This computationally efficient screening procedure successfully highlighted promising candidates for heteroleptic cage formation. Crucially, a large proportion of ligand combinations that did not form heteroleptic assemblies (i.e. true negatives) were identifiable and could reasonably be excluded. This low-cost approach can be run on a common laptop based only on UFF geometry optimisations of the ligand conformers. Conformer generation is achieved in minutes, whilst geometric matchings between conformers takes seconds. As such, this screening tool is viable for high-throughput analysis of large ligand libraries. The code for running this analysis has been made freely available, 37 only requiring ligand SMILES strings as input.