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light-figure-drawing

Create publication-ready figures with consistent styling across multiple plotting tools.

514|67|Updated Jun 7, 2026
Search Tags:#consistency#visualization#latex#publication#figure#gridlayout
One-click install
npx skills add https://github.com/Light0305/Light-skills --skill light-figure-drawing
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: light-figure-drawing
Source: https://github.com/Light0305/Light-skills/tree/main/skills/light-figure-drawing
Command: npx skills add https://github.com/Light0305/Light-skills --skill light-figure-drawing

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This skill provides a complete workflow to transform planning into publication-ready figures across multiple tools, ensuring a consistent, professional look suitable for direct submission to journals.

Core Features & Use Cases

  • Cross-tool figure drawing: Python (matplotlib/seaborn/plotly/altair), R (ggplot2), MATLAB, Visio, Origin, LaTeX/TikZ, Illustrator, PowerPoint.
  • Multi-panel composition and layout: consistent fonts, color palettes, and high-resolution vector outputs for clean, publication-quality figures.
  • Workflow-driven guidance: assets, templates and export scripts drive end-to-end figure creation with journal sizing checks and accessibility-conscious palettes.

Quick Start

Load your planning card and run the render workflow to generate the publication-ready figure.

Frequently Asked Questions about light-figure-drawing

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

FAQPage Schema
How do I create publication-ready figures with consistent styling across matplotlib and LaTeX?▼

This skill renders publication-ready figures by applying consistent fonts, colorblind-friendly palettes, and journal-specific sizing checks across matplotlib, LaTeX, and other tools to ensure clean, professional aesthetics for direct submission.

Can I assemble multi-panel figures using grid layouts in Python and R?▼

Yes, you can assemble multi-panel figures. The workflow supports Python (matplotlib/seaborn/plotly/altair) and R (ggplot2) to compose multiple plots into a single, consistently styled vector output.

Does this figure drawing workflow support colorblind-friendly palettes and vector outputs?▼

Yes, the figure drawing workflow supports colorblind-friendly palettes and high-resolution vector outputs. It ensures accessibility-conscious styling and clean rendering suitable for journal publication.

What is the best way to ensure font consistency across MATLAB, Visio, and Illustrator figures?▼

The best way to ensure font consistency is using a workflow-driven approach with standardized templates and export scripts. This standardizes fonts across MATLAB, Visio, Origin, and Illustrator for a unified look.

Do I need specific dependencies to run the figure rendering scripts?▼

Yes, you need matplotlib, numpy, Pillow, and colorspacious installed. These dependencies support the underlying data processing, image handling, and color space conversions required for rendering figures.

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