The COSPLAY framework enables LLM agents to retrieve and reuse structured skills from a learnable skill bank. This co-evolution approach targets the failure of models to maintain consistent decision-making over extended game episodes. It provides a mechanism for agents to discover and retain complex action chains. Practitioners can now better handle delayed rewards in interactive environments.