  One of the most promising tracers of the Galactic potential in the halo
region are stellar streams. However, individual stream fits can be limited by
systematic biases. To study these individual stream systematics, we fit streams
in Milky Way-like galaxies from FIRE cosmological galaxy formation simulations
with an analytic gravitational potential by maximizing the clustering of stream
stars in action space. We show that for coherent streams the quality of the
constraints depends on the orbital phase of the observed stream stars, despite
the fact that the phase information is discarded in action-clustering methods.
Streams on intermediate phases give the most accurate results, whereas
pericentre streams can be highly biased. This behaviour is tied to the amount
of correlation present between positions and momenta in each stream's data:
weak correlation in pericentre streams prohibits efficient differentiation
between potentials, while strong correlation in intermediate streams promotes
it. Although simultaneous fitting of multiple streams is generally prescribed
as the remedy to combat individual stream biases, we find that combining
multiple pericentric streams is not enough to yield a bias-free result. We
finally show that adopting the two-component St\"ackel model does not
fundamentally induce a biased mass estimate. With our full data set of two
multi-wrap streams, we recovered the true rotation curve of the simulated
galaxy within $12\%$ over the entire range of radii covered by our set of stars
(10 - 176 kpc) and within $6.5\%$ between the 5 and 95-percentile distance
range (23 - 109 kpc).
