This is a community-wiki answer illustrating Iosif Pinelis's solution (with some simplifications).
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Setting. We will write $s_n = \sum_{k=1}^{n} x_k$, so that the recurrence relation takes the form
$$ x_{n+1} = x_n + \frac{n}{s_n}. \tag{RE} $$
Also, let $\alpha$ and $\beta$ by
$$ \alpha = \liminf_{n\to\infty} \frac{x_n}{\sqrt{n}}
\qquad\text{and}\qquad
\beta = \limsup_{n\to\infty} \frac{x_n}{\sqrt{n}}. $$
Our goal is to prove that $\alpha = \beta = \sqrt{3}$. To make use of these quantities, we will frequently utilize the following inequalities:
Lemma. Let $(a_n)$ be any sequence of real numbers, and let $p > 0$. Then
$$ \color{navy}{\liminf_{n\to\infty} \frac{a_n}{n^p}}
\geq \liminf_{n\to\infty} \frac{a_n - a_{n-1}}{pn^{p-1}} \tag{SC1} $$
and
$$ \color{navy}{\limsup_{n\to\infty} \frac{a_n}{n^p}}
\leq \limsup_{n\to\infty} \frac{a_n - a_{n-1}}{pn^{p-1}}. \tag{SC2} $$
Proof. This is an immediate consequence of the Stolz–Cesàro theorem together with the asymptotic formula $n^p - (n-1)^p \sim pn^{p-1}$.
Step 1. Since $(x_n)$ is increasing, we know that $s_n \leq n x_n$. Then by the lemma,
\begin{align*}
\alpha^2
= \liminf_{n\to\infty} \frac{x_n^2}{n}
&\geq \liminf_{n\to\infty} \left( x_{n+1}^2 - x_n^2 \right)
\tag*{by $\color{#2E8B57}{\text{(SC1)}}$} \\
&\geq \liminf_{n\to\infty} \frac{2nx_n}{s_n}
\tag*{by $\color{#2E8B57}{\text{(RE)}}$} \\
&\geq 2.
\tag*{$\because \ s_n \leq n x_n$}
\end{align*}
Now, by the Stolz–Cesàro theorem again,
\begin{align*}
\beta
= \limsup_{n\to\infty} \frac{x_n}{\sqrt{n}}
&\leq \limsup_{n\to\infty} \frac{x_{n+1} - x_n}{\frac{1}{2}n^{-1/2}}
\tag*{by $\color{#2E8B57}{\text{(SC2)}}$} \\
&= \limsup_{n\to\infty} \frac{2n^{3/2}}{s_n}
\tag*{by $\color{#2E8B57}{\text{(RE)}}$} \\
&= \left[ \liminf_{n\to\infty} \frac{s_n}{2n^{3/2}} \right]^{-1} \tag{1} \\
&\leq \left[ \liminf_{n\to\infty} \frac{x_n}{3\sqrt{n}} \right]^{-1}
= \frac{3}{\alpha}.
\tag*{by $\color{#2E8B57}{\text{(SC1)}}$}
\end{align*}
These altogether show that $0 < \alpha \leq \beta < \infty$.
(Remark. Starting from $\alpha$ and applying a similar argument as above, we can show that $\alpha \beta = 3$. However, this does not determine the value of $\alpha$ and $\beta$. So, we will not bother to prove this.)
Step 2. Using the recurrence relation $\color{#2E8B57}{\text{(RE)}}$, we find that
\begin{align*}
s_{n+1}^2 - 2s_n^2 + s_{n-1}^2
&= (s_n + x_{n+1})^2 - 2s_n^2 + (s_n - x_n)^2 \\
&= 2 s_n(x_{n+1} - x_n) + x_{n+1}^2 + x_n^2 \\
&= 2n + x_{n+1}^2 + x_n^2. \tag{2}
\end{align*}
Using this, we get
\begin{align*}
\liminf_{n\to\infty} \frac{s_n^2}{n^3}
&\geq \liminf_{n\to\infty} \frac{s_{n+1}^2 - s_n^2}{3n^2}
\tag*{by $\color{#2E8B57}{\text{(SC1)}}$} \\
&\geq \liminf_{n\to\infty} \frac{s_{n+1}^2 - 2s_n^2 + s_{n+1}^2}{6n}
\tag*{by $\color{#2E8B57}{\text{(SC1)}}$} \\
&\geq \frac{1}{3} + \frac{1}{6} \biggl( \liminf_{n\to\infty} \frac{x_{n+1}^2}{n} \biggr) + \frac{1}{6} \biggl( \liminf_{n\to\infty} \frac{x_n^2}{n} \biggr)
\tag*{by $\color{#2E8B57}{\text{(2)}}$} \\
&= \frac{1 + \alpha^2}{3}.
