COSMO-Agent is a new reinforcement learning framework designed to optimize the CAD-CAE process by bridging the semantic gap between design and simulation. It enhances the capabilities of small open-source LLMs, outperforming larger models in terms of feasibility and efficiency for constraint-driven design tasks.