You don't get a full data dictionary with this dataset. Instead the explanation (from your link) is:
90 attributes, 12 = timbre average, 78 = timbre covariance
The first value is the year (target), ranging from 1922 to 2011.
Features extracted from the 'timbre' features from The Echo Nest API.
We take the average and covariance over all 'segments', each segment
being described by a 12-dimensional timbre vector.
This is basically features derived direct from the audio. This is typical for problems in signal analysis, and the UCI dataset has been cut down so that it is purely about matching audio summaries to year of production.
The data dictionary from the original MSD dataset shows much more metadata. There are 54 feature types, but actually thousands of features - each type can be repeated many times. The UCI subset is not only subset by row, but by columns too, and only uses some of the MSD data.