The paper describes an approach for the quality dependent reconstruction of building facades using 3D point clouds from mobile terrestrial laser scanning and coarse building models. Due to changing viewing conditions such measurements frequently suffer from different point densities at the respective building facades. In order to support the automatic generation of facade structure in regions where no or only limited LiDAR measurements are available, a quality dependent processing is implemented. For this purpose, facades are reconstructed at areas of sufficient LiDAR point densities in a first processing step. Based on this reconstruction, rules are derived automatically, which together with the respective facade elements constitute a so-called facade grammar. This grammar holds all the information that is necessary to reconstruct facades in the style of the given building. Thus, it can be used as knowledge base in order to improve and complete facade reconstructions at areas of limited sensor data. Even for parts where no LiDAR measurements are available at all synthetic facade structures can be hypothesized providing detailed building geometry.