From openrouter
Generates images from text prompts and edits existing images via OpenRouter's Image API. Discovers model capabilities to avoid guessing parameters.
How this skill is triggered — by the user, by Claude, or both
Slash command
/openrouter:openrouter-imagesThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Generate images from text prompts and edit existing images via OpenRouter's dedicated Image API (`POST /api/v1/images`). The skill also discovers which models exist and which parameters each one accepts, so you pick a valid model and options instead of guessing.
Generate images from text prompts and edit existing images via OpenRouter's dedicated Image API (POST /api/v1/images). The skill also discovers which models exist and which parameters each one accepts, so you pick a valid model and options instead of guessing.
The OPENROUTER_API_KEY environment variable must be set. Get a key at https://openrouter.ai/keys
Discovery (discover.ts) is public and works without a key; generation and editing require one.
cd <skill-path>/scripts && npm install
Pick the right script based on what the user is asking:
| User wants to... | Script | Example |
|---|---|---|
| See which image models exist and what they support | discover.ts | "What image models can I use?" |
| Check the exact params a specific model accepts | discover.ts <model> | "Does seedream support 4K?" |
| Generate an image from a text description | generate.ts "prompt" | "Create an image of a sunset over mountains" |
| Generate with specific options | generate.ts "prompt" --aspect-ratio 16:9 | "Make a wide landscape image of a forest" |
| Generate with a different model | generate.ts "prompt" --model <id> | "Generate using gemini 3.1 flash lite image" |
| Edit or modify an existing image | edit.ts path "prompt" | "Make the sky purple in photo.png" |
| Transform an image with instructions | edit.ts path "prompt" | "Add a party hat to the animal in this image" |
Different models accept different parameters. Rather than hardcoding flags and hitting 400s, discover what's available before generating.
List every image model with a compact capability summary:
cd <skill-path>/scripts && npx tsx discover.ts
Each entry reports the model id, input_modalities / output_modalities (image input means it supports editing / image-to-image), supports_streaming, and a supported_parameters map — the union of what any endpoint of that model accepts.
Inspect one model's definitive per-endpoint capabilities:
cd <skill-path>/scripts && npx tsx discover.ts bytedance-seed/seedream-4.5
This calls GET /api/v1/images/models/{author}/{slug}/endpoints and returns, per provider endpoint:
| Field | Meaning |
|---|---|
provider_name / provider_slug | The serving provider. Use provider_slug as the key in --provider-options. |
supported_parameters | The exact parameters this endpoint accepts, with allowed values. |
allowed_passthrough_parameters | Provider-specific keys you can pass under --provider-options (e.g. steps, guidance). |
supports_streaming | Whether this endpoint streams. |
pricing | Per-image / per-token pricing lines. |
Capability values print as readable strings: an enum shows as 1K | 2K | 4K, a range as 0–100, a boolean as supported. A parameter that's absent is unsupported — don't send it.
Create a new image from a text prompt:
cd <skill-path>/scripts && npx tsx generate.ts "a red panda wearing sunglasses"
cd <skill-path>/scripts && npx tsx generate.ts "a futuristic cityscape at night" --aspect-ratio 16:9
cd <skill-path>/scripts && npx tsx generate.ts "pixel art of a dragon" --output dragon.png
cd <skill-path>/scripts && npx tsx generate.ts "a watercolor painting" --model google/gemini-3.1-flash-lite-image --resolution 1K
Modify an existing image with a text prompt. The source image is sent as an image-to-image reference (input_references), so use a model whose input_modalities include image — check with discover.ts <model>.
cd <skill-path>/scripts && npx tsx edit.ts photo.png "make the sky purple"
cd <skill-path>/scripts && npx tsx edit.ts avatar.jpg "add a party hat" --output avatar-hat.png
cd <skill-path>/scripts && npx tsx edit.ts scene.png "convert to watercolor style" --model google/gemini-3.1-flash-lite-image
Supported input formats: .png, .jpg, .jpeg, .webp, .gif
Both generate.ts and edit.ts accept the same flags. Only pass parameters the target model supports — verify with discover.ts <model>.
| Flag | Description | Default |
|---|---|---|
--model <id> | OpenRouter model ID | google/gemini-3.1-flash-image-preview |
--output <path> | Output file path | image-YYYYMMDD-HHmmss.png |
--aspect-ratio <r> | Aspect ratio (e.g. 16:9, 1:1, 4:3) | Model default |
--resolution <t> | Resolution tier (512, 1K, 2K, 4K) | Model default |
--size <s> | Shorthand: a tier (2K) or explicit pixels (2048x2048) | Model default |
--quality <q> | auto, low, medium, or high | Model default |
--output-format <f> | png, jpeg, webp, or svg (vector models) | Model default |
--background <b> | auto, transparent, or opaque | Model default |
--output-compression <n> | Compression 0–100 for webp/jpeg | Model default |
--n <count> | Number of images to generate (1–10, provider permitting) | 1 |
--seed <int> | Seed for deterministic generation (where supported) | Random |
--provider-options <json> | Provider-specific passthrough, keyed by provider_slug | None |
--provider-options takes a JSON object keyed by provider slug, using keys from that endpoint's allowed_passthrough_parameters:
cd <skill-path>/scripts && npx tsx generate.ts "a dramatic portrait" \
--model black-forest-labs/flux.2-pro \
--provider-options '{"black-forest-labs": {"steps": 40, "guidance": 3}}'
{
"model": "google/gemini-3.1-flash-image-preview",
"prompt": "a red panda wearing sunglasses",
"images_saved": ["/absolute/path/to/image-20260305-143022.png"],
"count": 1
}
{
"model": "google/gemini-3.1-flash-image-preview",
"source_image": "photo.png",
"prompt": "make the sky purple",
"images_saved": ["/absolute/path/to/image-20260305-143055.png"],
"count": 1
}
The generation cost (USD) is printed to stderr when the API reports it. When --n requests multiple images, each is saved with a -1, -2, … suffix.
Generation uses POST /api/v1/images. See the Image Generation guide for full request/response details.
Images come back base64-encoded in a data array. For raster PNG output, media_type is omitted; vector outputs (e.g. SVG) include it, and the saved file extension follows it:
{
"created": 1748372400,
"data": [{ "b64_json": "<base64-encoded image data>" }],
"usage": { "prompt_tokens": 0, "completion_tokens": 4175, "total_tokens": 4175, "cost": 0.04 }
}
The default model is google/gemini-3.1-flash-image-preview (Nano Banana 2). To use another, pass --model <id> with any image model ID (e.g. google/gemini-3.1-flash-lite-image). Run discover.ts to browse image models and discover.ts <model> to confirm which parameters and providers it supports before generating.
npx claudepluginhub openrouterteam/skills --plugin openrouterGenerates and edits images using AI models (FLUX, Gemini) via OpenRouter. Use for photos, illustrations, artwork, and visual assets. Not for technical diagrams.
Generates and edits images via OpenRouter using FLUX and Gemini models. Use for photos, illustrations, artwork, and visual assets, not technical diagrams.
Generates or edits images using AI models (FLUX, Gemini) via OpenRouter Python script. For photos, illustrations, artwork, visual assets, concept art; excludes technical diagrams like flowcharts.