Skills

Gemini Imagegen

Generate and edit images using Google Gemini's native image generation models (Nano...

Install

npx skills add dp-archive/archive --skill gemini-imagegen -g -a claude-code -y
Repository
dp-archive/archive1.1k
Category
Media
Updated
8mo ago
License
Apache-2.0
Context cost
Lightabout 1,280 tokens
Runs scripts
No, instructions only

What it does

Generate and edit images using Google Gemini's native image generation models (Nano Banana / Nano Banana Pro). Supports text-to-image, image editing with reference images, multi-image composition, and character consistency. Use when the user asks to generate images via Gemini, create AI illustrations, edit photos with Gemini, or needs high-quality image generation with the Google API. Requires GEMINI_API_KEY. Triggers: "generate image with gemini", "nano banana", "gemini image", "create illustration", "AI generate picture", "text to image".

Gemini Image Generation

Generate and edit images via Google Gemini's native multimodal image generation.

Model Selection

Model IDCodenameBest forMax resolution
gemini-2.5-flash-imageNano BananaFast drafts, high-volume, low-latency1K
gemini-3-pro-image-previewNano Banana ProStudio-quality, text rendering, complex prompts4K

Default: gemini-3-pro-image-preview (Pro) unless speed/cost is a concern.

Setup

# Install (once)
# pip install google-genai

from google import genai
import os, base64

client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])

If GEMINI_API_KEY is missing, instruct the user to set it as an environment variable. Never ask the user to paste the key in chat.

Text-to-Image

from google import genai
from google.genai import types
import os

client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])

response = client.models.generate_content(
    model="gemini-3-pro-image-preview",
    contents="A photorealistic cat on a rainbow sofa",
    config=types.GenerateContentConfig(
        response_modalities=["TEXT", "IMAGE"],
    ),
)

# Extract and save
for part in response.candidates[0].content.parts:
    if part.inline_data is not None:
        with open("output.png", "wb") as f:
            f.write(part.inline_data.data)
        break

Aspect Ratio

Set via image_config:

config=types.GenerateContentConfig(
    response_modalities=["TEXT", "IMAGE"],
    image_config=types.ImageConfig(
        aspect_ratio="16:9",  # for slides / widescreen
    ),
)

Supported ratios: 1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9

Common choices:

  • Slides / presentations → 16:9
  • Social media / portraits → 9:16 or 4:5
  • Square thumbnails → 1:1

Image Editing (with reference image)

from google.genai import types
from pathlib import Path
import base64
Read the whole SKILL.md on GitHub

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