Although this solution can streamline the calculation and scripting process for replicating a literature method, it relies on human intervention for prompt engineering, XML file saving, error correction and manual reagent addition during experiment. Some key parameters, such as stirring rate and ramping rate are sometimes not addressed in the literature and may require users' judgement to edit before or after importing XML files to iControl. The XML generation accuracy also depends on the operation mapping rules in prompt 2, where new rules need to be established for the addition of new workups or operations. Due to the hardware constraints, such as temperature range, stirring rate limit and vessel capacity, it's important yet challenging for LLMs to design experiments that strictly adhere to these rules. Additionally, the response may encounter an unexpected pause due to high server load or token limit, potentially requiring a "continue" prompt to resume the generation. It's worth noting that GPT performance can vary across different releases, and its behaviour may evolve over time.