Recognizing these current limitations in text-to-procedure transcription and challenges in local SDLs execution, we aim to create an easy-to-use LLM prompt set for literature-toprocedure execution on an off-the-shelf automated laboratory reactor (ALR; Fig ). We selected the Mettler Toledo (MT) EasyMax because its software provides a user-friendly experimental design interface (iControl) and automatic design import from Extensible Markup Language (XML) (iC Data Center). We used ChatGPT-4 web-version to facilitate a no-code chemical protocol-to-procedure transcription, making it easy to be adopted by chemists with no coding expertise. We demonstrated the capability of this approach with three synthetic methods from the literature: 1) a detailed nucleophilic aromatic substitution reaction (SNAr) protocol; 2) a general hydrazine synthesis procedure and 3) an autonomous Curtius rearrangement monitoring protocol, showcasing different use case scenarios. Our two-prompt approach first transforms the literature protocol into a detailed stepwise procedure and subsequently to machine-executable XML scripts that communicated with MT EasyMax reactor. We further examined the generation robustness in length limits and accuracy as well as the code generation transferability in Python-based SDLs.