paper-plot-skills
paper-plot-skills is an AI-powered toolkit designed to streamline the reproduction and creation of academic figure charts found in top-tier conference papers. It addresses the repetitive nature of academic plotting by systematically extracting style parameters from nine real-world research figures, covering diverse chart types including bar charts, line plots with confidence intervals or insets, cluster scatter plots, and radar charts. The toolkit offers two primary workflows to simplify visualization tasks. The plot-from-data function allows users to select a pre-defined style template and input their own data to automatically generate publication-ready images at 300 DPI. The plot-from-image capability enables users to upload a screenshot of an existing chart, after which the system analyzes specific visual elements such as aspect ratio, font styles, and color schemes to automatically generate the corresponding Matplotlib script for exact reproduction. By providing these reusable style configurations, the so