Generates journal-ready scientific figures and multi-panel layouts following publication-quality standards.
This skill empowers researchers and scientists to create professional, publication-grade visualizations directly within Claude Code. It provides specialized guidance for creating multi-panel figures, applying journal-specific style presets (like Nature, Science, or Cell), and ensuring colorblind-safe palettes. By automating complex matplotlib and seaborn configurations, it handles technical requirements such as high-DPI resolution, vector export (PDF/EPS), and statistical markers, allowing users to focus on data interpretation rather than plot formatting.
Key Features
01Colorblind-safe palettes and perceptually uniform colormaps
02Automated multi-panel figure layouts with consistent labeling (A, B, C)
03Journal-specific styling for Nature, Science, Cell, and PLOS
04324 GitHub stars
05Integration of statistical markers, error bars, and significance indicators
06Publication-quality export in vector (PDF/EPS) and high-DPI raster formats
Use Cases
01Converting raw data plots into accessible, colorblind-friendly graphics for presentations
02Preparing high-resolution figures for submission to peer-reviewed scientific journals
03Standardizing visualization styles across a research team or large project
