This study applied the mode of on-the-fly assembled multistage adaptive testing to cognitive diagnosis (CD-OMST). Several and several module assembly methods for CD-OMST were proposed and compared in terms of measurement precision, test security, and constrain management. The module assembly methods in the study included the maximum priority index method (MPI), the revised maximum priority index (RMPI), the weighted deviation model (WDM), and the two revised Monte Carlo methods (R1-MC, R2-MC). Simulation results showed that on the whole the CD-OMST performs well in that it not only has acceptable attribute pattern correct classification rates but also satisfies both statistical and nonstatistical constraints; the RMPI method was generally better than the MPI method, the R2-MC method was generally better than the R1-MC method, and the two revised Monte Carlo methods performed best in terms of test security and constraint management, whereas the RMPI and WDM methods worked best in terms of measurement precision. The study is not only expected to provide information about how to combine MST and CD using an on-the-fly method and how do these assembled methods in CD-OMST perform relative to each other but also offer guidance for practitioners to assemble modules in CD-OMST with both statistical and nonstatistical constraints.