For the structure prediction of MOFs and related crystalline framework materials we have proposed the Reversed Topological Approach (RTA), where the default embedding of a topology is used as a blueprint. The optimal rotational insertion of the building blocks (BBs) at the fixed vertex positions of the blueprint is performed by minimizing the target function of the average angle deviation (AAD). Here we extend this idea by pre-optimizing the maximum symmetry embedding of a topology in order to minimize the overall mean AAD for the given set of BBs. By this fast and essentially parameter-free topoFF method, the vertex positions and cell parameters of the blueprint are further optimized in order to fit the structural needs of the BBs, which speeds up the overall search for the most energetically favorable structure. In addition, different topologies can be ranked in a quantitative and intuitive way. The definition and implementation of topoFF is explained and its application for the RTA-based structure prediction of MOFs is demonstrated with a number of instructive examples.