The Complete Automated Classification of Astronomical Objects Tool (CACAO) was developed as part of the BREAKFAST SUITE of tools (Burkutean et al. in prep) to offer source detection, description and classification in wide-field radio astronomical images. CACAO took part in the first SKA Data Challenge and is currently being extended beyond the specifications of the latter in order to address a wider range of image morphological descriptions and classifiers. CACAO's code development is structured in such a way as to allow maximal flexibility for applications to real data as well as for future data challenges. The code is fully parallelized and written entirely in python relying on the python libraries numpy, scipy and astropy. This webpage gives a brief overview of the current CACAO specifications. If you would like to apply CACAO to your datasets or would like to have further information, please write to firstname.lastname@example.org and stay tuned for the CACAO publication.