Stellar variability and transient events provide critical insights into many areas of astrophysics. Progress in these fields has been accelerated by high-precision space-based photometry missions such as CoRoT, Kepler, and K2. NASA's ongoing Transiting Exoplanet Survey Satellite (TESS) represents another significant milestone, offering a unique combination of long observational baseline, high cadence, and nearly all-sky coverage. However, extracting high-quality light curves from TESS full-frame images (FFIs) remains challenging due to contamination from scattered light and blending in crowded fields. In this study, we processed TESS FFIs to produce a comprehensive catalog of light curves for variable point sources observed during the satellite's prime mission. The resulting database, TESS Quick-look and Light curve Analysis (TEQUILA), provides over six million light curves. These include stellar variables, transient events, instrumental systematics, and moving objects. The data were obtained using a pipeline based on difference image analysis, construction of high S/N reference frames, and fixed-radius aperture photometry. A convolutional neural network was used to flag systematic noise, and cross-matching with known Solar System objects was performed to identify contamination. All extracted light curves are publicly accessible as a high-level science product through the MAST archive.

Cone search capability for table J/A+A/704/A317/tequila (TEQUILA master frame catalog)