Medical-research-skills imagegenskill

Generate renderable, scientific-style SVG graphics directly from natural-language requirements (no image models). Use when users ask for an image/picture/scientific diagram/visualization poster or explicitly request SVG output for web-embeddable vector graphics.

install

source · Clone the upstream repo

git clone https://github.com/aipoch/medical-research-skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/aipoch/medical-research-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/scientific-skills/Other/imagegenskill" ~/.claude/skills/aipoch-medical-research-skills-imagegenskill && rm -rf "$T"

manifest: scientific-skills/Other/imagegenskill/SKILL.md

source content

Source: https://github.com/aipoch/medical-research-skills

When to Use

You need scientific-looking diagrams/posters (laboratory poster aesthetic) generated from a short natural-language brief.
The user requests SVG output specifically (e.g., “output SVG”, “vector graphic”, “embeddable in a web page”).
You want language-to-image results without using diffusion/LLM image models, prioritizing interpretable structure over photorealism.
You need repeatable, parameter-controlled visuals (seed/palette/structure) for research notes, slides, or documentation.
You want a structured visualization (grids, networks, waveforms, symbol rings) rather than an illustrative drawing.

Key Features

Converts a natural-language brief into a renderable SVG with a scientific, restrained visual style.
Multiple built-in styles via
```
STYLE
```
:
- ```
lab-atlas
```
  (default): calm, stable, laboratory map feel
- ```
signal-loom
```
  : denser spectral waveforms, stronger texture
- ```
lattice-field
```
  : prominent lattice grids, denser nodes
Produces SVG + JSON metadata (e.g.,
```
prompt
```
,
```
seed
```
,
```
palette
```
) for traceability.
Writes a convenience preview file:
```
output/svggen/latest.svg
```
.
Tunable density and composition controls (e.g., nodes, noise, bands, rings).

Dependencies

Python
```
3.8+
```

Note: No third-party Python packages are specified in the provided documentation. If
scripts/svg_gen.py
imports external libraries, add them here with exact versions.

Example Usage

# 1) Create the brief (UTF-8)
mkdir -p input
cat > input/brief.txt << 'EOF'
Scientific poster-style SVG: "Graph topology in latent space".
Include a calm lab-atlas aesthetic, visible grid + network + waveform layers,
and a few symbol rings. Use restrained colors, high text readability.
Keywords: latent space, manifold, spectral bands, topology.
EOF

# 2) (Optional) Edit configuration at the top of the generator script
#    - STYLE (lab-atlas | signal-loom | lattice-field)
#    - canvas width/height
#    - density parameters (node_count, noise_points, band_count, ring_density)
# Example:
# sed -i 's/^STYLE = .*/STYLE = "lab-atlas"/' scripts/svg_gen.py

# 3) Run generation
python scripts/svg_gen.py

# 4) View output
# Primary output directory:
ls -la output/svggen/
# Quick preview file:
# open output/svggen/latest.svg   (macOS)
# xdg-open output/svggen/latest.svg (Linux)
# start output/svggen/latest.svg  (Windows)

Expected outputs:

```
output/svggen/latest.svg
```
(latest render for quick preview)
```
output/svggen/<name>.svg
```
(generated SVG)

output/svggen/<name>.json

(metadata: includes

prompt

seed

palette

)

Implementation Details

Workflow

Write requirements to
```
input/brief.txt
```
(UTF-8).
Adjust the configuration section at the top of
```
scripts/svg_gen.py
```
(e.g.,
```
STYLE
```
, canvas dimensions, density parameters).
Run
```
python scripts/svg_gen.py
```
.
Open
```
output/svggen/latest.svg
```
to inspect the result.

Prompt / Brief Guidelines

Use clear research semantics: field, object, structure, atmosphere, keywords.
English technical terms are allowed (e.g.,
```
latent space
```
,
```
graph topology
```
) and should remain unchanged.
Keep the brief concise; the script maps text into structural elements and symbols.

Composition & Quality Criteria

Text readability: ensure key labels (e.g., prompt/mode text if present) are not obscured.
Structural hierarchy: at least three layers should be simultaneously visible, chosen from:
- grid
- waveform / spectral bands
- network / nodes
- symbol rings
Style consistency: avoid overly saturated colors; maintain scientific visual restraint.

Tuning / Troubleshooting Parameters

Output too dense: decrease
```
node_count
```
or
```
noise_points
```
.
Output too empty: increase
```
band_count
```
or
```
ring_density
```
.
Style mismatch: switch
```
STYLE
```
and regenerate.

Primary Entry Point

Generator script:
```
scripts/svg_gen.py
```