Gpt Image Skill

GPT Image Skill

Generate or edit images using OpenAI's GPT Image models through a bundled Python script.

Resolve the skill directory

Before running any command, resolve the absolute directory containing this SKILL.md and refer to it as <skill-dir>. Never assume the current working directory is the Skill directory. Keep user input and output paths relative to the user's working directory unless the user requests another location.

Requirements

1. OPENAI_API_KEY: Must be configured in ~/.gpt-image.env or export OPENAI_API_KEY=<your-key>
2. OPENAI_API_BASE (optional): Custom API base URL for compatible endpoints (e.g. Azure OpenAI, proxies). Set in ~/.gpt-image.env or export it.
3. Python3 with dependencies: openai, httpx, python-dotenv. Install via python3 -m pip install -r "<skill-dir>/requirements.txt" if not installed yet.
4. Executable: <skill-dir>/gpt_image.py

Instructions

For image generation

1. Ask the user for:

   • What they want to create (the prompt)
   • Desired size (optional, defaults to 1024x1024)
   • Output filename (optional, auto-generates UUID-based name if not specified)
   • Model preference (optional, defaults to gpt-image-2)
   • Quality (optional, defaults to auto)
   • Number of images (optional, defaults to 1)

2. Run the script:

   python3 "<skill-dir>/gpt_image.py" --prompt "description of image" --output "filename.png"
   

3. Show the user the saved image path when complete.

For image editing

1. Ask the user for:

   • Input image file(s) to edit
   • What changes they want (the prompt)
   • Output filename (optional)

2. Run with input images:

   python3 "<skill-dir>/gpt_image.py" edit --prompt "editing instructions" --input image1.png image2.png --output "edited.png"
   

   Parent directories in the output path are created automatically. When --format is omitted, the script infers it from .png, .jpg/.jpeg, or .webp; otherwise it defaults to PNG.

Available Options

Models (--model)

• gpt-image-2 (default) — Latest model with strong instruction following, text rendering, and broad world knowledge
• gpt-image-1.5 — Mid-tier model
• gpt-image-1 — First-generation GPT image model
• gpt-image-1-mini — Lightweight, faster generation

Sizes (--size)

• 1024x1024 (default) — Square
• 1024x1536 — Portrait (2:3)
• 1536x1024 — Landscape (3:2)
• auto — Let the model decide

Quality (--quality)

• auto (default) — Model decides optimal quality
• high — Higher detail, slower
• medium — Balanced
• low — Fastest

Output Format (--format)

• png (default) — Lossless
• jpeg — Smaller file size
• webp — Modern format, good compression

Background (--background)

• auto (default) — Model decides
• transparent — Transparent background (png/webp only)
• opaque — Solid background

Other Options

• --n <count> — Number of images to generate (default: 1)
• --output <filename> — Output filename (default: auto-generated)

Examples

Generate a simple image

python3 "<skill-dir>/gpt_image.py" --prompt "A serene mountain landscape at sunset with a lake"

Generate with specific size and output

python3 "<skill-dir>/gpt_image.py" \
  --prompt "Modern minimalist logo for a tech startup" \
  --size 1024x1024 \
  --quality high \
  --output "logo.png"

Generate landscape image

python3 "<skill-dir>/gpt_image.py" \
  --prompt "Futuristic cityscape with flying cars" \
  --size 1536x1024 \
  --output "cityscape.png"

Generate with transparent background

python3 "<skill-dir>/gpt_image.py" \
  --prompt "A cute cartoon cat mascot" \
  --background transparent \
  --format png \
  --output "mascot.png"

Generate multiple images

python3 "<skill-dir>/gpt_image.py" \
  --prompt "Abstract art in the style of Kandinsky" \
  --n 3 \
  --output "art.png"

Edit existing images

python3 "<skill-dir>/gpt_image.py" edit \
  --prompt "Add a rainbow in the sky" \
  --input photo.png \
  --output "photo-with-rainbow.png"

Combine multiple reference images

python3 "<skill-dir>/gpt_image.py" edit \
  --prompt "Create a gift basket containing all items shown" \
  --input item1.png item2.png item3.png \
  --output "gift-basket.png"

Use a different model

python3 "<skill-dir>/gpt_image.py" \
  --prompt "Detailed portrait of a cat in watercolor style" \
  --model gpt-image-1 \
  --output "cat-portrait.png"

Error Handling

If the script fails:

• Check that OPENAI_API_KEY is exported
• If using a custom endpoint, verify OPENAI_API_BASE is correct
• Verify input image files exist and are readable (for editing)
• Ensure the output directory is writable
• Check that the model name is valid

Best Practices

1. Be descriptive in prompts — include style, mood, colors, composition details
2. For logos/icons, use square size (1024x1024) with transparent background
3. For social media, use portrait (1024x1536) for stories or square for posts
4. For wallpapers/headers, use landscape (1536x1024)
5. Use high quality for final output, auto for quick iterations
6. GPT Image models excel at text rendering — include text in prompts when needed
7. For editing, provide clear instructions about what to change and what to keep