Verifiable Chemical Reasoning through Tool-Calling Agentic Workflow

Reasoning models have increasingly been used to perform complex tasks in open ended environments. A challenge facing such efforts is domain specific tuning often requiring large quantities of data and verifiability. We can construct a high-performance reasoning agentic workflow for chemistry that is a) verifiable and b) extensible through the use of tools. We further show that distilling the outputs of the resulting workflow into smaller models results in lighter workflows that are still performant.