What problem does it solve? Building a publication-grade multi-panel figure requires coordinating panel planning, consistent styling, layout review, and provenance tracking, which is error-prone when done ad hoc across separate scripts. ## Core Features & Use Cases - Panel Planning: Draft a structured panel plan with labels, chart types, data sources, annotations, and the claim each panel supports. - Consistent Styling: Apply the figure-style skill across panels so axes, fonts, and color mappings stay uniform, then assemble with patchwork or cowplot over ggplot2. - Review and Provenance: Render, inspect, and revise for label collisions and readability, then save the figure, source data, generation code, caption, and a provenance sidecar. - Use Case: Given a regression result and supporting diagnostics in an R/Quarto project, plan a three-panel figure, style each plot consistently, compose the composite in one code chunk with a caption and cross-reference, and export a vector PDF for print. ## Quick Start Compose a multi-panel figure from my analysis results that argues a single claim, with consistent styling and a saved provenance sidecar.
