A new approach aims to optimize prompts and batching techniques for minimal-edit grammatical error correction in large language models, addressing the issue of systematic overcorrections that reduce $F_{0.5}$ scores. This improvement is crucial as it enhances the accuracy and reliability of text generated by LLMs without过度纠正。