A team runs an evaluation on their RAG-based customer support assistant. Using an evaluation framework, they observe that the 'context recall' metric is high (retrieved chunks reliably contain the information needed to answer), but the 'answer relevance' metric is low (generated responses often drift off-topic or fail to directly address the user's question). The retrieval pipeline appears healthy. Which action most directly targets the observed problem?