The CHARM framework addresses cascading hallucination in agentic retrieval-augmented generation (RAG) systems, significantly improving error detection and mitigation in multi-step reasoning tasks. With an impressive cascade detection rate of 89.4%, CHARM enhances the reliability of AI outputs without requiring major architectural changes.