  Since ancient times, mechanical design aids have been developed to assist
human users, aimed at improving the efficiency and effectiveness of design.
However, even with the widespread use of contemporary Computer-Aided Design
(CAD) systems, there are still high learning costs, repetitive work, and other
challenges. In recent years, the rise of Large Language Models (LLMs) has
introduced new productivity opportunities to the field of mechanical design.
Yet, it remains unrealistic to rely on LLMs alone to complete mechanical design
tasks directly. Through a series of explorations, we propose a method for
constructing a comprehensive Mechanical Design Agent (MDA) by guiding LLM
learning. To verify the validity of our proposed method, we conducted a series
of experiments and presented relevant cases.
