For what is worth, I was able to determine through numerical experiments, that Gretl uses the "Fisher-Pearson" formulas for calculating the skewness and excess kurtosis coefficients.

This essentially means that for the calculation of these coefficients, all sample means involved (even the sample variance/standard deviation) are calculated using the factor (1/n), and that no bias-correction terms appear.
I am writing this informatively - I have no settled opinion on which alternative formula should be preferred.

So

Skewness Coefficient (this version is usually denoted "g1")
Numerator: (1/n)(Σ(x_i - mean(X))^3)
Denominator : [(1/n) Σ(x_i - mean(X))^2]^(3/2)

(Excess) Kurtosis Coefficient
(this version is usually denoted "g2")
Numerator :
(1/n)(Σ(x_i - mean(X))^4)
Denominator : [(1/n) Σ[x_i - mean(X)]^2]^2

and we further subtract "3" after we calculate the ratio to obtain the "excess" over the kurtosis of the normal distribution.

References for the names and presentations of various alternatives

Joanes, D. N., & Gill, C. A. (1998). Comparing measures of sample skewness and kurtosis. Journal of the Royal Statistical Society: Series D (The Statistician), 47(1), 183-189.
Doane, D. P., & Seward, L. E. (2011). Measuring skewness: a forgotten statistic. Journal of Statistics Education, 19(2), 1-18.
Alecos Papadopoulos
Athens University of Economics and Business, Greece
Department of Economics
cell:+30-6945-378680
fax: +30-210-8259763
skype:alecos.papadopoulos
On 7/8/2014 19:00, gretl-users-request@lists.wfu.edu wrote:
Yes. I might just add that our measures are in agreement with those of the 
"moments" package for R, except that R gives total rather than excess 
kurtosis.

Allin Cottrell