  We report the results of $EasyCritics$, a fully automated algorithm for the
efficient search of strong-lensing (SL) regions in wide-field surveys, applied
to the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS). By using only
the photometric information of the brightest elliptical galaxies distributed
over a wide redshift range ($\smash{0.2 \lesssim z \lesssim 0.9}$) and without
requiring the identification of arcs, our algorithm produces lensing potential
models and catalogs of critical curves of the entire survey area. We explore
several parameter set configurations in order to test the efficiency of our
approach. In a specific configuration, $EasyCritics$ generates only $\sim1200$
possibly super-critical regions in the CFHTLS area, drastically reducing the
effective area for inspection from $154$ sq. deg to $\sim0.623$ sq. deg, $i.e.$
by more than two orders of magnitude. Among the pre-selected SL regions, we
identify 32 of the 44 previously known lenses on the group and cluster scale,
and discover 9 new promising lens candidates. The detection rate can be easily
improved to $\sim82\%$ by a simple modification in the parameter set, but at
the expense of increasing the total number of possible SL candidates. Note that
$EasyCritics$ is fully complementary to other arc-finders since we characterize
lenses instead of directly identifying arcs. Although future comparisons
against numerical simulations are required for fully assessing the efficiency
of $EasyCritics$, the algorithm seems very promising for upcoming surveys
covering $\smash{10^{4}}$ sq. deg, such as the $Euclid$ mission and $LSST$,
where the pre-selection of candidates for any kind of SL analysis will be
indispensable due to the expected enormous data volume.
