A summation method may be understood as a function
$$ \Sigma : \mathbb{R}^{\mathbb{N}} \to \mathbb{R} \cup \{\texttt{undefined}\}. $$
For instance, the ordinary summation method $\Sigma^{\text{ord}}$ is defined as
$$ \Sigma^{\text{ord}} ((a_k)_{k=1}^{\infty}) = \begin{cases}
\lim_{n\to\infty} \sum_{k=1}^{n} a_k, & \text{if this limit converges}, \\
\texttt{undefined}, & \text{otherwise}.
\end{cases} $$
This function has two additional properties:
Linearity. Suppose that $\mathbf{a} = (a_k)_{k=1}^{\infty}$ and $\mathbf{b} = (a_k)_{k=1}^{\infty}$ are summable, i.e. both $\Sigma^{\text{ord}}(\mathbf{a})$ and $\Sigma^{\text{ord}}(\mathbf{b})$ exist in $\mathbb{R}$. Then we have
$$\Sigma^{\text{ord}}(\alpha \mathbf{a} + \beta\mathbf{b}) = \alpha \Sigma^{\text{ord}}(\mathbf{a}) + \beta \Sigma^{\text{ord}}(\mathbf{b})$$
for all $\alpha, \beta \in \mathbb{R}$.
Stability. Whenever $\mathbf{a} = (a_k)_{k=1}^{\infty}$ is summable and $\mathbf{a}' = (a_{k+1})_{k=1}^{\infty}$, then $\mathbf{a}'$ is also summable and
$$ \Sigma^{\text{ord}}(\mathbf{a}) = a_1 + \Sigma^{\text{ord}}(\mathbf{a}'). $$
Now we have two observations:
$\Sigma^{\text{ord}}(1, -1, 1, -1, \cdots) = \texttt{undefined}$.
Assume that $\Sigma$ is a summation method which satisfies both linearity and stability and that $S = \Sigma(1, -1, 1, -1, \cdots)$ is defined. Then the only possible choice of the value of $S$ is $\frac{1}{2}$, since
\begin{align*}
S
= \Sigma(1, -1, 1, -1, \cdots)
&= 1 + \Sigma(-1, 1, -1, 1, \cdots) \tag{stability} \\
&= 1 - \Sigma(1, -1, 1, -1, \cdots) \tag{linearity} \\
&= 1 - S
\end{align*}
and solving this gives $S = \frac{1}{2}$. This is essentially what you computed.
These two facts do not contradict each other.