Why reading more 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.

  • Annual book targets give no signal until it's far too late to correct
  • The habit is a time slot, and it's usually lost to a phone rather than abandoned
  • A book you're not enjoying stalls the habit and gets blamed on discipline
  • Ten good minutes and a distracted hour count the same in most trackers

Worth tracking

  • Minutes read, and at what time of day
  • Which book, and whether it's moving
  • What you did instead on the nights you didn't
  • Format — paper, ebook, audio — since they behave differently

Cadence

Logged at the end of a session, usually at night

What progress looks like

Fourteen consecutive nights, and the first book finished inside three weeks

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 reading more gets recorded — with its context — in the time it takes to think it.

Reading More Chat

Read for about 30 minutes before bed, still on the Le Carré.

Called 4 tools

  • log_check_in(habit: "reading", minutes: 30, book: "Le Carré")
  • get_streak(habit: "reading")
  • get_progress(book: "Le Carré")
  • compare_periods(metric: "minutes", a: "this_month", b: "last_month")

11 nights running and 6.5 hours this month, up from 3.2 last month. You're 9 days into this book; your average finish is 17.

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 reading more 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.

Asking about the pattern Chat

Why did I stop reading in June?

Called 3 tools

  • get_history(habit: "reading", window: "6m")
  • find_pattern(group_by: "context")
  • compare_periods(metric: "completion")

You didn't stop, you moved. June was 14 sessions, all before 8pm — your evening slot was gone. The nights you missed, 19 of 23 logged phone use instead.

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 reading more

The same mechanics as every other habit, pointed at what actually matters for this one.

Targets per week, not per day

Three a week is a real goal and a daily checkbox can't hold it. Rest days get recorded as rest rather than counted as failures.

Streaks that survive a life

A missed day is a missed day. The streak that matters is the pattern over months, and one interruption shouldn't erase the evidence of it.

Partial credit

Ten minutes still counts, and gets logged as ten minutes. Half-measures are how most habits actually survive a bad week.

What predicts the days you show up

Which book, and whether it's moving — captured alongside the tick, because that's where the explanation for a good month usually turns out to be.

Measured against your other habits

Ask whether this one is propping up another, or being crowded out by it. Cross-habit questions on request.

Caught at day three

A gap is recoverable early and much less so at three weeks. One nudge when it's still the former.

Early access

Start with reading more

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.

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  • Export everything you've logged whenever you want

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Track reading more by talking about it

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