Moodset approaches self-tracking from two directions at once. On one side there is deliberate input: a quick tap that records how pleasant and how energised you feel, mapped onto a valence-and-arousal model rather than a flat happy-to-sad slider. On the other side there is passive signal: the app analyses the emotional character of the music you listen to and folds those observations into the same timeline, so the picture is built from what you report and what your habits reveal.
That combined view is where the product proves most useful. A chart mode surfaces trends, a list mode breaks down what actually shaped a given day, and toggles let you switch between manual entries, auto-tracked listening, or both together. Scope and date selectors stretch from today's ups and downs to a year of longer arcs, which is especially handy when preparing for a therapy session or trying to understand a recurring low or high stretch.
Moodset also builds a bridge from awareness to action. Because it knows your mood and your preferred genres, it can assemble playlists designed either to deepen the state you are in or to move you gently toward a different one. Notes attached to check-ins add context, so you see not only that a mood changed but what preceded it. The team emphasises privacy and real-time syncing across devices, positioning the app as a reflective companion rather than a clinical tool.
