openrouterteam/skills

openrouter-images

Generate images from text prompts and edit existing images using OpenRouter's dedicated Image API.

First seen Mar 5, 2026

Installation

$ npx skills add openrouterteam/skills --skill openrouter-images

Summary

  • Generate images from text prompts and edit existing images using OpenRouter's dedicated Image API.
  • Use when the user asks to create, generate, or make an image, picture, or illustration from a description, or wants to edit, modify, transform, or alter an existing image with a text prompt.

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Repository health

Stars 241
Default branch main
Open issues 13
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Declared agents gemini

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 7,829 B
  • docs README.md 1,446 B
  • docs SUMMARY.md 314 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 331 installs

SKILL.md

OpenRouter Images

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.

Prerequisites

The OPENROUTERAPIKEY 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.

First-Time Setup

cd <skill-path>/scripts && npm install

Decision Tree

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"

Discover Capabilities First

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, inputmodalities / outputmodalities (image input means it supports editing / image-to-image), supportsstreaming, and a supportedparameters 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
providername / providerslug The serving provider. Use provider_slug as the key in --provider-options.
supported_parameters The exact parameters this endpoint accepts, with allowed values.
allowedpassthroughparameters 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.

Generate Image

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

Edit Image

Modify an existing image with a text prompt. The source image is sent as an image-to-image reference (inputreferences), so use a model whose inputmodalities 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

Options

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 allowedpassthroughparameters:

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}}'

Output Format

generate.ts

{
  "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
}

edit.ts

{
  "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.

API Response Shapes

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 }
}

Using a Different Model

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.

Presenting Results

  • After generating or editing, display the saved image to the user
  • Include the model used and, when reported, the generation cost (printed to stderr)
  • If multiple images are returned, show all of them
  • When the user doesn't specify an output path, tell them where the file was saved
  • For edit operations, mention the source image that was modified