In my experience @rodrigo.constanzo is right. Also @rodrigo.constanzo has some great videos, many of which you can find on this discourse, and posts on this discourse that model the strategy of “knowing your data” by doing a lot of plotting, listening, and tweaking to really know what the audio analyses provide, what you care about as a listener/composer, and how to connect those two realities.
MFCCs tend to be a good general-purpose starting point. Also, it’s often not too much effort to do more analyses (spectral shape, pitch, loudness, etc.), then plot, listen, etc. and see what makes sense for you.
Something like this might get you going in that direction:
