A new dynamic policy-learning method, HCL-GP, enhances LLM-based agents by enabling them to learn and reuse task components for improved planning efficiency and accuracy. This approach shows significant performance gains in both normal and challenging tasks, indicating a promising integration of classical planning with modern AI technologies.