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scientific-visualization

Create publication-ready multi-panel figures with journal-specific styling and exports.

1|Updated Mar 5, 2026
Search Tags:#visualization#plotly#matplotlib#seaborn#publication#colorblind#multi-panel
One-click install
npx skills add https://github.com/Lin-Hi/DeepRead --skill scientific-visualization-lin-hi
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: scientific-visualization
Source: https://github.com/Lin-Hi/DeepRead/tree/main/.claude/skills/scientific-visualization
Command: npx skills add https://github.com/Lin-Hi/DeepRead --skill scientific-visualization-lin-hi

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires matplotlib, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

Transform data into publication-ready figures with consistent styling and journal-compliant layouts, reducing manual formatting and iteration time.

Core Features & Use Cases

  • Multi-panel figure assembly and layout management that adapts to single or double-column formats
  • Colorblind-safe palettes, typography conventions, and publisher-style integration across Matplotlib, Seaborn, and Plotly
  • Export to vector and raster formats (PDF, EPS, TIFF, PNG), with font embedding and DPI control tuned for various journals (Nature, Science, Cell)

Quick Start

Create a sample figure using the included style presets and export it to publication-ready formats.

Frequently Asked Questions about scientific-visualization

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create publication-ready figures for Nature or Cell journals?▼

Publication-ready figures for Nature or Cell are generated by applying configurable style presets that enforce publisher-specific typography, single or double-column layouts, and colorblind-safe palettes. The Skill then exports the final layout to journal-compliant formats.

Can I export matplotlib multi-panel figures to vector and raster formats with embedded fonts?▼

You can export matplotlib multi-panel figures to vector and raster formats including PDF, EPS, TIFF, and PNG. The export helpers handle font embedding and adjust DPI between 300 and 1000 to satisfy specific journal submission requirements.

Does this Skill support colorblind-safe palettes and typography conventions for scientific plotting?▼

The Skill supports colorblind-safe palettes and typography conventions across Matplotlib, Seaborn, and Plotly. It automatically applies these visual styles to ensure accessible and consistent scientific plotting without manual color adjustments.

What is the best way to automate multi-panel figure assembly for journal submissions?▼

Automating multi-panel figure assembly for journal submissions is best handled by the Skill's layout management, which adapts panels to single or double-column formats. It combines multiple subplots with publisher-specific styling and exports them as a unified journal-ready file.

Do I need matplotlib installed to use this scientific visualization Skill?▼

You need matplotlib installed to use this Skill, as it is a required dependency. The Skill builds upon matplotlib to apply journal-specific styling, manage multi-panel layouts, and handle export configurations for publication-ready output.

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