I have found $2$ references.
- Variational Analysis by Rockafellar/Wets.
9.1 Definition (Lipschitz continuity and strict continuity). Let $F$ be a singlevalued mapping defined on a set $D \subset \mathbb{R}^n$, with values in $\mathbb{R}^m$. Let $X \subset D$. The map $F$ is strictly continuous at $\bar{x}$ (without mention of $X$ ) if $\bar{x} \in \operatorname{int} D$ and the value
$$
\operatorname{lip} F(\bar{x}):=\limsup _{\substack{x, x^{\prime} \rightarrow \bar{x} \\ x \neq x^{\prime}}} \frac{\left|F\left(x^{\prime}\right)-F(x)\right|}{\left|x^{\prime}-x\right|}
$$
is finite.
9.17 Definition (strict differentiability). A function $f: \mathbb{R}^n \rightarrow \overline{\mathbb{R}}$ is strictly differentiable at a point $\bar{x}$ if $f(\bar{x})$ is finite and there is a vector $v$, which will be the gradient $\nabla f(\bar{x})$, such that $f\left(x^{\prime}\right)=f(x)+\left\langle v, x^{\prime}-x\right\rangle+o\left(\left|x^{\prime}-x\right|\right)$, i.e.,
$$
\frac{f\left(x^{\prime}\right)-f(x)-\left\langle v, x^{\prime}-x\right\rangle}{\left|x^{\prime}-x\right|} \rightarrow 0 \text { as } x, x^{\prime} \rightarrow \bar{x} \text { with } x^{\prime} \neq x .
$$
10.10 Exercise (subgradients of Lipschitzian sums). If $f=f_1+f_2$ with $f_1$ strictly continuous at $\bar{x}$ while $f_2$ is lsc and proper with $f_2(\bar{x})$ finite, then
$$
\partial f(\bar{x}) \subset \partial f_1(\bar{x})+\partial f_2(\bar{x}), \quad \partial^{\infty} f(\bar{x}) \subset \partial^{\infty} f_2(\bar{x}) .
$$
If $f_1$ is strictly differentiable at $\bar{x}$, these inclusions hold as equations.
- Optimization and Nonsmooth Analysis by Clarke.
We shall say that $F$ admits a strict derivative at $x$, an element of $\mathcal{L}(X, Y)$ denoted $D_s F(x)$, provided that for each $v$, the following holds:
$$
\lim _{\substack{x^{\prime} \rightarrow x \\ t \downarrow 0}} \frac{F\left(x^{\prime}+t v\right)-F\left(x^{\prime}\right)}{t}=\left\langle D_s F(x), v\right\rangle,
$$
and provided the convergence is uniform for $v$ in compact sets. (This last condition is automatic if $F$ is Lipschitz near $x$ ). Note that ours is a "Hadamard-type strict derivative".
If $f_i(i=1,2, \ldots, n)$ is a finite family of functions each of which is Lipschitz near $x$, it follows easily that their sum $f=\sum f_i$ is also Lipschitz near $x$.
2.3.3 Proposition (Finite Sums)
$$
\partial\left(\sum f_i\right)(x) \subset \sum \partial f_i(x).
$$
Corollary 1 Equality holds in Proposition 2.3.3 if all but at most one of the functions $f_t$ are strictly differentiable at $x$.