That's certainly true - while nose deep in working on this it's easy to forget that the goal is for the script to provide a good model for speculative worlds - and so the input data for such applications will probably be a bit 'cleaner' in the sense that it'll probably be closer to having the two extremes for everywhere, rather than a time snapshot that catches temperature/precipitation extremes for many places but not actually all.

Using the F aridity category for all pixels that have the same temperature in both input datasets gives the following result (after I toned down the top precipitation estimate to 300mm):
earthTest17.png

Or, using the W category as alternatively suggested in those same cases:
earthTest18.png

In practice the metric of 'same temperature in both seasons' will probably only hit equatorial regions, polar regions, and maybe a few other anomalous spots, and all the E climates are exempted from aridity checks already in my script - but it does still seem a kinda iffy way to check. I could restrict the assessment only to climates that would fall into A barring potential aridity and have the same temperature in both seasons, if that seems like it would be a better representation of equatorial climates where precipitation in either part of the year would have relatively equivalent impact on vegetation growth (although as Azélor mentioned this concern might apply to other regions where temperature has very little seasonal variation, where they exist besides equatorial zones).

Once I've set my script up to use configurable input color profiles it shouldn't be too hard to give an extra precipitation category a shot for very-dry-dry-season Am detection and so on.