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scientific-visualization

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

48|6|Updated Mar 9, 2026
Search Tags:#visualization#plotly#matplotlib#seaborn#publication#figures#colorblind
One-click install
npx skills add https://github.com/qinyan-ai/qinyan-academic-skills --skill scientific-visualization-qinyan-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: scientific-visualization
Source: https://github.com/qinyan-ai/qinyan-academic-skills/tree/main/skills/03-%E5%AD%A6%E6%9C%AF%E6%BC%94%E7%A4%BA%E4%B8%8E%E5%8F%AF%E8%A7%86%E5%8C%96/scientific-visualization
Command: npx skills add https://github.com/qinyan-ai/qinyan-academic-skills --skill scientific-visualization-qinyan-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Publication-quality figures for scientific manuscripts are time-consuming to craft and prone to inconsistent styling. This Skill centralizes styles, palettes, and layout patterns to streamline creation of multi-panel figures that conform to journal guidelines.

Core Features & Use Cases

  • Multi-panel figure layouts: Arrange panels with consistent spacing and labeling across figures.
  • Journal-style presets: Apply publisher-like typography, color palettes, and export settings for Nature, Science, Cell, and more.
  • Accessibility and export: Ensure colorblind-friendly palettes and export in vector or high-DPI raster formats for manuscript submission.

Quick Start

Configure publication styles, build your figure with Matplotlib/Seaborn/Plotly, and export publication-ready formats with the built-in scripts.

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 for journals like Nature or Cell?▼

Create publication-ready scientific figures by applying journal-specific presets for typography, color palettes, and multi-panel layouts. This Skill centralizes styling guidelines to ensure consistency and accessibility for manuscript submissions.

Does this Skill support colorblind-friendly palettes for scientific visualization?▼

Yes, colorblind-friendly palettes are supported for scientific visualization. The Skill applies accessibility-focused publication palettes to ensure figures remain legible and compliant with journal guidelines for all readers.

How do I export multi-panel matplotlib figures to vector or high-DPI raster formats?▼

Export multi-panel matplotlib figures to vector or high-DPI raster formats using the built-in scripts and export presets. The workflow ensures figures meet the resolution and styling requirements for journal submission.

Can I use seaborn or plotly with these publication figure presets?▼

Yes, you can build your scientific figures using Matplotlib, Seaborn, or Plotly. The Skill provides configurable scripts and publication presets that apply the journal-specific styling across your chosen visualization library.

What's the best way to arrange multi-panel layouts with consistent spacing for publication?▼

The best way to arrange multi-panel layouts is by using the Skill's centralized layout patterns. These scripts configure consistent spacing, axes, and labeling across all figures to conform to publisher-like guidelines.

Why do my scientific figures have inconsistent typography and styling across different plots?▼

Inconsistent typography and styling occur without centralized styles. This Skill applies publisher-like typography, color palettes, and export settings across all panels to ensure visual consistency for scientific manuscripts.

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