/gpt-image-skill

name: gpt-image-skill
description: 'Generate or edit images using OpenAI GPT Image API (gpt-image-2, gpt-image-1, etc). Use ONLY when the user explicitly names OpenAI or GPT as the provider: "gpt image", "openai image", "generate image with openai", "用 openai 画图", "用 GPT 生成图片". For generic image requests without a provider, use nanobanana-skill instead. Do NOT use for diagrams (架构图/流程图) — draw those with Mermaid or code.'
allowed-tools: Read, Write, Glob, Grep, Task, Bash(cat:*), Bash(ls:*), Bash(tree:*), Bash(python3:*)

GPT Image Skill

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

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, Pillow. Install via `python3 -m pip install -r ${CLAUDE_SKILL_DIR}/requirements.txt` if not installed yet. 4. **Executable**: `${CLAUDE_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 ${CLAUDE_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 (up to 3)
• What changes they want (the prompt)
• Output filename (optional)

2. Run with input images:

   python3 ${CLAUDE_SKILL_DIR}/gpt_image.py edit --prompt "editing instructions" --input image1.png image2.png --output "edited.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 ${CLAUDE_SKILL_DIR}/gpt_image.py --prompt "A serene mountain landscape at sunset with a lake"

Generate with specific size and output

python3 ${CLAUDE_SKILL_DIR}/gpt_image.py \
  --prompt "Modern minimalist logo for a tech startup" \
  --size 1024x1024 \
  --quality high \
  --output "logo.png"

Generate landscape image

python3 ${CLAUDE_SKILL_DIR}/gpt_image.py \
  --prompt "Futuristic cityscape with flying cars" \
  --size 1536x1024 \
  --output "cityscape.png"

Generate with transparent background

python3 ${CLAUDE_SKILL_DIR}/gpt_image.py \
  --prompt "A cute cartoon cat mascot" \
  --background transparent \
  --format png \
  --output "mascot.png"

Generate multiple images

python3 ${CLAUDE_SKILL_DIR}/gpt_image.py \
  --prompt "Abstract art in the style of Kandinsky" \
  --n 3 \
  --output "art.png"

Edit existing images

python3 ${CLAUDE_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 ${CLAUDE_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 ${CLAUDE_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