CigLit

Before tracking starts, CigLit asks you to calibrate once with your Apple Watch so it learns your smoking orientation, meaning how you hold and raise a cigarette. That setup is what lets the app tell a drag apart from a rest during a real session. If your habits or how you hold a cigarette change, you can recalibrate. It's a small chore up front that decides how accurate everything after it turns out.

The app watches a session frame by frame and separates drags from rests using the watch's motion data. That distinction is the point: two people can smoke the same number of cigarettes and still consume very different amounts of nicotine depending on how they draw. CigLit saves those metrics as you smoke, so a session becomes a set of measured events instead of one rounded-off count.

From the captured drags and the time each session takes, CigLit reports an estimate of nicotine consumed in milligrams. This turns an abstract habit into a number you can actually track and compare week to week. It's a guided reading rather than a lab result, but the trend is what matters most when you're watching a change.

CigLit keeps a running timeline and lets you look at it by day, week, month, or year. The point of stretching the view is to catch patterns that a single day hides. You see whether the count is creeping up, whether weekends differ from weekdays, and whether a period of cutting back is holding. Long-range charts make slow changes visible.

Beyond the raw count, the app tracks how long the average cigarette and session last. Duration often shifts before the cigarette count does, so it's an early signal of a habit changing. CigLit pulls these into easy-to-read stats for daily smoking habits, giving you a fuller portrait than a simple tally.

While a session is running, the app shows time spent smoking and the current count of cigarettes or sessions as they happen. Watching the number climb in real time is a different kind of feedback than reviewing it later. For people trying to slow down, seeing the meter run is often the nudge that works.

The core tracking lives on the Apple Watch, which is what makes hands-busy tracking possible: you raise the watch hand to smoke, and the app follows along. Background run support means the app can keep logging without you holding it open. It's built for the iPhone and Watch pairing rather than a phone alone.

The data is organized around three uses the app names directly: reflect, reduce, or quit. Reflection needs a clear baseline, cutting back needs a trend line that shows progress, and quitting needs a before-and-after picture to compare against. The same timeline serves all three depending on which one you're doing.