AGORA introduces a novel step-level compression method for large language model (LLM) agents, addressing the limitations of existing token-level compressors that fail to retain critical action semantics. This new approach significantly improves performance retention while achieving adaptive compression, marking a potential breakthrough in LLM efficiency and usability.