Gemini image

Skill BryceEWatson/claude-global-skills/gemini-image

A curated collection of Claude Code skills — code-review loop, local chat-history search, session end/resume, Gemini image generation, transcript retrospectives — that run machine-wide with just python and node.

Install

npx -y skills add BryceEWatson/claude-global-skills --skill gemini-image

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Generate and edit images with Google's Gemini models (Nano Banana / Gemini 3 Pro Image / 3.1 Flash Image) from a zero-dependency Python CLI. Use whenever the user wants to create, generate, edit, restyle, or compose an image with Gemini / Google AI; produce listing photos, mockups, banners, icons, or marketing visuals via Gemini; or attach reference images for image-to-image editing. Also handles text/conversation/model-listing — it is the maintained successor to the older `gemini-client` plugin. Triggers: "generate an image with Gemini", "use Google AI to make a picture", "Gemini image", "nano banana", "edit this image with Gemini", "Imagen".

SKILL.md

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gemini-image

The maintained, machine-wide core for image generation and editing with Google Gemini. One zero-dependency Python file — runs on any machine with python, no per-project install. It is the canonical successor to the gemini-client plugin (strict superset; that plugin is retired in its favour).

Quick start

GEM=~/.claude/skills/gemini-image/scripts/gemini_image.py

# Generate
python "$GEM" --image -o castle.png "A watercolor painting of a medieval castle"

# Pick a model / aspect ratio / resolution
python "$GEM" --image -o hero.png --model gemini-3-pro-image \
    --aspect-ratio 2:3 --image-size 2K "Botanical oil painting of peonies"

# Edit or compose from reference image(s) — repeat -i (3-pro up to 8, 3.1-flash up to 14)
python "$GEM" --image -o staged.png -i room.png -i sofa.png \
    "Place this sofa in this room with warm afternoon light"

# See which image models your key can use
python "$GEM" --list-models --images-only

Auth resolves in order: --api-key → GEMINI_API_KEY → GOOGLE_API_KEY → .env (cwd, then next to the script). The key is sent as x-goog-api-key.

Models (verified against the live API, 2026-06)

Model	Status	Use for
`gemini-3-pro-image` / `-preview`	GA / preview	Auto-selected default — highest fidelity, accurate text rendering, up to 8 reference images. Mockups, design, data-viz.
`gemini-3.1-flash-image` / `-preview`	GA / preview	Balanced (~half the cost, close to Pro on most prompts). Extreme aspect ratios (1:4…8:1), the `512` size, up to 14 reference images, video-to-image.
`gemini-2.5-flash-image`	GA	Cheapest/fastest, lowest fidelity. The offline/error fallback floor.
`imagen-4.0-*`	GA	Pure text-to-image via the separate `:predict` endpoint — not covered by this `generateContent` client.

Aspect ratios: 1:1 2:3 3:2 3:4 4:3 4:5 5:4 9:16 16:9 21:9 (3.1-flash adds the extreme ratios). Sizes: 1K 2K 4K universally; 512 only on gemini-3.1-flash-image.

Default model: best available, auto-selected

Omit --model (CLI) or model= (library) and the skill resolves the best image model your key can access — currently gemini-3-pro-image — instead of a fixed id. It stays current automatically: a future GA Pro model (e.g. gemini-4-pro-image) is adopted the day your key gains access, no code change. A newer flash model never displaces a GA pro one (newer ≠ higher fidelity).

Explicit always wins: --model <id> / model="<id>" skips resolution entirely (and the /models lookup).
Pin a default: GEMINI_IMAGE_DEFAULT=<id> hard-pins (e.g. a cost-sensitive project pins gemini-2.5-flash-image); explicit --model still overrides it.
Cost/speed: the best model costs more and is slower than the old default (approx. ~$0.13 vs ~$0.04/image, ~3× latency — Google list pricing, 2026-06). CLI use prints a one-line stderr notice when a non-default model is auto-selected; library use stays silent.
Never fails: the resolution is cached per key for 24h (a temp-file keyed by a hash of the API key — the key itself is never written). If /models is unreachable it falls back to gemini-2.5-flash-image, so a network blip can never break generation or cause a surprise bill.

What it does beyond the old plugin

Reference-image input (-i/--input-image, repeatable) — image editing and multi-image composition, which the plugin could not do.
Multi-image output — when the model returns several images they are all saved (out.png, out-2.png, …) instead of overwriting one file.
Safety-block diagnostics — a blocked/empty result reports the blockReason / finishReason / safety ratings instead of a bare "no image".
Verified model menu + exponential-backoff retry (429/5xx) + a GeminiError exception contract so projects can vendor the file and build thin wrappers (CLI exit 2 = image blocked, 1 = error, 0 = ok).

Importable

generate, generate_image, resolve_best_image_model, extract_text, extract_images, extract_usage, list_models, and GeminiError are public. generate_image() returns {output_paths, output_path, mime_type, text, blocked, diagnostic, raw}.

Notes

Every generated image carries an invisible SynthID watermark (Google, non-optional).
The saved file's extension matches the model's actual output format (the image models choose it — gemini-3-pro-image returns JPEG). A .png request that comes back as JPEG is saved as .jpg with a stderr note, so a file never lies about its contents.
The request uses generationConfig.imageConfig — the shape proven across all current production callers and accepted by the live API. The newer responseFormat.image shape is tracked as a future migration in SPEC.md, which is the canonical contract this skill and the project-specific TypeScript callers all conform to.
Per-project business logic (brand denylists, print-spec validation, Sharp compositing, pack rules) stays in those projects — this core only does correct generation/editing.