Trae1ounG

Trae1ounG / paper-plot-skills

Public

开源高质量论文图表绘制Skills

43
4
69% credibility
Found Apr 19, 2026 at 43 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

A toolkit with examples and AI agents for generating or recreating publication-quality charts and tables in the style of academic papers from data inputs or images.

How It Works

1
📚 Discover Paper Plot Skills

You stumble upon this helpful tool that creates eye-catching charts just like those in research papers, perfect for reports or presentations.

2
🚀 Start your chart adventure

You visit the simple homepage and see easy choices to make professional plots without any hassle.

3
Pick your starting point
📊
Use your data

Share your numbers and describe the kind of chart you dream of.

🖼️
Copy from image

Upload a snapshot of a chart from a paper to recreate it perfectly.

4
✨ Watch the magic unfold

The tool instantly crafts a stunning, publication-ready chart matching expert styles.

5
💾 Download your masterpiece

Save the crisp, beautiful image to use in your document or slide.

🎉 Impress everyone

Your charts now look pro-level, making your ideas shine like a research star!

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Star Growth

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AI-Generated Review

What is paper-plot-skills?

This Python repo delivers ready-to-run scripts for crafting publication-quality plots straight from data or images, mimicking styles from top ML papers like SPICE, DoRA, and SiameseNorm. Drop your numbers into bar charts with hatches, radar diagrams, broken-axis scatters, or even class-wise IoU tables, and output crisp 300 DPI PNGs tuned for LaTeX. It's built as "skills" for GitHub integrations like skills github anthropic, skills github claude code, and skills github copilot vscode/cli, letting AI agents generate paper plots on demand.

Why is it gaining traction?

Unlike generic Matplotlib templates, these nail exact paper aesthetics—serif fonts, custom grids, insets, value annotations—saving hours of tweaking. Developers grab it for the plug-and-play YAML prompts that hook into skills github openclaw or skills github copilot, turning vague "plot my results" into pro figures. Zero setup beyond Python means instant wins for experiment viz.

Who should use this?

ML researchers rushing paper deadlines who hate fiddling with plot styles. Data scientists plotting ablations, scaling curves, or t-SNEs for arXiv submissions. AI tool builders extending skills github repo or skills github pages with plot-from-data/image capabilities.

Verdict

Solid starter kit for paper plot python skills at 43 stars, but 0.7% credibility score flags it's early—light docs, no tests. Fork and adapt if you need these styles; skip for production pipelines.

(187 words)

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