scientific-visualization

Generate publication-ready figures from raw data using Matplotlib, Seaborn, and Plotly.

1|Updated Mar 25, 2026

Search Tags:#visualization #matplotlib #publication #figures #colorblind #journal-standards

Ready to run

npx skills add https://github.com/Alanxtl/skills --skill scientific-visualization-alanxtl

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: scientific-visualization
Source: https://github.com/Alanxtl/skills/tree/main/scientific-visualization
Command: npx skills add https://github.com/Alanxtl/skills --skill scientific-visualization-alanxtl

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Scientific visualization for research requires publication-ready figures with clean multi-panel layouts, accessible color palettes, precise typography, and journal-compliant exports.

Core Features & Use Cases

Create publication-quality figures using Matplotlib, Seaborn, and Plotly with pre-configured publication styles.
Apply colorblind-friendly palettes, consistent typography, and support for multi-panel layouts across journals (Nature, Science, Cell, PLOS, etc.).
Export figures in vector or raster formats (PDF, EPS, SVG, TIFF, PNG) with appropriate DPI and journal-specific settings for manuscripts.

Quick Start

Configure styles and palettes with the provided scripts, then build and export a publication-ready figure using the example workflows.

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?▼

Publication-ready figures for journals like Nature, Science, and Cell require clean multi-panel layouts, accessible colorblind-friendly palettes, and precise typography. This skill applies pre-configured styles and deterministic export tools to meet those specific journal-compliant formatting standards.

Can I export Matplotlib figures to vector and high-resolution raster formats for journal submission?▼

Yes, you can export figures to vector and raster formats including PDF, EPS, SVG, TIFF, and PNG. The skill provides deterministic export tools like save_publication_figure to generate high-resolution outputs with appropriate DPI and journal-specific settings for manuscript submission.

Does this skill provide colorblind-friendly palettes for scientific visualization?▼

Yes, this skill provides colorblind-friendly palettes for scientific visualization. It includes accessible palette assets and style presets that ensure consistent color schemes across multi-panel figures, meeting publication accessibility standards.

What's the best way to design multi-panel layouts for Cell or PLOS journals?▼

The best way to design multi-panel layouts for Cell or PLOS journals is to apply the skill's journal-specific style presets. These pre-configured styles handle multi-panel figure design, consistent typography, and compliant export settings for those specific academic outlets.

Do I need to install Seaborn or Plotly separately to use this visualization skill?▼

Matplotlib is the only explicitly required dependency. While the skill supports generating figures using Matplotlib, Seaborn, and Plotly, only Matplotlib is listed in its dependencies for the core publication-ready figure generation and export workflows.