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
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
Generate or edit images using OpenAI's GPT Image models through a bundled Python script.
~/.gpt-image.env or export OPENAI_API_KEY=<your-key>~/.gpt-image.env or export it.python3 -m pip install -r ${CLAUDE_SKILL_DIR}/requirements.txt if not installed yet.${CLAUDE_SKILL_DIR}/gpt_image.pyAsk the user for:
Run the script:
python3 ${CLAUDE_SKILL_DIR}/gpt_image.py --prompt "description of image" --output "filename.png"
Show the user the saved image path when complete.
Ask the user for:
Run with input images:
python3 ${CLAUDE_SKILL_DIR}/gpt_image.py edit --prompt "editing instructions" --input image1.png image2.png --output "edited.png"
gpt-image-2 (default) — Latest model with strong instruction following, text rendering, and broad world knowledgegpt-image-1.5 — Mid-tier modelgpt-image-1 — First-generation GPT image modelgpt-image-1-mini — Lightweight, faster generation1024x1024 (default) — Square1024x1536 — Portrait (2:3)1536x1024 — Landscape (3:2)auto — Let the model decideauto (default) — Model decides optimal qualityhigh — Higher detail, slowermedium — Balancedlow — Fastestpng (default) — Losslessjpeg — Smaller file sizewebp — Modern format, good compressionauto (default) — Model decidestransparent — Transparent background (png/webp only)opaque — Solid background--n <count> — Number of images to generate (default: 1)--output <filename> — Output filename (default: auto-generated)python3 ${CLAUDE_SKILL_DIR}/gpt_image.py --prompt "A serene mountain landscape at sunset with a lake"
python3 ${CLAUDE_SKILL_DIR}/gpt_image.py \
--prompt "Modern minimalist logo for a tech startup" \
--size 1024x1024 \
--quality high \
--output "logo.png"
python3 ${CLAUDE_SKILL_DIR}/gpt_image.py \
--prompt "Futuristic cityscape with flying cars" \
--size 1536x1024 \
--output "cityscape.png"
python3 ${CLAUDE_SKILL_DIR}/gpt_image.py \
--prompt "A cute cartoon cat mascot" \
--background transparent \
--format png \
--output "mascot.png"
python3 ${CLAUDE_SKILL_DIR}/gpt_image.py \
--prompt "Abstract art in the style of Kandinsky" \
--n 3 \
--output "art.png"
python3 ${CLAUDE_SKILL_DIR}/gpt_image.py edit \
--prompt "Add a rainbow in the sky" \
--input photo.png \
--output "photo-with-rainbow.png"
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"
python3 ${CLAUDE_SKILL_DIR}/gpt_image.py \
--prompt "Detailed portrait of a cat in watercolor style" \
--model gpt-image-1 \
--output "cat-portrait.png"
If the script fails:
OPENAI_API_KEY is exportedOPENAI_API_BASE is correcthigh quality for final output, auto for quick iterationsNo comments yet — start the thread.
Sign in to join the discussion.
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
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
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
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