Study Settings
Daily limits and target retention, set for each notebase, plus the day boundary the whole schedule is measured against.
Study settings belong to a notebase, not to your account. A 300-word exam list and a slow-burning notebase of reading notes can run at completely different paces.
Where they are
Go to readfrog.app/home, open the Actions menu on the notebase's row, and choose Options. Three fields, and that is the whole of it.
Daily limits
New cards per day and Review cards per day cap how many of each the session hands you in one study day. -1 means unlimited, which is what both start as.
The two limits are counted separately and independently. Hitting the new-card limit does not stop reviews from coming, and vice versa.
What counts against a limit is the first answer you give a card that day. Undoing an answer gives the allowance back, and a card you skip or suspend never spends any.
Which one to set
Review cards per day is the honest brake. Reviews are what a backlog is made of, and a cap here is what keeps a day you cannot finish from turning into a week you cannot start.
New cards per day is the one that decides the size of that backlog weeks from now. Every new card you take on today becomes roughly ten reviews spread over the following months. If you are saving words faster than you can keep up with them, this is the number to bring down — long before you touch the review cap.
A limit does not lose cards; it defers them. Cards over the limit stay due and come back the next day, so a week of 20-a-day on a notebase producing 40 a day quietly builds a queue. When Done for today keeps arriving early and the queue keeps growing, the new-card limit is too high, not too low.
Memory retention
Memory retention is your target: the chance you want of recalling a card at the moment it next comes up. The default is 90%, and the accepted range is 30% to 100%.
It is the one knob that changes the intervals themselves rather than how many you see. Ask for more retention and every interval shortens, so you remember more and review more. Ask for less and intervals stretch, so you review less and forget more.
| Setting | Effect |
|---|---|
Above 90% | Noticeably more reviews for a small gain. Worth it for a deadline, not for a habit. |
90% | The default, and a good balance for most material. |
80–85% | Fewer reviews, more forgotten cards to re-learn. Reasonable for a large, low-stakes notebase. |
Below 80% | You will meet Again often enough that the lapses cost more than the savings. |
Changing it takes effect on your next answer for each card; it does not rewrite due dates that already exist.
The study day
Everything above is measured in study days, and a study day runs from 04:00 to 04:00 in your timezone. A session at 1 a.m. belongs to the previous day, which is the point: a late night does not silently consume tomorrow's allowance.
Your timezone comes from Settings → Preferences → Language & time → Timezone. It is worth checking once if you have travelled or if your reviews seem to reset at an odd hour.
One card per note per day
This one is not configurable, and it is the setting people look for and do not find.
If a note has several cards — because the notebase has several card templates — only one of them comes up on a given day. Answer it and the note's other cards step aside until tomorrow. Two templates therefore do not double your daily load on the same material.
What you cannot change here
The scheduler has more parameters than these three. They are stored per notebase but are not exposed in the interface, and they hold values chosen to be sensible:
| Parameter | Value | What it is |
|---|---|---|
| Learning steps | 1 minute, 10 minutes | The same-session steps a new card walks before it gets a real interval |
| Relearning step | 10 minutes | Where a lapsed card restarts |
| Maximum interval | 36,500 days | The ceiling on any one interval — effectively none |
| Leech threshold | 8 lapses | After this many lapses a card is suspended automatically |
| Interval fuzz | Off | Whether intervals are jittered to spread future days apart |
The learning and relearning steps are not fixed forever, though: the optimizer recomputes them from your own review history along with the rest of the memory model. How Scheduling Works explains what it does and when.