$\textbf{Warning}$: The following approach is not the most efficient way of going about this—indeed, I probably wouldn't do this myself if I actually needed the answer. However, it has pedagogical value and presents a rare opportunity for me to share a cool bit of math. Without further adieu...
Let $\{\alpha_k\}_{k=1}^3$ be the roots of $f(x) = x^3 - x - 1$. Notice that $P(\alpha_1, \alpha_2, \alpha_3) = \alpha_1^6 + \alpha_2^6 + \alpha_3^6$ is a symmetric polynomial* in $3$ variables evaluated at the $\alpha_k$'s. It is a theorem** that any symmetric polynomial can be written as a polynomial in the elementary symmetric polynomials.
Let $\big\{e_k(x_1,x_2,x_3) \big\}_{k=1}^3$ be the collection of elementary symmetric polynomials in three variables. The above is saying that there exists a polynomial $Q \in \mathbb{Z}[x_1, x_2, x_3]$ such that $P(x_1, x_2, x_3) = Q\Big(e_1(x_1,x_2,x_3), \ e_2(x_1,x_2,x_3), \ e_3(x_1,x_2,x_3)\Big)$.
Now this looks like a mess, but the the elementary symmetric polynomials—evaluated at the $\alpha_k$'s—appear$^\dagger$ as the (signed) coefficients of $f$! Thus, if we can find the polynomial $Q$ above, then we can easily find the desired value $P(\alpha_1, \alpha_2, \alpha_3)$ because the right hand side of this evaluation will consist merely of the addition and multiplication of simple, already-known integers (see how robjohn got a clean natural number in his post?). To be explicit, we'll have:
$$\begin{align}
& e_1(\alpha_1, \alpha_2, \alpha_3) \ = \ 0 \qquad \ \ \text{ (the } x^2 \text{ coefficient)}\\
& e_2(\alpha_1, \alpha_2, \alpha_3) \ = \ -1 \\
& e_3(\alpha_1, \alpha_2, \alpha_3) \ = \ 1
\end{align}$$
Finding $Q$ may or may not be computationally difficult! It appears that Newton did find a recursion which writes symmetric polynomials of the form $\displaystyle \sum_{k=1}^n x_k^j$ for any $n, j \in \mathbb{N}$ in terms of elementary symmetric polynomials (of course, in this scenario, we have $n=3$ and $j=6$). See here for details.
$$\underline{\textbf{Footnotes}} \\[0.5em]$$
$\text{*}$The adjective "symmetric" here alludes to the fact that these polynomials do not change if you swap around ("permute") the variables. Indeed, $x_1^6\!+\! x_2^6 \!+\! x_3^6 = x_3^6 \!+ \!x_1^6 \!+ \!x_2^6$, etc. On the other hand, $f(x_1, x_2) = x_1x_2^2$ would not be a symmetric polynomial as $x_1x_2^2 \neq x_2x_1^2$.
$\text{**}$Called the "fundamental theorem of symmetric polynomials", this was originally discovered by Isaac Newton. See this thread for further discussion and links to several proofs.
$\mathbf{^\dagger}$For any $n \in \mathbb{N}$, a collection of $n\!+\!1$ elementary symmetric polynomials in $n$ variables is defined. To determine this collection, first start with a generic, completely-factored, $n^\text{th}$-degree monic polynomial $\displaystyle p(x) = \prod_{k=1}^n (x - \alpha_k)$. After expanding and grouping terms, we'll get $p(x) = e_0x^n - e_1x^{n-1} + e_2x^{n-2} - \cdots + (-1)^ne_n$. Each coefficient $e_k$ is the $k^\text{th}$ elementary symmetric polynomial in $n$ variables—a polynomial in $\mathbb{Z}[x_1, x_2, \cdots, x_n]$—which has been evaluated at the roots $x_k = \alpha_k$. For example, let's look at the $n=2$ case:
$$p(x) \ = \ (x-\alpha_1)(x-\alpha_2) \ = \ x^2 - (\alpha_1 + \alpha_2)x + \alpha_1\alpha_2$$
This reveals that, in two variables, $e_0(x_1, x_2) = 1$ and $e_1(x_1, x_2) = x_1 + x_2$ and $e_2(x_1,x_2) = x_1x_2$.
In generality, we'll have:
$$\begin{align}
& e_0(x_1, \cdots, x_n) \ = \ 1 \\[0.5em]
& e_1(x_1, \cdots, x_n) \ = \ \sum_{k=1}^n x_k \\[0.5em]
& e_2(x_1, \cdots, x_n) \ = \ \sum_{1 \leq k \leq j \leq n} x_kx_j \\[0.5em]
& e_3(x_1, \cdots, x_n) \ = \ \sum_{1 \leq k \leq j \leq m \leq n} x_kx_jx_m \\[0.5em]
& \ \ \vdots \qquad \text{ this pattern continues until: } \\[0.5em]
& e_n(x_1, \cdots, x_n) \ = \ \prod_{k=1}^n x_k
\end{align}$$
The problem, is that you are not using outward pointing normal vectors. Every plane has two unit normal vectors, but only one of them is pointing outward. For a flux integral, we use the convention that the flux is the flow out of an object.
In your case, the outward pointing normal vector for $S_1$ is $\langle -1,0,0\rangle$, which changes the sign of your answer. The outward pointing normal vector for $S_2$ remains $\langle 1,0,0\rangle$, so that answer doesn't change. There are two more vectors which need to swap signs, and after that, you'll get
$$
\left(-\frac{1}{2}\right)+\frac{3}{2}+\left(-\frac{1}{2}\right)+\frac{1}{2}+(-0)+1=2.
$$
Best Answer
How about
$$ -\sum_{i=1}^{n-1} \frac{\lvert n_i-n_{i+1} \rvert}{\max(\lvert n_i \rvert, \lvert n_{i+1} \rvert) } $$
That is: summing relative gaps.
(Considering $0/0$ to be 0.)