Comprehensive figure system for food & nutrition manuscripts: analyzes the user's data, recommends the best figure(s) to make, then produces submission-grade graphics in Python or R at the target journal's spec. Handles all common scientific figure types (bar/box/violin, line/kinetic, scatter/regression, Bland–Altman, radar/sensory, chromatograms, TPA/rheology, dose–response, survival, PCA/PLS-DA, heatmaps/clustering, forest, microscopy plates, multi-panel). Use to make, create, design, revise, audit, or recommend figures/charts/plots for a food-science paper, or to work out what to plot from a dataset. If Python or R isn't chosen, ask once and remember it. Triggers: make a figure, create a figure, design a figure, what figure should I make, recommend a chart, plot my data, analyze my data and plot it, chart my results, food science figure, journal figure, scientific plotting, data visualization for a manuscript.
How to install food-figure?
pangenomeai/academic-skills-food-nutrition/food-figure
$npx -y skills add pangenomeai/academic-skills-food-nutrition --skill food-figureInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/pangenomeai/academic-skills-food-nutrition" --skill "pangenomeai/academic-skills-food-nutrition/food-figure"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/pangenomeai/academic-skills-food-nutrition" that are relevant to the current task. Run `npx skills add "https://github.com/pangenomeai/academic-skills-food-nutrition"` and select the relevant skills, then follow their instructions.
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