Individual skill
food-figure
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.
food-figure/SKILL.md
Source commit 01b2158a48408a8d0e56238c04075080c793d53c
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- Not checked yet
- Last checked
- Nov 11, 2026
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Repository context
- Repository stars (not skill ratings)
- 43
- Repository last updated
- Aug 31, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- academic-writing Repository topic
- ai-agents Repository topic
- anthropic Repository topic
- claude-code Repository topic
- claude-skills Repository topic
- codex Repository topic
- food-science Repository topic
- food-technology Repository topic
- literature-review Repository topic
- llm Repository topic
- data Derived category
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Browse files
SKILL.mdcore · 8,363 bytesassets/publication.mplstyleasset · 1,452 bytesexamples/gallery/README.mddoc · 2,250 bytesexamples/gallery/ai-image-test.mddoc · 1,767 bytesexamples/gallery/captions.mddoc · 4,197 bytesexamples/gallery/data/active_packaging_dose_response.csvasset · 740 bytesexamples/gallery/data/active_packaging_material.csvasset · 7,262 bytesexamples/gallery/data/active_packaging_storage.csvasset · 8,236 bytesexamples/gallery/data/method_calibration_standards.csvasset · 614 bytesexamples/gallery/data/method_paired_measurements.csvasset · 5,324 bytesexamples/gallery/data/method_reaction_profiles.csvasset · 1,593 bytesexamples/gallery/data/method_recovery_precision.csvasset · 3,102 bytesexamples/gallery/data/method_robustness_matrix.csvasset · 669 bytesexamples/gallery/data/probiotic_challenge_survival.csvasset · 6,670 bytesexamples/gallery/data/probiotic_encapsulation_properties.csvasset · 372 bytesexamples/gallery/data/probiotic_storage_kinetics.csvasset · 9,766 bytesexamples/gallery/data/sensory_overall_liking.csvasset · 5,222 bytesexamples/gallery/data/sensory_panel_ratings.csvasset · 34,959 bytesexamples/gallery/figures/fig1_active_packaging.pdfasset · 54,477 bytesexamples/gallery/figures/fig1_active_packaging.pngasset · 1,506,049 bytesexamples/gallery/figures/fig2_probiotic_storage_kinetics.pdfasset · 60,869 bytesexamples/gallery/figures/fig2_probiotic_storage_kinetics.pngasset · 1,420,270 bytesexamples/gallery/figures/fig3_sensory_radar.pdfasset · 62,684 bytesexamples/gallery/figures/fig3_sensory_radar.pngasset · 1,347,485 bytesexamples/gallery/figures/fig4_method_validation_and_evidence.pdfasset · 44,806 bytesexamples/gallery/figures/fig4_method_validation_and_evidence.pngasset · 1,574,249 bytesexamples/gallery/render_gallery.Rruns · 29,648 bytesexamples/gallery/trace-cards.yamlasset · 4,938 bytesexamples/python_food_figures.pyruns · 7,236 bytesexamples/r_food_figures.Rruns · 4,888 bytesreferences/ai-image-generation.mddoc · 5,823 bytesreferences/chart-types.mddoc · 3,140 bytesreferences/color-palettes.mddoc · 2,223 bytesreferences/data-to-figure.mddoc · 2,665 bytesreferences/design-principles.mddoc · 1,707 bytesreferences/experimental-flow.mddoc · 3,088 bytesreferences/figure-contract.mddoc · 1,076 bytesreferences/figure-provenance.mddoc · 2,485 bytesreferences/figure-story-design.mddoc · 3,826 bytesreferences/food-recipes.mddoc · 2,505 bytesreferences/journal-specs.mddoc · 1,496 bytesreferences/python-guide.mddoc · 4,758 bytesreferences/qa-checklist.mddoc · 2,111 bytesreferences/r-guide.mddoc · 4,416 bytesscripts/analyze_data.pyruns · 9,129 bytesscripts/backend_pref.pyruns · 2,831 bytes
Read excerpt
# Food-Figure — 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) — don't read them all
up front. The map is in the frontmatter `references` list.
## Workflow
```mermaid
flowchart TD