Upwards of what d' values constitute "good" sensitivity?
There is no standard definition for a "good" value of d'. The index of sensitivity d' can be related to percent correct under certain conditions (unbiased observer, equal probability of signal and no signal trials, and a single observation). Under these conditions values of d' of 1, 1.5, 2, and 2.5 equate to a probability of correct of 0.69, 0.77, 0.84, and 0.89, respectively.

Historically, "threshold" was often defined as a probability of correct of 0.75. This is the midpoint of the psychometric function and in a yes/no task and the point with the steepest slope. With the transformed up-down method (Levitt, 1971) it is much easier to track a a probability of correct of 0.707 or 0.794, than a probability of correct of 0.75. These equate roughly to a d' of 1 and 1.5. Things got messier as people switched to 2-interval 2-AFC paradigms.

Another way to think about this is that the index of sensitivity d' is essentially the same thing as Cohen's d. Cohen (1988) proposed that values of Cohen's d of 0.2, 0.5, and 0.8 were small, medium, and large effects, respectively. Again, there is no obvious mapping of "good" onto small, medium, and large.