Breaking · Cutting Screen Time
A screen time habit tracker that knows the difference between hours and habits
Your phone already tells you the number, and the number hasn't changed anything. Six hours of screen time isn't a habit, it's an aggregate of about forty separate ones — the reach before you're properly awake, the reflex pickup at every pause, the app you open without deciding to. Changing it means picking one of those and tracking that.
Why cutting screen time is hard to track
Not hard to do — that's a separate problem. These are the reasons the tracking itself tends to give out first, which is usually what takes the habit with it.
- Built-in screen time reports are a total, and totals aren't habits
- App limits get dismissed in half a second and log nothing when they do
- The reaches that matter are the unconscious ones, which by definition go unnoticed
- Some of those hours are work and some are the void, and the total can't tell them apart
Worth tracking
- Whether the first thirty minutes awake were phone-free
- Pickups during specific protected blocks, not all day
- The one or two apps you're actually trying to cut
- What you did instead when you put it down
Cadence
Logged at natural boundaries — morning, end of work, bed
What progress looks like
Seven consecutive phone-free mornings, and the first evening block held without checking
In practice
Log it in the sentence you'd have said anyway
Every operation in the app is a tool the chat can call, so cutting screen time gets recorded — with its context — in the time it takes to think it.
Called 4 tools
log_check_in(habit: "phone-free-morning", status: "held")get_streak(habit: "phone-free-morning")log_replacement(activity: "reading")correlate_habits(a: "phone-free-morning", b: "reading")
Every figure here was counted from your check-ins. The model picked the tools and filled in the arguments — it never estimates a streak or invents a number.
And then ask
The question your history can answer
Weeks of check-ins about cutting screen time contain a genuine answer to questions you've been guessing at. The only thing that was ever missing was something willing to read them.
Ask in plain language; the model turns it into queries against your record and shows the numbers behind the answer, so you can tell a real pattern from a coincidence in eleven data points.
Called 3 tools
get_history(habit: "screen-time", window: "6m")find_pattern(group_by: "context")compare_periods(metric: "completion")
Every figure is a count or an average over your own check-ins. The model chose which comparisons to run; it produced none of the numbers.
What it does
Set up around cutting screen time
The same mechanics as every other habit, pointed at what actually matters for this one.
A slip is a data point, not a reset
One bad day doesn't zero six good weeks. It gets logged with what was happening around it, which is the part that makes the next week survivable.
Near misses count as signal
The times you wanted to and didn't are the most informative events you have. Pickups during specific protected blocks, not all day is recorded as its own thing, not inferred from an absence.
Reduction targets, not just zero
Cutting down is a legitimate goal with a number in it. Set a target and a taper, and measure against those rather than against perfection.
Trend across months
One rough week reads as one rough week when it sits on a six-month line. That's the view that keeps people going, and it's the one streak counters can't draw.
The hours that actually matter
Logged at natural boundaries — morning, end of work, bed — so the record lines up with when the difficulty is, rather than with midnight.
A nudge before the hard part
Not a daily ping you learn to swipe away. Something at the hour your own data says is the risky one.
Early access
Start with cutting screen time
Tell us where it's gone wrong before and we'll set it up with you — measuring the right thing, at a cadence you'll keep.
- Founding accounts lock their price for life
- No card, no trial clock, no streak-guilt notifications
- Export everything you've logged whenever you want
Also breaking
Other habits people track
Quitting Smoking
Logged when a craving hits, reviewed every Sunday
Quitting Vaping
Counted roughly through the day, reviewed weekly against the taper plan
Drinking Less
Logged the next morning, reviewed against a weekly target
Cutting Sugar
Logged in the moment, one line, reviewed weekly
Beating Procrastination
Logged as it happens or at end of day, reviewed weekly
Track cutting screen time by talking about it
Founding pricing is locked for accounts opened during early access.
Founding accounts lock their price for life. No card required.