What problem does it solve? Producing figures that meet journal formatting requirements (IEEE, Nature) is tedious: styles, sizes, labels, legends, and vector exports all need manual tuning, and visual defects like overlapping labels or clipped text are easy to miss. This Skill enforces a consistent construction and validation workflow so every figure is publication-ready. ## Core Features & Use Cases - Venue-aware styling: Applies SciencePlots style combinations (science, ieee, nature, notebook, grayscale) matched to the target venue. - Construction rules: Enforces axis labels with units, per-series legends, explicit figure sizes for single- or double-column layouts, and grayscale-safe series differentiation. - Visual validation: Runs the script, inspects the PNG preview for overlaps and boundary violations, and checks the PDF/SVG at 400% zoom for raster artifacts. - Use Case: You have simulation results for an IEEE Transactions paper. Ask for a double-column figure and receive a runnable Python script plus PDF and PNG outputs styled with ['science', 'ieee'] at 7.16 inches wide. ## Quick Start Plot my experiment results as an IEEE-style double-column figure with labeled axes, a legend, and both PDF and PNG outputs.
