nature-figure-style

What problem does it solve?

Generates publication-ready Nature/Nature Photonics figure styles without painstaking manual tuning of fonts, line widths, ticks, panels, and palettes.

Core Features & Use Cases

• Matplotlib data-plot styling (Nature-compliant): line plots, bar charts, scatter plots, heatmaps, spectra, log-log, polar, insets, dual y-axes, and legends with Nature-specific spines/ticks and text sizing.
• Architecture/schematic diagram components (Nature Photonics-compliant): optical setups, block/flow diagrams, 2D vector schematics, and 3D isometric chip cross-sections with consistent material and pump/signal color conventions.
• Empirical guardrails & checklist: enforces recurring “Nature fingerprints” like sans-serif typography, bold lowercase panel labels (a/b/c), inward ticks, and consistent linewidths, plus a post-render validation checklist.
• Use case examples: turning a dataset into a Nature-style plot for submission, and producing an optical-setup schematic or hybrid (3D chip + 2D link) figure for Nature Photonics.

Quick Start

Use the nature-figure-style skill to generate a Nature-style line chart from your time-series data.