health-check-in

name	health-check-in
description	Guided daily or weekly health check-in workflow with adaptive questioning
version	1.0.0

Health Check-In Skill

This skill provides a structured, interactive health check-in workflow that adapts to the user's active conditions and medications. Use this for daily or weekly health monitoring.

Purpose

Guide users through a comprehensive health check-in that covers medication adherence, vital measurements, symptoms, and diet. The check-in adapts based on active conditions and produces a summary at the end.

Prerequisites

Before starting the check-in, gather context:

1. Get active conditions: condition_list(status="active")
2. Get active medications: medication_list(active_only=true)
3. Get recent measurements to understand what vitals the user typically tracks

Check-In Flow

Follow this structured flow in order. Use progressive disclosure — ask one question at a time and wait for response before proceeding.

1. Medication Adherence (if applicable)

If the user has active medications:

For each active medication:

• Ask: "Did you take [medication name] [dosage] today?" (or "this week" for weekly check-ins)
• If yes: Log the dose using medication_log_dose(medication_id=..., notes=...)
• If no: Ask if there was a specific reason and record in notes
• If skipped doses: Remind about importance of adherence

2. Vital Measurements

Based on active conditions, prompt for relevant measurements:

Standard vitals for everyone:

• Weight (if tracked regularly)
• Ask: "Would you like to log your weight today?"
• Use: measurement_log(type="weight", value=..., unit="kg")

Condition-specific vitals:

• If user has diabetes or "blood sugar" condition:

  • Ask: "What's your blood glucose reading?"
  • Use: measurement_log(type="blood_glucose", value=..., unit="mg/dL")

• If user has hypertension or cardiovascular condition:

  • Ask: "What's your blood pressure reading?"
  • Accept format like "120/80"
  • Use: measurement_log(type="blood_pressure", value={"systolic": 120, "diastolic": 80}, unit="mmHg")

• If user has respiratory condition:

  • Ask: "What's your oxygen saturation (SpO2)?"
  • Use: measurement_log(type="oxygen_saturation", value=..., unit="%")

• If user tracks heart rate:

  • Ask: "What's your resting heart rate?"
  • Use: measurement_log(type="heart_rate", value=..., unit="bpm")

Progressive approach:

• Start with most critical measurements based on conditions
• Offer to log additional measurements if user volunteers them
• Don't overwhelm with too many questions at once

3. Symptom Screening

Screen for symptoms based on active conditions:

General screening:

• Ask: "Are you experiencing any new or unusual symptoms today?"
• If yes: Ask for symptom name, severity (1-10), and any additional details
• Use: symptom_log(name=..., severity=..., notes=...)

Condition-specific screening:

• If diabetes: Ask about fatigue, thirst, frequent urination, blurred vision
• If cardiovascular: Ask about chest pain, shortness of breath, dizziness, palpitations
• If respiratory: Ask about coughing, wheezing, shortness of breath
• If gastrointestinal: Ask about nausea, pain, changes in appetite
• If chronic pain: Ask about pain location and intensity

For each reported symptom:

• Ask severity on 1-10 scale (1=mild, 10=severe)
• Ask if symptom is new or ongoing
• Log using symptom_log(name=..., severity=..., notes=...)

Important: Only ask about condition-relevant symptoms. If user has no active conditions, do general screening only.

4. Diet and Nutrition (optional)

Ask: "Would you like to log any meals from today?"

If yes:

• For each meal: Ask when it was eaten (approximate time is fine), get description, approximate calories if known, and any relevant nutrients
• Always pass eaten_at — this is required. Use the user's stated or estimated time. If they say "lunch around noon", use today at 12:00. For planned/future meals, use the expected time.
• Use: meal_log(type=..., description=..., eaten_at=..., nutrition={...})

If user is tracking specific dietary concerns (based on conditions):

• Diabetes: Ask about carbohydrate intake
• Cardiovascular: Ask about sodium intake
• Weight management: Suggest using nutrition_summary to review calorie intake

5. Summary Generation

After completing the check-in, generate a summary using this template:

# Health Check-In Summary
**Date:** [current date]
**Type:** [daily/weekly]

## Medication Adherence
[List each medication with adherence status]
- [Medication name]: ✓ Taken / ✗ Missed [reason if provided]

## Vital Signs
[List measurements logged]
- [Type]: [value] [unit] [trend indicator if available]

## Symptoms
[List symptoms reported]
- [Symptom name]: Severity [1-10] [notes]
[Or "No new symptoms reported" if none]

## Diet
[Summary of meals logged or "No meals logged"]

## Notes
[Any additional observations or concerns]

## Follow-Up Actions
[Suggest any recommended actions based on the check-in]
- [Action item 1]
- [Action item 2]

Trend indicators:

• Get latest previous measurement using measurement_latest(type=...)
• Compare current vs previous value
• Show: ↑ (increased), ↓ (decreased), → (stable)

Follow-up recommendations:

• If missed multiple medications: Suggest setting reminders
• If concerning symptom severity (≥7): Suggest contacting healthcare provider
• If vital signs outside normal range: Suggest monitoring or medical consultation
• If tracking incomplete: Offer to set up scheduled check-ins

Summary Storage

After presenting the summary to the user:

1. Offer to save summary as a research note
2. If accepted: research_save(topic="Health Check-In [date]", content="[summary text]")
3. This makes check-in summaries searchable later via research_search

Adaptive Tips

For daily check-ins:

• Focus on medications and symptoms
• Keep vital measurements light (2-3 key metrics)
• Quick flow, 5-10 minutes

For weekly check-ins:

• More comprehensive measurement review
• Use trend_report to show weekly trends
• Review medication adherence rate using medication_history
• More detailed nutrition review using nutrition_summary

User preferences:

• After first check-in, ask user preference for daily vs weekly
• Note preference in AGENTS.md for future sessions
• Adapt questioning style based on user engagement

Error Handling

• If user doesn't know a measurement: Skip it, don't pressure
• If user reports concerning symptoms: Prioritize logging those first
• If check-in is interrupted: Offer to resume where left off next time
• If medication ID lookup fails: Use medication name to search and confirm with user

Example Check-In Flow

Bot: "Good morning! Let's do your daily health check-in. First, let's check on your medications."

Bot: "Did you take your Metformin 500mg this morning?" User: "Yes, just took it." Bot: [Logs dose] "Great! Did you take your Lisinopril 10mg?" User: "Not yet, I'll take it with breakfast." Bot: [Notes for reminder] "Okay, I'll note that. Now let's check your vitals."

Bot: "What's your blood glucose reading this morning?" User: "112 mg/dL" Bot: [Logs measurement] "That's within normal range. Would you like to log your blood pressure today?" User: "Yes, it's 128 over 82." Bot: [Logs measurement] "Got it. Any symptoms you'd like to report today?" User: "No, feeling good." Bot: [Generates summary and offers to save]

Bot: "Here's your check-in summary: [displays formatted summary]. Would you like me to save this summary for future reference?"