paper-figure

To generate publication-ready figures automatically, submit your experiment results in JSON or CSV format along with a figure plan. The skill processes this data to create data-driven plots, multi-panel figures, and vector-format images suitable for manuscript submission.

Yes, you can create LaTeX-ready tables and includegraphics snippets directly from CSV or JSON results. The skill outputs vector-format images alongside LaTeX include snippets, enabling seamless integration of figures and tables into your manuscript.

The best way to build multi-panel figures for a research manuscript is to provide a structured figure plan and your experiment data. The skill uses this plan to automatically render and align multiple panels into a single publication-quality vector image.

Yes, this approach works with Matplotlib and LaTeX workflows by rendering data-driven visualizations and exporting them as vector-format images. It also generates LaTeX include snippets to directly embed the rendered figures and tables into your documents.

Before automating figure generation, you need to prepare your experiment data in JSON or CSV format, a defined figure plan, and any existing figures you want to include. These inputs allow the skill to render publication-quality outputs and verify figure quality before submission.

Automating visualization reduces manual errors in manuscript preparation by programmatically generating plots and LaTeX tables from structured experiment data. This data-driven workflow ensures consistent formatting and accurate data mapping without manual chart adjustments.