| name | scientific-visualization |
| description | Publication-quality chart patterns for agentsociety-analysis Stage 4 refine — Okabe-Ito palettes, seaborn CI bands, small multiples, error bars, grayscale-safe encoding. Use when writing run-code chart scripts or reviewing chart QA failures. |
Scientific Visualization (bundled support)
Active only during agentsociety-analysis explore/refine/produce. Does not replace figure contracts or harness gates.
When to read
- Writing
charts/chart_NN_*.py via run-code
- Chart failed squint test or
validate-chart
- User asks for better-looking or clearer plots
Read order
references/charts.mdreferences/chart-recipes.mdassets/chart_scaffold.reference.pyreferences/api.md
Absorbed sources (patterns only — no external deps required)
| Source | Absorbed |
|---|
| K-Dense scientific-visualization | Okabe-Ito, CI/error bars, multi-panel labels, grayscale test |
| seaborn | set_theme(ticks, paper, colorblind), lineplot CI, boxplot+stripplot |
| Observable Plot | Defaults-first workflow, faceting, shared scales |
| Tufte | Small multiples, chart junk removal |
| Cursor canvas | Mandatory metric titles, axis units, source in caption |
AgentSociety overrides
- English-only legend text
- matplotlib
Agg required
- Simulation caveats — no overstated significance
- Semantic palette locked per condition across report
- PNG in
assets/ required; interactive HTML optional
Quick invoke
Copy scaffold → pick recipe letter (A–G) → fill SQL/pandas → save_chart_bundle → rubric → compose-figure if needed.
