Agree overall, but tf.eager doesn't have much to do with the rest of the list.

tf.contrib is just a module where user-contributed code was stored, which included both low-level constructs and higher level APIs. tf.estimator is an abstraction that is mostly used for productionizing models. tf.slim/tf.learn were indeed redundant with keras (a library developped externally), but were necessary steps before keras became part of tensorflow.