paper-figure

Generate publication-quality figures and LaTeX tables from experimental data.

Updated Jul 6, 2026
One-click install
npx skills add https://github.com/caw111/2026-SoftwareCup --skill paper-figure-caw111
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: paper-figure
Source: https://github.com/caw111/2026-SoftwareCup/tree/main/.agents/skills/paper-figure
Command: npx skills add https://github.com/caw111/2026-SoftwareCup --skill paper-figure-caw111

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill addresses the challenge of manually creating publication-quality figures and tables from experimental data, streamlining the process for researchers and scientists.

Core Features & Use Cases

  • Automated Figure Generation: Generate figures such as line plots, bar charts, scatter plots, heatmaps, and more directly from data.
  • Comparison Tables: Automatically create LaTeX tables for comparison purposes.
  • Multi-panel Figures: Combine multiple plots into a single figure for comprehensive visual representation.
  • Use Case: A researcher can use this Skill to quickly generate figures for their scientific paper without the need for extensive manual work.

Quick Start

Use the paper-figure skill to generate figures from the data in the 'experiment_results.csv' file.

Frequently Asked Questions about paper-figure

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

FAQPage Schema
How do I create publication-quality figures from experiment data?

You can generate publication-quality figures by feeding experiment data in JSON, CSV, or screen log format into an automated plotting tool. The process utilizes matplotlib to produce multi-panel plots and outputs high-resolution PDF or PNG files for academic publishing.

Can I generate LaTeX tables from CSV files for academic publishing?

Yes, you can generate LaTeX tables from CSV files for academic publishing. The tool automatically parses the structured experiment data to create comparison tables, streamlining the integration of tabular results into LaTeX documents.

What data formats are supported for automated figure generation?

Supported data formats for automated figure generation include JSON, CSV, and screen log formats. The tool processes these inputs to create various plot types and LaTeX tables, outputting the final visualizations as PDF or PNG files.

Does this data visualization tool support multi-panel figures?

Yes, this data visualization tool supports multi-panel figures. It allows you to combine multiple plots, such as line charts and heatmaps, into a single comprehensive figure for scientific papers using matplotlib.

What is the best way to visualize experiment data for a research paper?

The best way to visualize experiment data for a research paper is using an automated generation tool that creates publication-quality figures and LaTeX tables. It processes CSV or JSON inputs using matplotlib and pandas to output ready-to-publish PDF or PNG files.