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paper-figure

Generate publication-quality figures and tables from JSON or CSV data using Python and matplotlib.

Updated Apr 29, 2026
Search Tags:#data-visualization#publication-ready#multi-panel#plots#experimental-results#figure-generation#latex-integration
One-click install
npx skills add https://github.com/jkfee/Auto-Research --skill paper-figure-jkfee
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: paper-figure
Source: https://github.com/jkfee/Auto-Research/tree/main/skills/paper-figure
Command: npx skills add https://github.com/jkfee/Auto-Research --skill paper-figure-jkfee

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Generate publication-quality figures and tables from experiment results to accelerate manuscript preparation and data storytelling.

Core Features & Use Cases

  • Data-driven plotting for experiments (line, bar, scatter, heatmaps)
  • Multi-panel figures and LaTeX-ready includes
  • Tables for comparisons and ablations, ready for publication

Quick Start

Feed your experiment results in JSON or CSV into the tool and run the per-figure scripts to produce publication-ready PDFs.

Frequently Asked Questions about paper-figure

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

FAQPage Schema
How do I generate publication-ready figures from CSV or JSON data for machine learning papers?▼

Generate publication-ready figures by feeding structured JSON or CSV experiment results into Python matplotlib scripts. The tool produces data-driven plots and multi-panel figures, outputting vector PDFs directly to your figures directory for manuscript inclusion.

Can I create LaTeX-ready tables for ablation studies and experimental comparisons?▼

Create LaTeX-ready tables for ablation studies and experimental comparisons directly from structured experiment data. The tool formats comparison and ablation results into tables suitable for immediate publication and LaTeX integration.

Do I need Python and matplotlib installed to produce multi-panel plots for data science research?▼

Python with matplotlib installed is required to produce multi-panel plots. You must have a Python environment configured with matplotlib and access to your experiment data sources in JSON or CSV format to generate the figures.

What types of data-driven plots can I build for experimental results?▼

Build line, bar, scatter, and heatmap plots for experimental results using Python and matplotlib. These data-driven visualizations support multi-panel figure assembly to comprehensively represent machine learning and data-science outcomes.

What are the limitations of automated figure generation for academic manuscripts?▼

Automated figure generation handles data-driven plots and tables but cannot create complex diagrams or hero imagery, which require manual creation. It is designed for experimental result visualization rather than illustrative graphics.

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