The poster exports Garmin data into a Claude project and meal planner, where Claude spotted a link between eating more on one day and reduced medication efficacy.
The poster exports Garmin data into a Claude project and meal planner, where Claude spotted a link between eating more on one day and reduced medication efficacy.
One commenter said they keep separate meal-planner and health projects and manually enter data from a Hume band, body-composition scales, and their medication use. In back-and-forth conversations, Claude helped them spot that they consistently ate much more on one day of the week and linked it to reduced Mounjaro effect a set number of days after injection; the person then used that finding to update the meal planner.
The result was meals for that day being redesigned so they could eat a lot more without side effects. The thread gives no hard metrics, and other commenters warned that LLMs can overread anomalies unless you provide enough context.
Their practical shortcut was not exporting everything: they said they usually just type a few app data points by hand, which only takes a few minutes.
I'm uploading my Garmin export covering [date range] along with my [medications and meal log]. Look for patterns between my sleep, activity, heart rate and eating, and tell me anything linked to how well [medication or symptom] works. Then draft a one-week meal plan for [goal] based on those patterns, and list the questions to bring to my doctor rather than making medical conclusions.
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