generate-image

name	generate-image
description	Generate or edit images via two backends: Google Gemini (gemini-3-pro-image) or any OpenAI-compatible endpoint (gpt-image-2, dall-e-3). Use when the user wants to create, draw, illustrate, or edit an image, icon, logo, poster, or concept art.

Generate Image (gemini / openai backends)

Turn a text prompt — optionally with reference images — into one or more images via one of two explicit backends. --backend has no default — always pick one (gemini or openai), or set IMAGE_BACKEND. The script does the API call, file saving, and configuration; your job is to pick the backend, craft a strong prompt, and wire up the flags.

• gemini — Google's native Gemini API via google-genai. Full feature set: --aspect-ratio, --size tiers (1K/2K/4K), and multi-image edit/compose (-i a.png -i b.png). Use GEMINI_API_KEY / GEMINI_IMAGE_MODEL.
• openai — any OpenAI-compatible image endpoint (OpenAI official, DashScope, new-api gateways, ...). Use OPENAI_API_KEY / OPENAI_BASE_URL / OPENAI_IMAGE_MODEL. Supports gpt-image-2, dall-e-3, etc.

Prerequisites

• uv available (the script is a self-contained uv run script; deps install on first run).

• The API key for the chosen backend. The script resolves it progressively, so any one works:

  • export GEMINI_API_KEY=... (gemini backend) or export OPENAI_API_KEY=... (openai backend), or
  • a .env file (checked in order: $PWD/.env, then ${CLAUDE_PLUGIN_ROOT}/.env), or
  • --api-key ... on the command line.

  CRITICAL -- Never paste the API key into chat or commit a .env. If the key is missing, the script prints exactly how to set it — relay that to the user rather than guessing.

Workflow

1. Clarify intent (only if genuinely ambiguous)

A one-line request like "draw a fox in a spacesuit" needs no questions — just generate. Ask (via AskUserQuestion) only when a choice would materially change the result and you cannot reasonably default it, e.g. aspect ratio for a "banner vs. avatar", or whether an attached image should be edited vs. used as style reference.

2. Craft the prompt

Read references/prompting.md before writing a non-trivial prompt. In short: describe subject, composition, lighting, style, and mood in concrete terms; put any literal text to render in quotes; and for edits, state what to change AND what to keep. A vivid one-paragraph prompt beats a terse phrase.

3. Run the script

Invoke it directly (the shebang runs it through uv):

${CLAUDE_PLUGIN_ROOT}/skills/generate-image/scripts/generate_image.py "PROMPT" --backend BACKEND -o OUT.png [flags]

Flags:

Flag	Purpose	Default
--backend	gemini (native Google API) or openai (OpenAI-compatible endpoint). No default — also via IMAGE_BACKEND.	required
-o, --output	Output path (.png/.jpeg)	generated.png
-i, --input	Reference/input image (repeatable). gemini: edit/compose multi-image. openai: edit single image (first wins).	none
--aspect-ratio	1:1 2:3 3:2 3:4 4:3 4:5 5:4 9:16 16:9 21:9. gemini: via image_config. openai: via extra_body (Gemini-compat endpoints only).	model decides
--size	gemini: 1K/2K/4K. openai: free string (1024x1024, auto, ...).	model decides
--count	Number of images. gemini: N separate calls. openai: one call, n=N.	1
--model	Model id or alias (else GEMINI_IMAGE_MODEL/OPENAI_IMAGE_MODEL). gemini: pro/flash/raw id. openai: raw id (e.g. gpt-image-2).	backend default
--quality	low/medium/high/auto — openai backend only.	model decides
--response-format	b64_json/url/none — openai backend only. url is downloaded to disk; none omits the param. Some gateways require url or reject the param (use none).	b64_json

Models (pass the alias to --model or set the backend's env var):

Backend	Alias / id	Notes
gemini	pro (default) → gemini-3-pro-image	highest quality
gemini	flash → gemini-2.5-flash-image	faster / cheaper
openai	gpt-image-2, dall-e-3, gpt-image-1, ...	any id the endpoint serves

Examples:

# Gemini, 2K wide banner
generate_image.py "podcast cover art" --backend gemini --aspect-ratio 16:9 --size 2K -o cover.png
# Gemini multi-image compose
generate_image.py "put the watch from image 1 on the wrist in image 2" --backend gemini -i watch.png -i wrist.png -o composite.png
# OpenAI-compatible gateway, gpt-image-2 (this gateway needs url format)
generate_image.py "a red bicycle" --backend openai --base-url https://api.tu-zi.com/v1 \
  --model gpt-image-2 --size 1024x1024 --response-format url -o bike.png
# OpenAI official
generate_image.py "a red bicycle" --backend openai --base-url https://api.openai.com/v1 --model gpt-image-2 -o bike.png

When the user wants choices to pick from, request --count 2 (or more) and show all outputs. With -i, the prompt becomes an edit/compose instruction over the supplied image(s).

4. Report

Tell the user the saved path(s). If nothing was returned, it is usually a safety-filtered prompt — say so and offer a reworded prompt. Output files are images: reference them by path; do not try to inline their bytes.

Configuration is progressive (the key best practice)

Backend, key, base URL, model, and quality are each resolved by lib/progressive_env.py in this order, stopping at the first hit: CLI flag → process env → .env chain → built-in default. This is why the same command works in a project with a local .env, in a shell with exports, or with everything overridden inline — and why a newer model or a different endpoint can be selected with export GEMINI_IMAGE_MODEL=... / export OPENAI_BASE_URL=... without touching code. See references/prompting.md for the parameter reference.

Files

• scripts/generate_image.py — the generator (google-genai for gemini, openai for openai).
• references/prompting.md — prompt-writing guide and full parameter reference.
• ${CLAUDE_PLUGIN_ROOT}/lib/progressive_env.py — shared progressive config resolver.