\end{align*}
Plugging this into $\color{#2E8B57}{\text{(1)}}$,
\begin{align*}
\beta
\leq \left[ \liminf_{n\to\infty} \frac{s_n}{2n^{3/2}} \right]^{-1}
\leq 2\sqrt{\frac{3}{1+\alpha^2}}. \tag{3}
\end{align*}
A similar calculation also shows that
$$ \alpha \geq 2\sqrt{\frac{3}{1+\beta^2}}. \tag{4} $$
Step 3. Define $f(x) = 2\sqrt{\frac{3}{1+x^2}}$, and note that $f$ is decreasing on $[0, \infty)$. So, using $\color{#2E8B57}{\text{(3)}}$ and $\color{#2E8B57}{\text{(4)}}$, we get
$$ \beta \leq f(\alpha) \implies f(f(\alpha)) \leq f(\beta)
\qquad\text{and}\qquad
\alpha \geq f(\beta) \implies f(\alpha) \leq f(f(\beta)) $$
and hence
$$ \beta \leq f(f(\beta)) \qquad\text{and}\qquad f(f(\alpha)) \leq \alpha. $$
It is not hard to check that these inequalities yield $\beta \leq \sqrt{3} \leq \alpha$:
So, using the obvious relation $\alpha \leq \beta$, we conclude that
$$ \sqrt{3} \leq \alpha \leq \beta \leq \sqrt{3} $$
and therefore $\alpha = \beta = \sqrt{3}$.
Best Answer
The following solution is a generalization of robjohn's answer to For a positive real sequence $(a_n)$ from exponent $p=2$ to arbitrary exponents $p > 1$.
The sequence $$ \frac{x_1+x_2+\cdots+x_n}{n} $$ is convergent and therefore bounded, let $K > 0$ be an upper bound.
Also (compare Suppose that a sequence is Cesaro summable. Prove....) $$ \frac{x_n}{n} = \frac{x_1+x_2+\cdots+x_{n-1}+x_n}{n} - \frac{n-1}{n} \cdot \frac{x_1+x_2+\cdots+x_{n-1}}{n-1} $$ converges to $a - 1 \cdot a = 0$.
Given $\epsilon > 0$ there is an index $n_0$ such that $$ \frac{x_n}{n} < c := \sqrt[p-1]{\frac{\epsilon}{2K}} $$ for $n \ge n_0$. It follows that for $n \ge n_0$ $$ \frac{1}{n^p} \sum_{k=n_0}^n x_k^p = \sum_{k=n_0}^n \left( \frac{x_k}{k} \right)^p \cdot \left( \frac kn\right)^p \le c^{p-1} \sum_{k=n_0}^n \frac{x_k}{k} \cdot \frac kn \\ = c^{p-1} \frac 1n \sum_{k=n_0}^n x_k \le c^{p-1} K = \frac 12 \epsilon\, . $$ Now choose $n_1 > n_0$ so large that $$ \frac{1}{n^p} \sum_{k=1}^{n_0-1} x_k^p < \frac 12 \epsilon $$ for $n \ge n_1$. Then $$ 0 \le \frac{1}{n^p} \sum_{k=1}^n x_k^p \le \epsilon $$ for $n \ge n_1$ and that proves
$$ \lim_{n \to \infty } \frac{1}{n^p} \sum_{k=1}^n x_k^p = 0 \, . $$