marginal effects in glm's

Hi,

I wonder if there is a function in (some package of) R which computes 
marginal effects of the variables in a glm, say, for concretness, a 
probit model. By marginal effects of the covariate x_j I mean

d P(y=1 | x),

which is approx

g(xB)B_j dx_j

where g is the pdf of the normal distribution, x is the vector of 
covariates (at some points, say, the mean values) and B is the estimated 
vector of coefficients. Of course, it isn't difficult to write such a 
function, but that's exactly why I find it strange the fact that I 
didn't find it.

Also, I couldn't find a function which gives the percent correctly 
predicted for some threshold, say, .5 (something usually reported). Any 
suggestions where to look for these two functions?

Many thanks,

Dimitri