Individual skill
paper-figures
Use this skill to produce standalone, publication-ready PNG graphics and reproducible matplotlib scripts from tabular data (CSVs or DataFrames). It renders numerical data into formal scientific visualizations—including scatter, line, bar, pie, ring, bubble, tornado, KDE, violin, box, heatmap, histogram, and area charts, plus composite multi-panel figures that combine these types in a single image—for scholarly manuscripts. Only trigger when the final deliverable is an individual image file. Do not use for interactive dashboards or HTML-rendered outputs (Plotly, Streamlit, Quarto, Jupyter notebooks), nor when the request involves building a container document or presentation that includes charts (slide deck, conference poster). It is not for non-data conceptual illustrations like flowcharts, algorithm schematics, or process diagrams. This skill focuses on high-fidelity data rendering into final image files, not presentation design, document layout, or reverse-engineering code from existing screenshots.
skills/paper-figures/SKILL.md
Source commit 4889c2270af5f9a7658bb6a6709bf37040902006
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- Last checked
- Nov 4, 2026
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- 488
- Repository last updated
- Oct 27, 2026
- License
- Apache-2.0
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- skills Repository topic
- ai-agent Repository topic
- ai4science Repository topic
- vibe-research Repository topic
- core Declared skill tag
- figures Declared skill tag
- visualization Declared skill tag
- academic-writing Declared skill tag
- data Derived category
- research Derived category
- engineering Derived category
- design Derived category
- operations Derived category
- writing Derived category
- devops Derived category
- devops-containers Derived category
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SKILL.mdcore · 17,655 bytesSKILL.mdcore · 17,655 bytesSKILL.mdcore · 17,655 bytesreferences/chart-types.mddoc · 26,345 bytesreferences/publication-style.mddoc · 13,768 bytesrequirements.txtdoc · 30 bytesscripts/validate_figure.pyruns · 6,179 bytes
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# Paper Figures
A structured approach to producing publication-ready chart figures (PNG) from tabular data plus a natural-language description, using matplotlib.
## When to Use This Skill
- User provides a CSV / dataframe / inline data and asks for a chart
- User describes a target figure in words and wants it rendered
- User mentions "figure", "plot", "chart", "visualize", "render" for a paper or experiment
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## Inputs and Output