mcpbeat

Generate Image

k-dense-ai/generate-image

Generate or edit images with AI models through the OpenRouter Image API (Gemini, Seedream, Recraft, GPT-Image, Riverflow). Use for photos, illustrations, artwork, concept art, visual assets, logos, and image editing or compositing from reference images. For flowcharts, circuits, pathways, and other technical diagrams, use the scientific-schematics skill instead.

14k tokens
context cost
the whole folder, loaded on every use
3
files
ships runnable scripts
0
copies elsewhere
how many repositories repackaged it
32514
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill generate-image

The instruction itself

14 sections, as written by the author

Generate Image

Generate and edit images through OpenRouter's Image API, which reaches Gemini, Seedream, Recraft,

GPT-Image, Riverflow, and roughly thirty other models behind one request shape.

When to use

Use this skill for: photos and photorealistic images, illustrations and artwork, concept art,

presentation and poster visuals, logos and vector marks, image editing, and compositing from

reference images.

Use scientific-schematics instead for: flowcharts, circuit diagrams, biological pathways,

system architecture diagrams, CONSORT diagrams, and other technical schematics.

API key

Generation requires an OpenRouter key. The script resolves it in this order:

  • --api-key
  • the OPENROUTER_API_KEY environment variable
  • OPENROUTER_API_KEY= in a .env file, searching the working directory upward, then the

script's own directory

If none is present the script exits with setup instructions. Keys: https://openrouter.ai/keys

--list-models, --model-info, and --dry-run need no key.

Quick start

# Generate
python scripts/generate_image.py "A beautiful sunset over mountains"

# Edit an existing image
python scripts/generate_image.py "Make the sky purple" -i photo.jpg -o edited.png

Paths are relative to this skill's directory. Output defaults to generated_image.<ext>, where the

extension follows the media type the model returned. The per-request cost is printed after the run.

Then look at the image. Read the file back and check it before using it anywhere: composition,

aspect ratio, and any text are all things models get wrong silently.

Choosing a model

Default: google/gemini-3.1-flash-image.

| Need | Model |

| --- | --- |

| General quality, prompt adherence | google/gemini-3.1-flash-image |

| Highest Gemini tier | google/gemini-3-pro-image |

| Cheap iteration | google/gemini-3.1-flash-lite-image (1K only), openai/gpt-image-1-mini |

| Photoreal control, reproducible seeds | bytedance-seed/seedream-4.5 |

| Several images per request | bytedance-seed/seedream-4.5, openai/gpt-image-2 (up to 10) |

| Vector / SVG output | recraft/recraft-v4.1-vector |

| Transparent background | openai/gpt-image-1 with --background transparent |

| Legible text inside the image | recraft/recraft-v4.1, sourceful/riverflow-v2.5-pro — see the caveat below |

references/models.md carries the full catalogue with per-model parameters, allowed values, and

prices. The live listing is authoritative and free:

python scripts/generate_image.py --list-models            # every model and its allowed values
python scripts/generate_image.py --list-models gemini     # filtered by substring
python scripts/generate_image.py --model-info openai/gpt-image-1   # one model, plus pricing

Parameter support varies by model

This is the main thing to get right. Models advertise different parameter sets **and different

allowed values**, and sending something a model does not support is rejected, not ignored.

The script checks the request against the live catalogue before spending anything, so a bad

parameter fails locally in under a second with the legal values printed:

$ python scripts/generate_image.py "abstract pattern" -m openai/gpt-image-2 --background transparent
Error: Request rejected before billing (1 problem):
  - background=transparent is not allowed; this model accepts: auto, opaque

Rough guide — but let the check be the authority, since the catalogue moves:

  • --resolution — Gemini, Seedream, Riverflow, Krea, Grok. The tiers differ: 512 only on Gemini

3.1 Flash, 4K on Gemini 3 Pro / Seedream / Riverflow, and 1K only on

gemini-3.1-flash-lite-image and the Krea models.

  • --output-format — Riverflow 2.5 only (png, jpeg, webp; the fast variant takes jpeg

alone). Gemini, OpenAI, Seedream, and Recraft all choose their own container.

  • --quality, --background, --output-compression — the OpenAI family, plus --background on

Riverflow 2.5. **--background transparent is not available on gpt-image-2 or

gpt-5.4-image-2** — use gpt-image-1, gpt-image-1-mini, gpt-5-image, or gpt-5-image-mini.

