from google import genai from google.genai import types from PIL import Image

client = genai.Client()

Load existing image

img = Image.open("input.png")

response = client.models.generate_content( model="gemini-3-pro-image-preview", contents=[ "Add a party hat to this character", img ], config=types.GenerateContentConfig( response_modalities=['IMAGE'] ) )

for part in response.parts: if part.inline_data is not None: part.as_image().save("tmp/edited.png") print("Saved: tmp/edited.png") EOF

Debugging Tips

• Print response.parts to see what was returned

• Check for text parts - model may include explanations

• Save images immediately to verify output visually

• Use Read tool to view saved images after generation

Error Recovery

If a script fails:

• Check error message for API issues

• Verify GOOGLE_API_KEY is set

• Try simpler prompt to isolate the issue

• Check image format compatibility for edits

Advanced Scenarios

For complex workflows including thinking process, Google Search grounding, multi-turn conversations, and professional asset production, load references/guide.md .