Crafter: A Multi-Agent Harness for Editable Scientific Figures Generation from Diverse Inputs

Scientific figures are vital for communicating complex research, yet producing publication-quality illustrations remains labor-intensive. Existing automated systems each target a single figure type from text-only input, missing the diversity of types and conditions researchers actually need, and their raster outputs resist local revision. Since scientific figures are structured compositions of discrete semantic components, the localized error generators produce on such layouts demand not a stronger backbone but a harness. We instantiate this harness in two complementary systems:Crafter, a multi-agent harness for figure generation that generalizes across figure types and conditions without architectural changes, and CraftEditor, which converts raster outputs into editable SVGs. We introduce CraftBench, a benchmark spanning three figure types and four input conditions with human quality annotation. Experiments show that Crafter substantially outperforms standalone generators and agentic baselines on PaperBananaBench and CrafterBench, ablations confirm each component's contribution, and CraftEditor yields editable SVGs surpassing all baselines.