In general we can define the condition number in the following way.
Suppose we calculate a finite amount of (output) values $y_i$, $i=1,…,n$, for some input data $x_j$, $j=1…,m$ with some algorithm, given as functions: $$y_i:=f_i(x_1,…,x_m).$$
This above describes what we call "a problem".
Suppose we have some perturbation in the data, $x_i+δx_i$, we are interested in the behavior of the output values: $$y_i+δy_i.$$
Using Taylors Expansion, cutting after the term of first order, we get:
$$δy_i =f_i(x+δx)-f_i(x)=\sum_{j=1}^m\frac{∂f_i}{∂x_j}(x)δx_j + R_i^f(x;δx)\approx \sum_{j=1}^m\frac{∂f_i}{∂x_j}(x)δx_j.$$
Note that we need that $f$ is two times differentiable.
It follows:
$$\frac{δy_i}{y_i} \approx \sum_{j=1}^m\frac{∂f_i}{∂x_j}(x)\frac{δx_j}{y_i}= \sum_{j=1}^m\underbrace{\frac{∂f_i}{∂x_j}(x)\frac{x_j}{f_i(x)}}_{:=k_{ij}(x)}\frac{δx_j}{x_j}$$
So the condition number describes how the relative error in the input $x$ transfers to the relative error in the output $y$.
The cutting after the first term is ok, if $|δx|=o(|y_i|)\quad i=1,…,n$.
If $|κ_{ij}|>>1$ we call the problem ill-conditioned.
Example: Adding numbers $y=f(x_1,x_2) = x_1+x_2$
We get \begin{align*}
k_1 = \frac{∂f}{∂x_1}\frac{x_1}{f} = 1\cdot \frac{x_1}{x_1+x_2} = \frac{1}{1+x_2/x_1} \\
k_2 = \frac{∂f}{∂x_2}\frac{x_2}{f} = 1\cdot \frac{x_2}{x_1+x_2} = \frac{1}{1+x_1/x_2}
\end{align*}
Hence addition is ill-conditioned if $x_1/x_2\approx -1$.
Back to your question: Calculating the derivative is the first step, but not enough. You can see that in the example above, where the derivative is constant. Using your argument it would follow, that adding numbers is always well-conditioned, which is not true.
Can you solve your problem now?
EDIT:
The derivative is given by $$f'(x)=\frac{2}{(x-1)^2}.$$
So for the condition number we get:
$$κ=\frac{2x}{(1-x)(1+x)}.$$
This number "seems to be bad" at $x=1$ or $x=-1$, which would mean, that both intervals $(-1,0)$ and $(1/2,1)$ are "bad". But that might be a false conclusion, as we did not simplify $κ$ in a way, that we actually can see something.
(And that conclusion is in fact wrong!)
Do you understand how $κ$ was calculated?
Can you interpret our condition number?
(Have a look at the example above)
