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DataPython

Academic Plotting

by OpenRaiser

Academic Plotting is a Data skill for Claude Code, published by OpenRaiser in NanoResearch.

1.4K stars95 forkson OpenRaiser/NanoResearchAdded 2026/08/19Repository updated 2026/05/26
View source on GitHubDownload repo ZIP
agent-skillsagentsaiai-agentsai-scientistartificial-intelligenceautonomous-agentsautonomous-researchautoresearchclaude-codeclaude-skillsnanobotopenclaw
Install in seconds
Install Academic Plotting
Copy Academic Plotting into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.
terminal
npx degit https://github.com/OpenRaiser/NanoResearch/tree/main/skills/vendor-ai-research/academic-plotting ~/.claude/skills/academic-plotting

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/OpenRaiser/NanoResearch.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file
skills/vendor-ai-research/academic-plotting/SKILL.md in OpenRaiser/NanoResearch
Installs to
~/.claude/skills/academic-plotting
Collection
One of 16 skills cataloged from this repository
Category
Data — 668 skills

What Academic Plotting does

Academic Plotting generates publication-quality figures for ML papers from research context or experimental data. It creates architecture diagrams via Gemini and data-driven charts via matplotlib/seaborn, auto-selecting chart types and highlighting key results.

Academic Plotting is cataloged under Data on DirSkills. Academic Plotting comes from a repository tagged agent-skills, agents, ai, ai-agents and ai-scientist.

Documentation

README

Academic Plotting for ML Papers

Generate publication-quality figures for ML/AI conference papers. Two distinct workflows:

  1. Diagram figures (architecture, system design, workflows, pipelines) — AI image generation via Gemini
  2. Data figures (line charts, bar charts, scatter plots, heatmaps, ablations) — matplotlib/seaborn

When to Use Which Workflow

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Academic Plotting

  • What else does OpenRaiser publish alongside Academic Plotting?

    Academic Plotting is one of 16 skills that DirSkills catalogs from OpenRaiser/NanoResearch, the repository it ships in. Its siblings there include Autoresearch, Creative Thinking for Research and Hugging Face Accelerate. Each one is a separate skill with its own page in this directory, installs the same way Academic Plotting does, and is maintained by OpenRaiser in that same repository. The rest of the collection is listed on the OpenRaiser/NanoResearch page.

  • How does Academic Plotting compare to other Data skills?

    Academic Plotting ranks #406 by stars among the 668 Data skills in this catalog. The most-starred ones next to it are Benchmark Methodology, Jupyter Notebook and Solana. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Academic Plotting against them. Open each page to compare what they document and how they install.

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