The rapid urban growth poses a huge challenge in sustaining the quality of local environment and life characteristics in contemporary cities. There is a growing body of literature on sustainable cities, QoL, livability; yet a transparent and verifiable knowledge on its assessment at the urban scale is both limited and disparate. Very recently, the use of computational models, tools and indices has seen a sudden upsurge in QoL assessment at the city and sub-city level. This research, through an exhaustive review of scientific and policy literature postulates that despite promulgation of numerous and comprehensive indices and tools, yet these demonstrate a great deal of inconsistency and incomparability. This necessitates an investigation into what ought to be the preferred attributes/features of an ideal model, thereby demanding a systematic, transparent and objective appraisal of urban QoL assessment tools used worldwide. Addressing to the above objective, the research examines peer-reviewed papers to derive eight fundamental study criteria (type of dataset, scope or parameters, sample- coverage and unit, approach, technique, model type, interphase and application) that could typically characterizes such tool. It then reviews scientific and policy literature, open-access webpages on the internet to identify a first of its kind, exhaustive inventory of 26 urban QoL models and then critically evaluates these on the basis of the eight study criteria. The ensuing results bring to the fore a plethora of new, interesting and some inconvenient findings, most importantly that not even a single tool captures all the seven theoretical dimensions of QoL. Despite meant to evaluate quality in cities, only few tools conduct qualitative, subjective, bottom-up, GIS based simulation modeling that could effectively be put to use for more public and policy oriented applications. Lastly, the research demonstrates with credible evidence that a majority of tools/index continue to understand the city as a homogenous entity, with limited know-how on the variability of QoL at the neighbourhood level. © 2019, Springer Nature B.V.