Best use case
scientific-visualization is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
## Overview
Teams using scientific-visualization should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/visualization/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How scientific-visualization Compares
| Feature / Agent | scientific-visualization | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
## Overview
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Scientific Visualization ## Overview Publication-quality scientific figure generation. GENERAL: language-agnostic (R, Python, Julia, or any tool). ## Aesthetic System (ScienceClaw Standard) ### Palette Selection | Group Count | Recommended Palette | |-------------|-------------------| | 2-5 groups | NPG or Lancet | | 6-12 groups | Paired | | >12 groups | colorRampPalette | | Diverging data | RdBu | | Sequential data | viridis | | Up/Down/NS | "#E64B35" / "#4DBBD5" / "#999999" | ### Journal Figure Sizing | Format | Width | Height | Base Size | DPI | |--------|-------|--------|-----------|-----| | Single column | 8.5 cm | 7 cm | 11 pt | 300 | | 1.5 column | 12 cm | 9 cm | 12 pt | 300 | | Double column | 17.5 cm | 10 cm | 13 pt | 300 | | PPT | 25 cm | 18 cm | 16 pt | 150 | ### Theme Rules - Clean, minimal. No unnecessary gridlines. - theme_classic() or theme_bw() as starting points (R) / white background in matplotlib - Consistent margins across all figures in a project - Arial or Helvetica font family ### Code Rules - Adjustable parameters at the TOP of every script - Return the plot object (don't hardcode file saving) - Output formats: PNG (300+ dpi), PDF (vector), SVG ## Chart Type Guide - **Distribution**: boxplot, violin, density, histogram, jitter - **Comparison**: barplot, grouped bar, dotplot, radar - **Correlation**: scatter, correlation matrix, bubble - **Composition**: pie, ring, Venn, UpSet, stacked bar - **Genomics**: volcano, Manhattan, Q-Q, GSEA, UMAP/tSNE, heatmap - **Survival**: Kaplan-Meier, Cox forest plot - **Network**: Sankey, chord, network graph - **Spatial**: spatial transcriptomics, geographic ## 35 Detailed Chart Skill References Available in `mcp-servers/visualization/skills/` — one .md file per chart type with full aesthetic guidelines, data requirements, and code examples.
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## Overview
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