The relevance of neutral versus niche-based community assembly rules (i.e. the processes sorting species present in a larger geographical region into local communities) remains to be demonstrated in ecology and biogeography. To attempt to do this, a number of complex null models are increasingly being used that compare observed community functional diversity (FD, i.e. the extent of trait dissimilarity between coexisting species) with randomly simulated FD. However, little is known about the performance of these null models in detecting non-neutral community assembly rules such as trait convergence and divergence of communities (supposedly revealing habitat selection and limiting similarity, respectively). Here, using both simulated and field communities, I show that assembly rule detection varies systematically with the magnitude of the observed FD, so that these null models do not really succeed in breaking down the observed functional relationships between species. This is a particular concern, making detection of community assembly dependent on: (1) the pool of samples considered, and (2) the capacity of observed FD to correctly discriminate these rules. Null models should be more thoroughly described and validated before being considered as a magic wand to reveal assembly patterns.