Nature Figure

Nature-style publication figure and scientific schematic workflow for Python or R, including figure intent, panel composition, annotations, reproducible export, and source-aware review. Use for submission figures, graphical abstracts, or method schematics.

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Nature Figure

Use scientific-visualization as the integrity baseline, then apply the target venue contract.

  1. Define the message of the figure in one sentence and list the data or source evidence supporting it.
  2. Plan panels as a coherent visual argument: overview, comparison, mechanism, validation, or limitation. Give each panel one job.
  3. Preserve raw values and analysis provenance. Keep a record of transformations, statistical annotations, units, color mapping, and export settings.
  4. Prefer vector output for diagrams and text; preserve raster resolution for images without implying that upsampling adds detail.
  5. Review visual hierarchy, color accessibility, font size, caption completeness, and claim strength at final size.

If a schematic is generated from prose, mark it as a conceptual illustration and do not present it as measured data. Do not copy third-party figure assets without a compatible license and attribution.

This is a ScanSci adaptation of the nature-figure workflow from Yuan1z0825/nature-skills.

rimagination/scansci-pi/tree/main/src/scansci_html/builtin_skill_assets/nature-figure commit 264d9e66d0

Frequently asked questions

npx skillmds@latest add rimagination/nature-figure