Probit marginal effects

I estimated the following probit model:

Code:

probit enrolled i.male##c.wealth i.male##c.oppcost hhsize

Following this, marginal effects are obtained as follows:

Code:

margins, dydx(*)
                        
        Delta-method
    dy/dx    Std. Err.    z    P>z    [95% Conf.    Interval]
wealth    .5586363    .0266069    21.00    0.000    .5064878    .6107849
1.male    -.0147905    .0069082    -2.14    0.032    -.0283303    -.0012507
oppcost    -.0159329    .0014443    -11.03    0.000    -.0187638    -.0131021
hhsize    -.0075958    .0019605    -3.87    0.000    -.0114383    -.0037534

Marginal effects of the interaction term male*wealth is obtained as follows

Code:

. margins male, dydx(wealth) pwcompare
   
Contrast Delta-method    Unadjusted
dy/dx   Std. Err.    [95% Conf. Interval]
wealth           
male 
1 vs 0     .1057078   .0486557    .0103444    .2010713

A referee states that 'the effect of being male should include main effects plus interactions, evaluated at the mean values of the variables with which 'male' is interacted'. What extra insight would this offer? How do I interpret the result below assuming this is how to evaluate at the mean values?

Code:

margins male, dydx(wealth) at(wealth oppcost)    vsquish

Average marginal effects                        Number of    obs     =    12,740
Model VCE    : OIM

Expression   : Pr(enrolled), predict()
dy/dx w.r.t. : wealth
at           : wealth              =      .54912 (mean)
oppcost        =    2.853002 (mean)

Delta-method
dy/dx   Std. Err.      z    P>z    [95% Conf.    Interval]
        
wealth           
male 
0     .5653815   .0406956    13.89   0.000    .4856197    .6451434
1     .7143289   .0430323    16.60   0.000    .6299872    .7986706