You are correct, there is no analog to the choices for multiple comparisons as found in the Oneway platform.
The Wilcoxon test is an omnibus indicator of any difference. It is not specific to one parameter like the mean or variance. The plot at the top can help there, though. Parallel lines have the same variance or scale. Displaced lines have different mean or location. So if one agent is consistently completing their calls more quickly, their curve would shift to the left.
You also have the parameter point estimates and confidence intervals for each group (agent) for comparison, although that information is not the same as a multiple comparison test.
You can also use the profilers to extract information about each group. These answers are provided both as a point estimate and interval estimate.
I am not apologizing but simply recognizing that the methodology here comes from the reliability engineering field. The same methods were independently discovered in medical mortality and morbidity. The terminology, therefore, pertains to those fields but the methods are none the less relevant. It just requires a bit of translation. Sometimes it also requires reversing the goals. In reliability, an increasing hazard function is bad. In your case, though, it is good. It means that an event is more likely to happen. But in your case an event is not a failure, it is a completed call.
There are analogous methods for regression models with time to event data. So if you had covariates, you could include them in the model for lifetime and test them. There is a lot of flexibility here.
