/Catalogue/Prompt/feiskyer/feiskyer-claude-code-settings-gpt-image-skill

Origin: github

gpt-image-skill

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.

by feiskyer · updated 1mo ago · imported from GitHub

Installs0+0/7d
Security score82/100
Retention 14d0%
GitHub stars1.7K

Skill logic

Execution graph
User message
Prompt rewrites behaviour
Response

SKILL.md

View on GitHub ↗

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

Discussion

No comments yet — start the thread.

Sign in to join the discussion.

/More from feiskyer/claude-code-settings

feiskyer· 1mo agoCommunity
chrome

MCP servers · Python · v0.1.0

Curated skills, sub-agents, and config templates that supercharge Claude Code — research, image gen, GitHub automation & more.

#agentic-ai#agents#ai

0 1.7K
feiskyer· 1mo agoCommunity
brainstorming

Prompts · Python · v0.1.0

Explore user intent, requirements, and design options through collaborative dialogue before implementation. Use before building new features, components, or systems — whenever the user describes something to build and design decisions are involved. Triggers: "brainstorm", "help me design", "think through the requirements", "头脑风暴", "设计方案", "梳理需求". Not for bug fixes, config changes, or tasks with an obvious implementation path.

#agentic-ai#agents#ai

0 1.7K
feiskyer· 1mo agoSandbox
codex-skill

Prompts · Python · v0.1.0

Leverage OpenAI Codex/GPT models for autonomous code implementation, code review, and plan review. Triggers: "codex", "use gpt", "gpt-5", "let openai", "full-auto", "adversarial review", "second opinion review", "用codex", "让gpt实现", "对抗式审查", "让codex审查计划", "第二意见". Use this skill whenever the user wants to delegate coding tasks to OpenAI models, run code or plan reviews via codex, get a second-opinion review from a different model, or execute tasks in a sandboxed environment.

#agentic-ai#agents#ai

0 1.7K
feiskyer· 1mo agoCommunity
deep-research

Prompts · Python · v0.1.0

Multi-agent research orchestration: split a research goal into parallel sub-goals, run each via headless `claude -p` subprocesses, aggregate results into a polished report file. Use for systematic web/document research, competitive or industry analysis, batch link/dataset processing, and long-form evidence synthesis. Triggers: "深度调研", "deep research", "wide research", "多 Agent 调研", "系统调研".

#agentic-ai#agents#ai

0 1.7K