  The completeness of the Gaia catalogues heavily depends on the status of that
space telescope through time. Stars are only published with each of the
astrometric, photometric and spectroscopic data products if they are detected a
minimum number of times. If there is a gap in scientific operations, a drop in
the detection efficiency or Gaia deviates from the commanded scanning law, then
stars will miss out on potential detections and thus be less likely to make it
into the Gaia catalogues. We lay the groundwork to retrospectively ascertain
the status of Gaia throughout the mission from the tens of individual
measurements of the billions of stars, by developing novel methodologies to
infer both the orientation and angular velocity of Gaia through time and gaps
and efficiency drops in the detections. We have applied these methodologies to
the Gaia DR2 variable star epoch photometry -- which are the only publicly
available Gaia time-series at the present time -- and make the results publicly
available. We accompany these results with a new Python package scanninglaw
(https://github.com/gaiaverse/scanninglaw) that you can use to easily predict
Gaia observation times and detection probabilities for arbitrary locations on
the sky.
