Is any feed-forward neural network a composable function?
I suppose you could write $ h\circ [g\circ f\ |\ f]$ if you argue that matrix augmentation is itself a multivariate function.
But to avoid pedantic arguments, you could use multivariate function composition (although it is uglier).
Define a multivariate concatenate function for column vectors:
$ c(\vec{x_1},\vec{x_2},...,\vec{x_n})=\left[
\begin{matrix}
\vec{x_1} \\ \vec{x_2} \\ \vdots \\ \vec{x_n}
\end{matrix}
\right]$
In a network $f\rightarrow g\rightarrow h$ having skip connection $f\rightarrow h$, you could then write: $ h\circ c|_{g\circ f,f}$.