k-dense-ai/scientific-agent-skillsMIT3 files

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.

Specification
Skill ID
k-dense-ai/scientific-agent-skills/generate-image
Publisher
k-dense-ai
Repository
scientific-agent-skills
Installs
0
Files
3
License
MIT
Requires
Requires Python 3.9+ and network access to openrouter.ai. The bundled script uses only the standard library. Image generation requires the OPENROUTER_API_KEY credential and bills per request; listing models, inspecting a model, and --dry-run do not. Targets the OpenRouter Image API (POST /api/v1/images) as verified on 2026-07-31.
Synced
Sep 23, 2026
How to use it

Open any RiverX project, open the Skills panel in the chat, and search for this identifier. The files are fetched from the source repository at install time.

k-dense-ai/scientific-agent-skills/generate-imageInstalls these files
  • SKILL.md
  • references/models.md
  • scripts/generate_image.py

What this skill tells the agent

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:

  1. --api-key
  2. the OPENROUTER_API_KEY environment variable
  3. 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.

NeedModel
General quality, prompt adherencegoogle/gemini-3.1-flash-image
Highest Gemini tiergoogle/gemini-3-pro-image
Cheap iterationgoogle/gemini-3.1-flash-lite-image (1K only), openai/gpt-image-1-mini
Photoreal control, reproducible seedsbytedance-seed/seedream-4.5
Several images per requestbytedance-seed/seedream-4.5, openai/gpt-image-2 (up to 10)
Vector / SVG outputrecraft/recraft-v4.1-vector
Transparent backgroundopenai/gpt-image-1 with --background transparent
Legible text inside the imagerecraft/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:

  1. Subject — what is in frame, and how much of it. "A single pipette tip above a 96-well plate."
  2. Medium and style — photograph, watercolour, 3D render, flat vector, scientific illustration.
  3. Lighting and palette — "soft diffuse lighting, cool blue and white palette."
  4. Composition — "wide shot, subject left of centre, empty space on the right for a title."
  5. 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

More from k-dense-ai

Use this skill in a project

Open any RiverX project, search the Skills panel for k-dense-ai/scientific-agent-skills/generate-image, and install it in one click.

Use this skill