skills.rest
bahayonghang
bahayonghangCOMMUNITY
Explore all skills by this author →
GitHub

academic-figure

Generate journal-compliant academic figures from raw data using Matplotlib, Seaborn, or Plotly.

16|1|Updated Jan 2, 2026
Search Tags:#research#academic#visualization#plotting#matplotlib#publication
One-click install
npx skills add https://github.com/bahayonghang/my-ai-cli-toolkit --skill academic-figure-bahayonghang
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: academic-figure
Source: https://github.com/bahayonghang/my-ai-cli-toolkit/tree/main/skills/academic-research-tools/academic-figure
Command: npx skills add https://github.com/bahayonghang/my-ai-cli-toolkit --skill academic-figure-bahayonghang

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill solves the friction of creating and reviewing publication-ready academic figures that comply with strict journal requirements, saving researchers from manual formatting and rejection due to technical errors.

Core Features & Use Cases

  • Journal-Spec Mode: Generates figures compliant with IEEE, Elsevier, Nature, and other major journal standards, including vector-first exports and font embedding.
  • Data-Driven Reproduction: Recreates complex plots from user data using established academic styles like MemEvolve or SPICE.
  • Visual Mimicry: Reproduces figures from uploaded images into editable Matplotlib scripts with 300 DPI output.

Quick Start

Use the academic-figure skill to create an IEEE-compliant time-series plot from my provided data.

Frequently Asked Questions about academic-figure

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

FAQPage Schema
How do I create publication-ready figures that meet IEEE or Nature journal formatting standards?▼

You can reproduce complex academic plots from raw data using established styles like MemEvolve or SPICE. This process automates plotting while applying strict journal-specific visual standards, ensuring high-fidelity output for scientific manuscripts without manual formatting.

Can I recreate an editable Matplotlib script from an existing scientific figure image?▼

This Skill integrates with Matplotlib, Seaborn, and Plotly to ensure high-fidelity vector or raster output. It leverages these libraries to enforce journal-specific formatting, automate plotting from raw data, and perform compliance reviews for submission-ready graphics.

What is the best way to automate plotting from raw data for scientific manuscripts?▼

The best way to automate plotting from raw data is to apply established academic styles and enforce publication-ready standards automatically. This generates high-fidelity vector or raster outputs compliant with journal requirements, saving researchers from manual formatting and technical errors.

Does this approach support compliance review for submission-ready graphics before journal submission?▼

Yes, the approach supports compliance review for submission-ready graphics by checking figures against strict journal requirements. This review process verifies formatting, fonts, and resolution standards to ensure your scientific graphics are fully compliant before manuscript submission.

Related Skills

Explore More Education & Research Skills→
ovachieverovachiever
52

zarr-python

Create and manipulate chunked N-dimensional arrays with NumPy, Dask, and Xarray.

Community
Advanced
youyinnnyouyinnn
1

scientific-visualization

Automates creation of publication-ready scientific figures via Matplotlib and Seaborn with journal-specific formatting.

Community
Advanced
gracefullightgracefullight

seaborn

Generate statistical visualizations with seaborn in Python.

Community
Advanced
yf8578yf8578
1

plotly

Generate interactive, web-embeddable Plotly charts from your data.

Community
Intermediate