From the (limited) description the uHz rotator algorithm sounds like one of the phase-weighted averages from this site, but it's not an algorithm I am familiar with.
The Cramér–Rao lower bound$^1$ for estimating the frequency of sinusoid with amplitude $A$ in white noise with variance $\sigma^2$ is given by:
$$ \mathrm{var}(\hat{f}) \ge \frac{12}{(2\pi)^2\eta N(N^2-1)} $$
where $N$ is the number of samples and $\eta = A^2/(2\sigma^2)$ (taken from Kay's Fundamentals of Statistical Signal Processing, Estimation Theory equation 3.41).
So, assuming $A =1$, $\sigma^2 = 0.1$, and assuming that frequency accuracy can exceed 8 significant digits means that $\mathrm{var}(\hat{f}) < (10^{-8})^2$ we get:
$$
\begin{array}
\ (10^{-8})^2 &\ge& \frac{12}{(2\pi)^2 5 N(N^2-1)}\\
\frac{20}{12} \pi^2 \times 10^{-16} &\ge& \frac{1}{N(N^2-1)}\\
N(N^2-1) &\ge& 6.079271 \times 10^{14}\\
N &\ge& 84713
\end{array}
$$
This means that your data length would need to be 84713 samples to achieve this accuracy.
$^1$ The Cramér–Rao lower bound is the lowest achievable variance of an unbiased estimator.