  There has been significant recent interest in harnessing LLMs to control
software systems through multi-step reasoning, planning and tool-usage. While
some promising results have been obtained, application to specific domains
raises several general issues including the control of specialized domain
tools, the lack of existing datasets for training and evaluation, and the
non-triviality of automated system evaluation and improvement. In this paper,
we present a case-study where we examine these issues in the context of a
specific domain. Specifically, we present an automated math visualizer and
solver system for mathematical pedagogy. The system orchestrates mathematical
solvers and math graphing tools to produce accurate visualizations from simple
natural language commands. We describe the creation of specialized data-sets,
and also develop an auto-evaluator to easily evaluate the outputs of our system
by comparing them to ground-truth expressions. We have open sourced the
data-sets and code for the proposed system.
