Turn your sleep data into an actual answer
Sleep data is where the gap between “here's a chart” and “here's what's going on” is widest. Stage breakdowns are only useful once something correlates them with the rest of your life.
Your time in bed is fine — 8h 6m average — but efficiency is only 81%, so actual sleep is closer to 6h 34m. The pattern is late: awake time averages 1h 12m and clusters in the second half of the night. Deep sleep is also low at 47 minutes against a 1h 12m average earlier in the year. Nights following days with strain above 15 were the worst of the set.
Illustrative example. Your assistant calls the tools itself — you never name them.
Time in bed is not time asleep
WHOOP doesn't return “time asleep” directly — it's in-bed minus awake. Plenty of people are in bed eight hours and asleep six and a half, and that difference is the whole explanation for feeling wrecked.
Correlation is where it gets useful
Ask your assistant to line sleep up against something else it knows: your calendar, your training log, notes about alcohol or late meals. That's a question a sleep app structurally can't answer because it only holds one of the two datasets.
Before and after
Changed something? “Compare my sleep for the 30 days before 1 June against the 30 days after.” Two tool calls, one paragraph, no spreadsheet.
Prompts to try
- Compare my sleep stages this month against last month.
- Which nights had the least deep sleep, and what was my strain the day before?
- Has my sleep efficiency changed since I stopped drinking coffee after 2pm?
- Include naps — how much total sleep am I really getting?
Tools involved
Ask this about your own data
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