Claude Code Plugins

Community-maintained marketplace

Feedback

Gemini image coder - Generate and edit images using Google's Gemini API. Supports text-to-image, image editing, multi-turn refinement, and composition from multiple reference images. Use when user asks to generate images, create images, edit images, or mentions "gemini image coder".

Install Skill

1Download skill
2Enable skills in Claude

Open claude.ai/settings/capabilities and find the "Skills" section

3Upload to Claude

Click "Upload skill" and select the downloaded ZIP file

Note: Please verify skill by going through its instructions before using it.

SKILL.md

name gemini-image-coder
description Gemini image coder - Generate and edit images using Google's Gemini API. Supports text-to-image, image editing, multi-turn refinement, and composition from multiple reference images. Use when user asks to generate images, create images, edit images, or mentions "gemini image coder".
allowed-tools Read, Write, Bash, WebSearch

Gemini Image Generation

Generate and edit images using Google's Gemini API. Requires GEMINI_API_KEY environment variable.

Quick Reference

Setting Default Options
Model gemini-3-pro-image-preview Use this for all generation
Resolution 1K 1K, 2K, 4K
Aspect Ratio 1:1 1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9

CLI Scripts

Generate Image

python scripts/generate_image.py "A cat in space" output.jpg
python scripts/generate_image.py "Epic landscape" landscape.jpg --aspect 16:9 --size 2K
python scripts/generate_image.py "Logo for Acme Corp" logo.jpg --aspect 1:1

Edit Image

python scripts/edit_image.py input.jpg "Add a rainbow" output.jpg
python scripts/edit_image.py photo.jpg "Make it look like Van Gogh" artistic.jpg

Core API Pattern

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

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

response = client.models.generate_content(
    model="gemini-3-pro-image-preview",
    contents=["Your prompt here"],
    config=types.GenerateContentConfig(
        response_modalities=['TEXT', 'IMAGE'],
    ),
)

for part in response.parts:
    if part.text:
        print(part.text)
    elif part.inline_data:
        image = part.as_image()
        image.save("output.jpg")  # Always use .jpg!

Custom Resolution & Aspect Ratio

response = client.models.generate_content(
    model="gemini-3-pro-image-preview",
    contents=[prompt],
    config=types.GenerateContentConfig(
        response_modalities=['TEXT', 'IMAGE'],
        image_config=types.ImageConfig(
            aspect_ratio="16:9",
            image_size="2K"
        ),
    )
)

Editing Images

from PIL import Image

img = Image.open("input.jpg")
response = client.models.generate_content(
    model="gemini-3-pro-image-preview",
    contents=["Add a sunset to this scene", img],
    config=types.GenerateContentConfig(
        response_modalities=['TEXT', 'IMAGE'],
    ),
)

Multi-Turn Refinement

chat = client.chats.create(
    model="gemini-3-pro-image-preview",
    config=types.GenerateContentConfig(response_modalities=['TEXT', 'IMAGE'])
)

response = chat.send_message("Create a logo for 'Acme Corp'")
# Save first image...

response = chat.send_message("Make the text bolder and add a blue gradient")
# Save refined image...

Prompting Best Practices

Style Prompt Pattern
Photorealistic Include camera: lens, lighting, angle, mood
Stylized Art Specify style explicitly: "kawaii-style", "cel-shading"
Text in Images Be explicit: font style, placement, colors
Product Mockups Describe lighting setup and surface

Examples

# Photorealistic
"A photorealistic close-up portrait, 85mm lens, soft golden hour light, shallow depth of field"

# Stylized
"A kawaii-style sticker of a happy red panda, bold outlines, cel-shading, white background"

# Logo with text
"Create a logo with text 'Daily Grind' in clean sans-serif, black and white, coffee bean motif"

# Product mockup
"Studio-lit product photo on polished concrete, three-point softbox setup, 45-degree angle"

Advanced Features

Google Search Grounding

response = client.models.generate_content(
    model="gemini-3-pro-image-preview",
    contents=["Visualize today's weather in Tokyo as an infographic"],
    config=types.GenerateContentConfig(
        response_modalities=['TEXT', 'IMAGE'],
        tools=[{"google_search": {}}]
    )
)

Multiple Reference Images (Up to 14)

response = client.models.generate_content(
    model="gemini-3-pro-image-preview",
    contents=[
        "Create a group photo of these people in an office",
        Image.open("person1.jpg"),
        Image.open("person2.jpg"),
        Image.open("person3.jpg"),
    ],
    config=types.GenerateContentConfig(
        response_modalities=['TEXT', 'IMAGE'],
    ),
)

Critical: File Format

Gemini returns JPEG by default. Always use .jpg extension.

# CORRECT
image.save("output.jpg")

# WRONG - causes "Image does not match media type" errors
image.save("output.png")  # Creates JPEG with PNG extension!

If PNG is Required

from PIL import Image

for part in response.parts:
    if part.inline_data:
        img = part.as_image()
        img.save("output.png", format="PNG")  # Explicit conversion

Verify Format

file image.png
# If output shows "JPEG image data" - rename to .jpg!

Notes

  • All generated images include SynthID watermarks
  • Default to 1K for speed; use 2K/4K when quality is critical
  • For editing, describe changes conversationally—the model understands semantic masking
  • Image-only mode won't work with Google Search grounding