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Gemini Image Generation Skill

gemini-image-gen

Guide for implementing Google Gemini API image generation - create high-quality images from text prompts using gemini-2.5-flash-image model. Use when generating images, creating visual content, or implementing text-to-image features. Supports text-to-image, image editing, multi-image composition,...

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SKILL.md

Full skill instructions

Gemini Image Generation Skill

Generate high-quality images using Google's Gemini 2.5 Flash Image model with text prompts, image editing, and multi-image composition capabilities.

When to Use This Skill

Use this skill when you need to:

  • Generate images from text descriptions
  • Edit existing images by adding/​removing elements or changing styles
  • Combine multiple source images into new compositions
  • Iteratively refine images through conversational editing
  • Create visual content for documentation, design, or creative projects

Prerequisites

API Key Setup

The skill automatically detects your GEMINI_API_KEY in this order:

  1. Process environment: export GEMINI_API_KEY="your-key"
  2. Skill directory: .claude/​skills/​gemini-image-gen/​.env
  3. Project directory: ./​.env (project root)

Get your API key: Visit Google AI Studio

Create .env file with:

GEMINI_API_KEY=your_api_key_here

Python Setup

Install required package:

pip install google-genai

Quick Start

Basic Text-to-Image Generation

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

# API key detection handled automatically by helper script
client = genai.Client(api_key=os.getenv('GEMINI_API_KEY'))

response = client.models.generate_content(
    model='gemini-2.5-flash-image',
    contents='A serene mountain landscape at sunset with snow-capped peaks',
    config=types.GenerateContentConfig(
        response_modalities=['image'],
        aspect_ratio='16:9'
    )
)

# Save to ./​docs/​assets/
for i, part in enumerate(response.candidates[0].content.parts):
    if part.inline_data:
        with open(f'./​docs/​assets/​generated-{i}.png', 'wb') as f:
            f.write(part.inline_data.data)

Using the Helper Script

For convenience, use the provided helper script that handles API key detection and file saving:

# Generate single image
python .claude/​skills/​gemini-image-gen/​scripts/​generate.py \
  "A futuristic city with flying cars" \
  --aspect-ratio 16:9 \
  --output ./​docs/​assets/​city.png

# Generate with specific modalities
python .claude/​skills/​gemini-image-gen/​scripts/​generate.py \
  "Modern architecture design" \
  --response-modalities image text \
  --aspect-ratio 1:1

Key Features

Aspect Ratios

RatioResolutionUse CaseToken Cost
1:11024×1024Social media, avatars1290
16:91344×768Landscapes, banners1290
9:16768×1344Mobile, portraits1290
4:31152×896Traditional media1290
3:4896×1152Vertical posters1290

Response Modalities

  • ['image']: Generate only images
  • ['text']: Generate only text descriptions
  • ['image', 'text']: Generate both images and descriptions

Image Editing

Provide existing image + text instructions to modify:

import PIL.Image

img = PIL.Image.open('original.png')
response = client.models.generate_content(
    model='gemini-2.5-flash-image',
    contents=[
        'Add a red balloon floating in the sky',
        img
    ]
)

Multi-Image Composition

Combine up to 3 source images (recommended):

img1 = PIL.Image.open('background.png')
img2 = PIL.Image.open('foreground.png')

response = client.models.generate_content(
    model='gemini-2.5-flash-image',
    contents=[
        'Combine these images into a cohesive scene',
        img1,
        img2
    ]
)

Prompt Engineering Tips

Structure effective prompts with three elements:

  1. Subject: What to generate ("a robot")
  2. Context: Environmental setting ("in a futuristic city")
  3. Style: Artistic treatment ("cyberpunk style, neon lighting")

Example: "A robot in a futuristic city, cyberpunk style with neon lighting and rain-slicked streets"

Quality modifiers:

  • Add terms like "4K", "HDR", "high-quality", "professional photography"
  • Specify camera settings: "35mm lens", "shallow depth of field", "golden hour lighting"

Text in images:

  • Limit to 25 characters maximum
  • Use up to 3 distinct phrases
  • Specify font styles: "bold sans-serif title" or "handwritten script"

See references/​prompting-guide.md for comprehensive prompt engineering strategies.

Safety Settings

The model includes adjustable safety filters. Configure per-request:

config = types.GenerateContentConfig(
    response_modalities=['image'],
    safety_settings=[
        types.SafetySetting(
            category=types.HarmCategory.HARM_CATEGORY_HATE_SPEECH,
            threshold=types.HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE
        )
    ]
)

See references/​safety-settings.md for detailed configuration options.

Output Management

All generated images should be saved to ./​docs/​assets/ directory:

# Create directory if needed
mkdir -p ./​docs/​assets

The helper script automatically saves to this location with timestamped filenames.

Model Specifications

Model: gemini-2.5-flash-image

  • Input tokens: Up to 65,536
  • Output tokens: Up to 32,768
  • Supported inputs: Text and images
  • Supported outputs: Text and images
  • Knowledge cutoff: June 2025
  • Features: Image generation, structured outputs, batch API, caching

Limitations

  • Maximum 3 input images recommended for best results
  • Text rendering works best when generated separately first
  • Does not support audio/​video inputs
  • Regional restrictions on child image uploads (EEA, CH, UK)
  • Optimal language support: English, Spanish (Mexico), Japanese, Mandarin, Hindi

Error Handling

Common issues and solutions:

API key not found:

# Check environment variables
echo $GEMINI_API_KEY

# Verify .env file exists
cat .claude/​skills/​gemini-image-gen/​.env
# or
cat .env

Safety filter blocking:

  • Review response.prompt_feedback.block_reason
  • Adjust safety settings if appropriate for your use case
  • Modify prompt to avoid triggering filters

Token limit exceeded:

  • Reduce prompt length
  • Use fewer input images
  • Simplify image editing instructions

Reference Documentation

For detailed information, see:

  • references/​api-reference.md - Complete API specifications
  • references/​prompting-guide.md - Advanced prompt engineering
  • references/​safety-settings.md - Safety configuration details
  • references/​code-examples.md - Additional implementation examples

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