We developed a two-step sequential prompt to convert literature text into a machine-readable format using ChatGPT-4. The first prompt transformed general experimental procedures/protocols from the literature to detailed, structured, and step-by-step procedures. The second prompt transcribed the output from the first prompt to machine readable tailored XML scripts that can communicate with iControl. This sequential prompt approach also allows for the integration of additional prompts in either step for potential correction in molecular weight lookup and syntax error fixing. The first prompt in Fig. ("prompt 1 -input" box) focused on breaking the translation task into three subtasks, called "Instructions" in the prompt. This was inspired by how human researchers replicate a literature procedure, specifically contextualization, calculation and step organization as the "prelab" exercises. The first instruction requires the LLM to retrieve information to comprehensively understand the reaction before performing calculations. The second instruction specifically asks to find the reagent phase and calculate the actual addition mass or volume, significantly improving the mathematical accuracy of the chemical amounts in the stepwise procedure. Lastly, the third subtask is to rewrite the protocol to a step-by-step procedure with detailed chemical quantities, breaking down an unstructured procedure into modular and explicit steps. This prompt can also be highly flexible, accommodating more specific requests, such as searching for the density for all liquid chemicals and displaying results in a markdown table, see examples in ESI † S3.2.