  • --seed — Seedream and Krea. Not Gemini, not OpenAI.
  • --aspect-ratio — nearly all models, but the enum differs sharply: gpt-image-1 accepts only

1:1, 3:2, 2:3, auto, and gpt-5-image* does not accept it at all.

  • --n — capped per model: 1 for Gemini, Riverflow, MAI and Grok, 6 for Recraft, 10 for Seedream

and OpenAI. The Krea models reject it outright.

Pass --dry-run to validate and print the exact request body without generating or billing.

--no-preflight skips the check when you want the API itself to arbitrate.

Writing the prompt

Prompt quality decides output quality more than model choice does. Name, in one sentence each:

  • Subject — what is in frame, and how much of it. "A single pipette tip above a 96-well plate."
  • Medium and style — photograph, watercolour, 3D render, flat vector, scientific illustration.
  • Lighting and palette — "soft diffuse lighting, cool blue and white palette."
  • Composition — "wide shot, subject left of centre, empty space on the right for a title."
  • What to avoid — "no text, no labels, no watermark."

Asking for empty space where a caption or title will go is the single most useful compositional

instruction for posters and slides.

Iterate cheaply: draft on gemini-3.1-flash-lite-image, then regenerate the wording you settled on

with the model you actually want. To refine rather than restart, feed the last output back as a

reference (-i out.png) and describe only the change.

Editing and reference images

-i/--input is repeatable and accepts local paths, HTTP(S) URLs, or data URLs. Local files are

base64-encoded and sent as input_references.

# Single-image edit
python scripts/generate_image.py "Add sunglasses to the person" -i portrait.png

# Composite several references
python scripts/generate_image.py "Blend these two styles" -i style_a.png -i style_b.jpg -o blend.png

# Reference an image already on the web
python scripts/generate_image.py "Restyle as a watercolor" -i https://example.com/photo.jpg

Reference limits differ: 16 for OpenAI, 14 for Gemini and Seedream, 10 for riverflow-v2*-pro,

3 for gemini-2.5-flash-image and Grok, 1 for Recraft, MAI, and Krea. Accepted local formats: PNG,

JPEG, GIF, WebP. Riverflow v2 bills $0.20 per reference image on top of the output.

Worked examples

The -o paths are destinations the script creates, not files bundled with the skill.

# Wide hero image for a poster, with space reserved for the title
python scripts/generate_image.py \
  "Laboratory with modern equipment, photorealistic, well-lit, wide shot, \
   equipment on the left, empty wall on the right, no text" \
  --aspect-ratio 21:9 --resolution 2K -o poster/hero.png

# Conceptual illustration for a manuscript — illustrative, never presented as data
python scripts/generate_image.py \
  "Stylised illustration of immune cells surrounding a tumour cell, scientific illustration, \
   cool palette, no text" \
  --resolution 2K -o figures/immunotherapy_concept.png

# Vector logo
python scripts/generate_image.py \
  "Minimal geometric fox logo, two colors" \
  -m recraft/recraft-v4.1-vector -o assets/logo.svg

# Slide background with a transparent alpha channel
python scripts/generate_image.py \
  "Abstract molecular pattern, subtle, blue and white, no text" \
  -m openai/gpt-image-1 --background transparent -o slides/bg.png

# Four variations in one request
python scripts/generate_image.py \
  "Stylized neuron network illustration" \
  -m bytedance-seed/seedream-4.5 --n 4 -o variations.png
# -> variations_1.png ... variations_4.png

# Reproducible output
python scripts/generate_image.py "A cat astronaut" \
  -m bytedance-seed/seedream-4.5 --seed 42

# Check a request costs nothing to get wrong
python scripts/generate_image.py "A cat astronaut" --resolution 4K --dry-run

