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Skills/Backend & APIs
feiskyer avatar

Gpt Image Skill

feiskyer/claude-code-settings

This wraps OpenAI's image generation API in a Python script with sensible defaults and Chinese language triggers. You get access to gpt-image-2 and the earlier models, with options for different aspect ratios, transparent backgrounds, and multi-image editing where you can feed in up to three reference images. The script handles both generation and editing modes, saves files locally, and supports custom API endpoints if you're running through Azure or a proxy. It's straightforward if you already have an OpenAI key and just want Claude to generate images without switching contexts. The bilingual triggers are a nice touch for international teams.

installs
146
GitHub stars
1.7K
last updated
Apr 25, 2026
View on GitHubSave

Install

$ npx -y skills add feiskyer/claude-code-settings --skill gpt-image-skill --agent claude-code

Installs into .claude/skills of the current project.

Files

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
SKILL.md on GitHub

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Details

Repository
github.com/feiskyer/claude-code-settings
Categories
Backend & APIs, AI & Agent Building
License
MIT
First seen
Jun 11, 2026

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