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

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

Instructions

For image generation

• 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)

• Run the script:

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

• Show the user the saved image path when complete.

For image editing

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

• 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

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