In this work, we have proposed an iterative method of prompting we call PromptSMILES to achieve scaffold decoration and fragment linking (a.k.a. scaffold hopping) with CLMs in drug design. In combination with RL, we show that decoder-only CLMs can quickly adapt to the task of iterative prompting as well as maintain the ability to optimize arbitrary objectives. This was done by demonstrating comparable or improved performance for a variety of orthogonal approaches and different objectives. The ability to link more than two fragments is an extension to practical utility beyond other known methods to our knowledge. Crucially, this method does not require a bespoke architecture, bespoke grammar, or even retraining of a SMILES-based decoder-only model.