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DataPython

Food Figure

by PangenomeAI

Food Figure is a Data skill for Claude Code, published by PangenomeAI in academic-skills-food-nutrition.

16 stars1 forkson PangenomeAI/academic-skills-food-nutritionAdded 2026/07/16Repository updated 2026/07/17
academic-writingai-agentsanthropicclaude-codeclaude-skillscodexfoodfood-sciencefood-science-innovationfood-technologyliterature-reviewllmmeta-analysisnutritionnutrition-sciencepeer-reviewresearch-toolsscholarly-publishingscientific-figuressystematic-review
Install in seconds
Install Food Figure
Copy Food Figure 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/PangenomeAI/academic-skills-food-nutrition/tree/main/food-figure ~/.claude/skills/food-figure

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

Without Node.js

git clone https://github.com/PangenomeAI/academic-skills-food-nutrition.git

Clones the whole repository, then copy the skillโ€™s own directory into your skills folder yourself.

In this catalog

Source file
food-figure/SKILL.md in PangenomeAI/academic-skills-food-nutrition
Installs to
~/.claude/skills/food-figure
Collection
One of 41 skills cataloged from this repository
Category
Data โ€” 812 skills

What Food Figure does

Analyzes data and produces submission-ready figures for food and nutrition science manuscripts, supporting Python or R export at journal specifications.

Food Figure is cataloged under Data on DirSkills. Food Figure comes from a repository tagged academic-writing, ai-agents, anthropic, claude-code and claude-skills.

Documentation

README

Food-Figure โ€” Data-Driven Figure System for Food & Nutrition Science

Turn a dataset (or a described result) into the right submission-grade figure. The chart serves the scientific logic; polish is subordinate to making the core conclusion clear, defensible, and reviewable. Original work; architecture informed by open community figure skills (see the repo README Acknowledgements).

Load reference files as needed (progressive disclosure) โ€” don't read them all up front. The map is in the frontmatter references list.

Workflow

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

Frequently asked about Food Figure

  • What else does PangenomeAI publish alongside Food Figure?

    Food Figure is one of 41 skills that DirSkills catalogs from PangenomeAI/academic-skills-food-nutrition, the repository it ships in. Its siblings there include AAAS Science Family, Agri Deep Research and Agri Pipeline. Each one is a separate skill with its own page in this directory, installs the same way Food Figure does, and is maintained by PangenomeAI in that same repository. The rest of the collection is listed on the PangenomeAI/academic-skills-food-nutrition page.

  • How does Food Figure compare to other Data skills?

    Food Figure ranks #803 by stars among the 812 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 Food Figure against them. Open each page to compare what they document and how they install.

More from PangenomeAI/academic-skills-food-nutrition

Food Figure is one of 41 skills cataloged on DirSkills from PangenomeAI/academic-skills-food-nutrition.

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Agri Pipeline

Orchestrates the complete agricultural research-to-publication workflow, from journal selection and research to writing, figures, peer review, and final manuscript. Use when you want end-to-end management of an agricultural paper.
Automation
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Agri Ppt

Agri Ppt turns agricultural reports, manuscripts, and evidence briefs into fully editable PowerPoint decks with native text, tables, figures, and speaker notes. It is used when making slides from agronomy, soil science, horticulture, or other agricultural research sources.
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253
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Agri-Paper

Assists in writing, revising, and formatting agricultural science manuscripts using a multi-agent system that handles literature, statistics, figures, and journal-specific reporting standards.
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161
๐ŸŒพ
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Agri-Research

Conducts comprehensive literature and evidence synthesis for agricultural science, acting as a senior agricultural scientist. Use for in-depth research, literature reviews, evidence briefs, or systematic reviews.
AI Engineering
161