clmm Random slopes

I'm having trouble understanding random slopes in a clmm() model. We want to predict Exercise during behaviour with Exercise before behaviour (both categorical variables) with country as a random effect. So first my model was like this:

fm2 <- clmm(Ex_during ~ Ex_before + (1|Country), data=data6)
With this, I had no trouble understanding the random intercept, as this is well described in the Christensen CLMM Tutorial. The random intercept would represent the differences in the DV of each country.

However, in my opinion it would make sense to introduce Ex_before as a random slope (and this model shows a superior model fit) as we don't just want to take into account that countries differ in the dependent variable but also in the relation between the predictor and the dependent variable!

fm2.RS <- clmm(Ex_during ~ Ex_before + (Ex_before |Country), data=data6)

Now I get random effects for each country and each level of the predictor Ex_before. I plotted it, but I can not make sense of the values.

What do the values of the random effects in CLMM describe? Country specific Coefficients? But what does that mean?