From the specified distribution, for all $x \geqslant 1$ you have:
$$\begin{equation} \begin{aligned}
F_{X_{1:n}}(x) \equiv \mathbb{P}(X_{1:n} \leqslant x)
&= 1 - \mathbb{P}(X_{1:n} > x) \\[6pt]
&= 1 - \mathbb{P}(\min \{ X_1,...,X_n \} > x) \\[6pt]
&= 1 - \prod_{i=1}^n \mathbb{P}(X_i > x) \\[6pt]
&= 1 - \prod_{i=1}^n x^{-1} \\[6pt]
&= 1 - x^{-n}.
\end{aligned} \end{equation}$$
Hence, for all $x \geqslant 1$ you have:
$$\begin{equation} \begin{aligned}
F_{X_{1:n}^n}(x) \equiv \mathbb{P}(X_{1:n}^n \leqslant x)
&= \mathbb{P}(X_{1:n} \leqslant x^{1/n}) \\[6pt]
&= 1 - (x^{1/n})^{-n} \\[6pt]
&= 1 - x^{-1}.
\end{aligned} \end{equation}$$
This gives us back the original distribution of $X_i$. This distribution does not depend on $n$ so its limiting distribution is just the original distribution.
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