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aris-paper-figure

Generate publication-quality matplotlib figures and LaTeX tables from experiment data.

1.1k|116|Updated Feb 26, 2026
Search Tags:#publication#Matplotlib#research writing#plot generation#paper figures#LaTeX tables#Data Visualization
One-click install
npx skills add https://github.com/OpenLAIR/dr-claw --skill aris-paper-figure
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: aris-paper-figure
Source: https://github.com/OpenLAIR/dr-claw/tree/main/skills/aris-paper-figure
Command: npx skills add https://github.com/OpenLAIR/dr-claw --skill aris-paper-figure

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires matplotlib.

What problem does it solve?

Turning raw experiment results into publication-ready figures and tables is repetitive and error-prone, requiring consistent styling, correct figure-type selection, and LaTeX integration for every plot in a paper.

Core Features & Use Cases

  • Automated figure generation: Creates line plots, bar charts, scatter plots, heatmaps, box/violin plots, and multi-panel subfigures from JSON/CSV experiment data using matplotlib with a shared publication style config.
  • LaTeX table and snippet output: Produces comparison tables as standalone .tex files and generates latex_includes.tex with ready-to-paste figure environments.
  • Quality review workflow: Runs a reviewer-model pass over figure captions and plans, plus a publication checklist (font sizes, grayscale readability, no in-figure titles, vector PDF output).
  • Use Case: After finishing experiments for a conference paper, point the skill at your PAPER_PLAN.md figure plan and results JSON files to generate all data-driven figures at 300 DPI in PDF format, while preserving manually created architecture diagrams.

Quick Start

Ask the assistant to generate all paper figures from the figure plan in PAPER_PLAN.md and the experiment data in the figures directory.

Frequently Asked Questions about aris-paper-figure

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

FAQPage Schema
How do I generate publication-quality matplotlib figures for a paper?▼

Use a shared style configuration setting serif fonts, 10pt base size, 300 DPI, and PDF output, then write one Python script per figure that reads data from JSON or CSV files. Keep titles out of figures and put captions only in LaTeX.

What figure types can be auto-generated from experiment data?▼

Line plots for training curves, bar charts for method comparison, scatter plots, heatmaps, box/violin plots, and multi-panel subfigures can all be auto-generated. Comparison tables are produced as standalone LaTeX .tex files.

Can this skill create architecture or pipeline diagrams?▼

No, architecture diagrams, generated image grids, and screenshots are out of scope and must be created manually with tools like draw.io, Figma, or TikZ. The skill preserves existing manual figures and only generates their LaTeX include snippets.

Should paper figures be saved as PDF or PNG?▼

PDF is the default because it is a vector format that keeps text sharp in LaTeX documents. PNG at 300 DPI is supported only as a raster fallback when vector output is not possible.

Why do my paper figures look inconsistent across plots?▼

Inconsistency comes from per-script ad hoc styling. Use a single shared style module defining fonts, color palette, and sizes, and import it in every figure script so all outputs match the paper's typography.

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