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Lord1Egypt
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scientific-visualization

Generate journal-compliant scientific figures with matplotlib, seaborn, and plotly.

2|Updated Jun 4, 2026
Search Tags:#accessibility#visualization#science#plotting#matplotlib#seaborn#publication
One-click install
npx skills add https://github.com/Lord1Egypt/scientific-agent-toolkit --skill scientific-visualization-lord1egypt
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: scientific-visualization
Source: https://github.com/Lord1Egypt/scientific-agent-toolkit/tree/main/scientific-skills/scientific-visualization
Command: npx skills add https://github.com/Lord1Egypt/scientific-agent-toolkit --skill scientific-visualization-lord1egypt

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This skill solves the challenge of creating high-quality, journal-compliant figures that meet strict resolution, accessibility, and formatting standards required by top-tier scientific publications.

Core Features & Use Cases

  • Journal-Specific Styling: Automatically configures figure dimensions and styles for journals like Nature, Science, and Cell.
  • Accessibility Compliance: Implements colorblind-friendly palettes (Okabe-Ito) and grayscale testing to ensure figures are inclusive.
  • Publication Workflow: Provides automated export utilities for vector (PDF/EPS) and raster (TIFF) formats at required DPI levels.

Quick Start

Use the scientific-visualization skill to apply the Nature journal style to your current matplotlib figure and export it as a 300 DPI PDF.

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 scientific figures with matplotlib that meet journal formatting standards?▼

To create publication-ready scientific figures with matplotlib, you must enforce journal-specific formatting, resolution, and accessibility standards. This skill configures figure dimensions and styles to comply with requirements from publishers like Nature, Science, and Cell.

Can I apply colorblind-safe palettes and grayscale testing to seaborn plots for manuscripts?▼

Yes, you can apply colorblind-safe palettes and grayscale testing to seaborn plots for manuscripts. This skill implements colorblind-friendly palettes like Okabe-Ito to ensure visualizations are inclusive and accessible for publication.

Does this skill support exporting matplotlib figures to vector and raster formats at required DPI levels?▼

Yes, this skill supports exporting matplotlib figures to vector and raster formats at required DPI levels. It provides automated export utilities for PDF, EPS, and TIFF formats to satisfy strict publication resolution standards.

What's the best way to generate multi-panel layouts with statistical annotations for scientific publications?▼

The best way to generate multi-panel layouts with statistical annotations for scientific publications is using specialized visualization skills. This skill integrates with matplotlib, seaborn, and plotly to facilitate complex layouts and ensure compliance.

Do I need pandas and scipy to create journal-compliant scientific visualizations?▼

You need pandas and scipy to handle data manipulation and statistical calculations when creating journal-compliant scientific visualizations. This skill integrates these dependencies alongside matplotlib and seaborn to produce publication-quality figures.

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