Extension to meta-GGA exchange–correlation functionals, as well as to functionals with more complex forms sitting on higher rungs of Jacob’s ladder, could be achieved with various degrees of difficulty. For example, meta-GGA functionals depend on at least three variables that cannot be decoupled (e.g. the density, its gradient, and the kinetic energy density), and therefore they require higher dimensional interpolations. The interpolation using multi‑dimensional grids and appropriate functions is not problematic, especially using available python libraries. A slightly more complicated case is the case of hybrid functionals (e.g. functionals that include a fraction of Hartree–Fock exchange), for which the parameter that represents the fraction of HF exchange could be encoded in the procedure, for example at the beginning of the sequence. For range-separated hybrid functionals, more complicated ad hoc procedure must be designed. However, since representing functionals with one parameter has no inherent benefit for DFT as a method, going beyond the simple proof-of-principle described above has very little scientific merit and is not explored further in this context. A more rewarding endeavor is the search for a procedure that does not rely on counting the number of parameters to evaluate the transferability of functionals, as presented in the next section.