Modified cyclodextrins (CDs) are cyclic oligosaccharides with many applications in drug delivery, catalysis, and as active pharmaceutical ingredients. In general, they exist as distributions of structurally diverse molecules rather than single-isomer compounds. Their performance depends on the number of glucopyranose units (GPUs), and the type, number, and position of chemical substitutions in their hydroxyl groups. Effectively targeting individual species within these distributions is essential for optimizing CDs for specific applications. Computational techniques can generate large datasets to AI-driven structural optimization, but the absence of a standardized nomenclature system for modified CDs presents a major barrier to progress in this direction. This lack of consensus limits effective communication, data sharing, automation, and collaboration. To address this, a clear and extensible nomenclature for modified CDs is proposed. In this framework, GPUs are treated like amino-acid residues, with unsubstituted GPUs as reference building-blocks and substituted ones considered as mutations. This approach precisely defines substitution types and patterns, resolves cyclic permutation ambiguities, and offers versatility for both simple and complex modifications, including chiral center alterations and covalently linked CD oligomers. By introducing this standardized nomenclature, we aim to enhance molecular design, improve reproducibility, and streamline both experimental and computational research in the CD field.