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scientific-visualization

Create publication-ready scientific figures with journal-compliant styling and colorblind-friendly palettes.

2|Updated Oct 29, 2025
Search Tags:#visualization#matplotlib#publication#color-palettes#colorblind#journal-standards
One-click install
npx skills add https://github.com/shanelindsay/agentic-r --skill scientific-visualization-shanelindsay
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: scientific-visualization
Source: https://github.com/shanelindsay/agentic-r/tree/main/skills/scientific-thinking/scientific-visualization
Command: npx skills add https://github.com/shanelindsay/agentic-r --skill scientific-visualization-shanelindsay

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires matplotlib, numpy, PyPDF2, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill helps researchers and developers create publication-quality figures quickly, ensuring accessibility and journal-compliant styling without manual formatting.

Core Features & Use Cases

  • Multi-panel figure composition with consistent styling that matches journal guidelines
  • Colorblind-friendly palettes and grayscale-friendly verification
  • Export in vector and high-resolution raster formats with precise DPI and font embedding

Quick Start

Configure publication style for a Nature-like single-column figure, build a three-panel layout, and export as a high-DPI PDF with embedded fonts.

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?▼

Create publication-ready scientific figures by applying journal-compliant styling, accessible colorblind-friendly palettes, and correct typographic conventions across multipanel layouts, heatmaps, and line plots.

How do I export matplotlib plots as high-DPI PDFs with embedded fonts?▼

Export matplotlib plots as high-resolution raster or vector PDFs with precise DPI and font embedding to satisfy strict file format requirements defined in journal guidelines.

What's the best way to verify colorblind-friendly palettes for scientific figures?▼

Verify colorblind-friendly palettes for scientific figures using built-in grayscale-friendly verification and accessible color schemes designed to meet journal publication standards.

Does this skill support multi-panel figure composition for Nature and Cell journals?▼

Multi-panel figure composition supports Nature, Science, Cell, and PLOS journals by applying consistent styling, specific figure sizing, and required typographic conventions.

Why do my journal figures fail publication guidelines for figure sizing and color schemes?▼

Journal figures fail publication guidelines when they lack correct figure sizing, accessible color schemes, and high DPI; applying automated publication-quality styling resolves these formatting issues.

Do I need numpy to build colorblind-friendly scientific figures?▼

You need numpy and matplotlib to build colorblind-friendly scientific figures, as these dependencies support the data manipulation and plotting required for journal-compliant outputs.

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