Script parameters

| Flag | Purpose |

| --- | --- |

| prompt | Image description, or the edit to apply (required unless --list-models / --model-info) |

| -m, --model | Model slug (default google/gemini-3.1-flash-image) |

| -o, --output | Output path; extension defaults to the returned media type |

| -i, --input | Reference image — path, URL, or data URL. Repeatable |

| --n | Images per request, model-capped |

| --aspect-ratio | 1:1, 16:9, 9:16, 4:3, 3:2, 21:9, … — enum differs per model |

| --resolution | 512, 1K, 2K, 4K — tiers differ per model |

| --quality | auto, low, medium, high (OpenAI) |

| --output-format | png, jpeg, webp (Riverflow 2.5) |

| --background | auto, transparent, opaque |

| --output-compression | 0–100, OpenAI models |

| --seed | Deterministic output where supported |

| --api-key | Overrides the environment and .env |

| --timeout | Request timeout, seconds (default 300) |

| --retries | Retries for rate limits and 5xx responses (default 2) |

| --no-preflight | Skip the free capability check before the billed request |

| --dry-run | Validate and print the request, then exit without generating |

| --list-models | Print the catalogue with allowed values, optionally filtered, then exit |

| --model-info | Print one model's allowed values and pricing, then exit |

There is no --size: no model in the catalogue accepts a size parameter. Shape output with

--aspect-ratio and --resolution.

API shape

For direct requests without the script:

curl -s https://openrouter.ai/api/v1/images \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "google/gemini-3.1-flash-image",
    "prompt": "A red bicycle against a white wall",
    "aspect_ratio": "16:9"
  }'

Response:

{
  "created": 1748372400,
  "data": [{ "b64_json": "<base64>", "media_type": "image/png" }],
  "usage": {
    "prompt_tokens": 4,
    "completion_tokens": 1120,
    "total_tokens": 1124,
    "cost": 0.0672,
    "completion_tokens_details": { "image_tokens": 1120 }
  }
}

b64_json is raw base64, not a data URL. media_type reflects the real format, so honour it

when naming files — vector models return image/svg+xml, and gemini-3.1-flash-lite-image returns

JPEG rather than PNG.

Streaming ("stream": true) emits image_generation.partial_image, image_generation.completed,

and error events, terminating with data: [DONE]. Only the OpenAI models support it, and the

bundled script does not use it.

Billing is all-or-nothing: a generation is either completed and billed in full, or it fails and is

not billed — so a rejected parameter costs nothing but time. Streaming preview frames are not

charged separately. On a bring-your-own-key account usage.cost reads 0 and the real amount is

in cost_details.upstream_inference_cost; the script reports that figure rather than claiming the

run was free.

Cost

Per-image models are predictable: Seedream $0.04, Recraft v4.1 $0.035 (vector $0.08, pro $0.21),

Riverflow 2.5 fast $0.019 and pro $0.13–0.17, Grok $0.05–0.07.

Gemini, OpenAI, and MAI bill per output token, which scales with resolution — a 4K image costs

roughly sixteen times a 1K one. Measured: one 1K gemini-3.1-flash-lite-image render is 1120

output tokens, $0.034. At the same size gemini-3.1-flash-image is double that and

gemini-3-pro-image four times. Draft at low resolution on a cheap model; pay for size once.

Notes and caveats

  • Models cannot be trusted with text. Words inside a generated image come back misspelled,

garbled, or invented. Ask for "no text" and overlay real type in LaTeX, PowerPoint, or HTML — or

use scientific-schematics when labels are the point.

  • A generated image is an illustration, never evidence. It shows nothing that was measured.

Never present one as microscopy, imaging, gel, or instrument output, never let it stand in for a

figure that reports results, and label it as an illustration in captions. Nature and Science both

require disclosure of generative-AI imagery, and several journals prohibit it outside

clearly-marked concept art — check the target venue before submitting.

  • Generation is a paid API call. Prefer a cheap model and low resolution while iterating on wording.
  • Generation takes roughly 5–60 seconds depending on model and resolution.
  • Reference images are uploaded to OpenRouter. Do not send unpublished or sensitive data, patient

images, or anything under embargo.

  • Never hardcode the API key. Keep it in the environment or an ignored .env.
  • Prompt specifically when editing: "change the sky to sunset colours" beats "edit the sky".
  • A refusal arrives as an HTTP 400 or 403 mentioning content policy, not as a bad image. Rephrase —

clinical and anatomical subjects trip moderation more often than the request warrants.

  • Rate limits and 5xx responses are retried automatically; a 4xx is final, because the request

itself is what needs changing.

  • scientific-schematics — technical diagrams, flowcharts, circuits, pathways
  • scientific-slides — presentations that embed generated visuals
  • latex-posters — posters that embed hero images

How to use it

Copy the folder

Take k-dense-ai/generate-image from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.