Mathodology Figure Presets

by sweetcornna

Mathodology Figure Presets is a Data skill for Claude Code, published by sweetcornna in mathodology.

179 stars9 forkson sweetcornna/mathodologyAdded 2026/09/07+18% in starsRepository updated 2026/09/07

View source on GitHub Download repo ZIP

agent-skillsai-codingclaude-codecodex

Install in seconds

Install Mathodology Figure Presets

Copy Mathodology Figure Presets 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/sweetcornna/mathodology/tree/main/.claude/skills/mathodology-figure-presets ~/.claude/skills/mathodology-figure-presets

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/sweetcornna/mathodology.git

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

In this catalog

Source file: .claude/skills/mathodology-figure-presets/SKILL.md in sweetcornna/mathodology
Installs to: ~/.claude/skills/mathodology-figure-presets
Collection: One of 8 skills cataloged from this repository
Category: Data — 796 skills

What Mathodology Figure Presets does

Mathodology Figure Presets helps choose, design, generate, and review scientific figures, modeling charts, and paper illustrations. Use it for data-driven figure work, especially when adapting templates or checking publication-ready output.

Mathodology Figure Presets is cataloged under Data on DirSkills. Mathodology Figure Presets comes from a repository tagged agent-skills, ai-coding, claude-code and codex.

Documentation

README

Excerpt

Mathodology Scientific Figure Presets

Choose a figure from the question the reader needs to answer. Complex figures are useful when their panels expose related evidence; complexity itself is not a quality measure. Use actual data and the user's paper language.

Agent-facing guidance

Read default figure guidance when starting figure work or briefing another agent. It is the canonical reusable instruction: select a code template, fill real data, run it and inspect the resulting PNG/PDF. Use it as adaptable guidance, not a fixed pipeline.

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

Frequently asked about Mathodology Figure Presets

What else does sweetcornna publish alongside Mathodology Figure Presets?
Mathodology Figure Presets is one of 8 skills that DirSkills catalogs from sweetcornna/mathodology, the repository it ships in. Its siblings there include Mathodology Award Gates, Mathodology Evidence Search and Mathodology Modeling Companion. Each one is a separate skill with its own page in this directory, installs the same way Mathodology Figure Presets does, and is maintained by sweetcornna in that same repository. The rest of the collection is listed on the sweetcornna/mathodology page.
How does Mathodology Figure Presets compare to other Data skills?
Mathodology Figure Presets ranks #735 by stars among the 796 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 Mathodology Figure Presets against them. Open each page to compare what they document and how they install.