diabetes

name: diabetes description: Diabetes management - blood glucose monitoring, HbA1c tracking, TIR analysis, hypoglycemia event logging, and complication screening argument-hint: <operation_type+info, e.g.: record fasting 6.5, hba1c 6.8, hypo 3.4 sweating, screening retina none> allowed-tools: Read, Write schema: diabetes/schema.json

Diabetes Management Skill

Comprehensive blood glucose monitoring and diabetes management to help control blood sugar and prevent complications.

Core Flow

User Input -> Identify Operation Type -> Extract Parameter Info -> Check Completeness -> [Need Supplement] Ask User
                                                      |
                                                   [Information Complete]
                                                      |
                                              Generate JSON -> Save Data -> Output Confirmation

Step 1: Parse User Input

Operation Type Recognition

Glucose Type Keywords

Hypoglycemia Symptom Keywords

Complication Screening Types

Retinopathy Severity

Nephropathy Status

Step 2: Check Information Completeness

Glucose Record Required:

• Glucose value
• Glucose type (fasting/postprandial_2h/bedtime/random)

HbA1c Record Required:

• HbA1c value (%)

Hypoglycemia Event Required:

• Glucose value
• Symptoms (optional)

Complication Screening Required:

• Screening type
• Result status

Step 3: Interactive Prompts (If Needed)

Scenario A: Missing Glucose Type

Please select glucose measurement type:
- fasting (fasting blood glucose)
- postprandial (2-hour post-meal blood glucose)
- bedtime (bedtime blood glucose)
- random (random blood glucose)

Scenario B: Hypoglycemia Symptom Inquiry

Do you have any of the following symptoms?
- Sweating
- Palpitations
- Tremor
- Hunger
- Confusion
- Dizziness

Scenario C: Missing Complication Screening Parameters

Please provide detailed screening results:
- Retina: none/mild/moderate/severe/proliferative
- Kidney: normal/microalbuminuria/macroalbuminuria + UACR + eGFR
- Nerve: normal/abnormal
- Foot: normal/low_risk/high_risk + Wagner grade

Step 4: Generate JSON

Glucose Record

{
  "id": "glu_20250620070000001",
  "date": "2025-06-20",
  "time": "07:00",
  "type": "fasting",
  "value": 6.5,
  "unit": "mmol/L",
  "in_range": true,
  "target_range": "4.4-7.0"
}

HbA1c Record

{
  "date": "2025-06-15",
  "value": 6.8,
  "unit": "%",
  "target": "<7.0",
  "in_target": true,
  "change_from_previous": -0.3
}

Hypoglycemia Event

{
  "id": "hypo_20250618153000001",
  "date": "2025-06-18",
  "time": "15:30",
  "value": 3.4,
  "severity": "level_1",
  "symptoms": ["sweating", "palpitations"],
  "treatment": "glucose_tablets",
  "resolved": true
}

Complication Screening

{
  "retinopathy": {
    "status": "none",
    "last_exam": "2025-03-20",
    "next_exam": "2026-03-20"
  },
  "nephropathy": {
    "status": "microalbuminuria",
    "uacr": 45,
    "egfr": 78,
    "ckd_stage": "G2A2"
  },
  "neuropathy": {
    "status": "none",
    "monofilament_test": "normal"
  },
  "foot": {
    "status": "low_risk",
    "pulses_present": true,
    "ulcer": false,
    "wagner_grade": 0
  }
}

Complete schema definition: see schema.json.

Step 5: Save Data

1. Read data/diabetes-tracker.json
2. Update corresponding sections based on operation type
3. Update statistics
4. Write back to file

Execution Instructions

1. Identify operation type (record/hba1c/trend/tir/hypo/screening/target/achievement/medication)
2. Extract parameter information
3. Check required field completeness
4. If missing, ask user to supplement
5. Generate JSON compliant with schema.json
6. Save to data/diabetes-tracker.json
7. Output confirmation and medical recommendations

Example Interactions

Example 1: Record Fasting Glucose

User: record fasting 6.5

AI: Blood glucose measurement recorded
Time: 2025-06-20 07:00
Type: Fasting blood glucose
Value: 6.5 mmol/L
Status: Within target range (4.4-7.0)

Recommendation: Continue maintaining good blood glucose control

Example 2: Record Hypoglycemia Event

User: hypo 3.4 sweating

AI: Hypoglycemia event recorded
Time: 2025-06-18 15:30
Blood glucose: 3.4 mmol/L
Severity: Level 1 (mild)
Symptoms: Sweating, Palpitations

Hypoglycemia Management Recommendations:
━━━━━━━━━━━━━━━━━━━━━━━━━━
1. Immediately take 15g fast-acting glucose
   - 3-5 glucose tablets
   - 150ml juice or sugary drink

2. Re-check after 15 minutes

3. If still below 3.9 mmol/L, repeat step 1

4. After glucose normalizes, if >1 hour until next meal, eat small amount of long-acting carbohydrate

Example 3: Record HbA1c

User: hba1c 6.8

AI: HbA1c test result recorded
Value: 6.8%
Target: <7.0%
Status: On target

Change from last: -0.3% (improved)

Recommendation: Test HbA1c every 3 months

Example 4: View Achievement Status

User: achievement

AI: Blood Glucose Achievement Report
━━━━━━━━━━━━━━━━━━━━━━━━━━
HbA1c: 6.8% (target <7.0%) ✓ On target

Past 7 days glucose:
- Fasting: Average 6.2 mmol/L (achievement rate 85.7%)
- Post-meal 2h: Average 8.5 mmol/L (achievement rate 71.4%)
- Bedtime: Average 7.1 mmol/L (achievement rate 100%)

TIR: 72% (target >70%) ✓ On target
Hypoglycemia events: 1 (level 1)

Control Evaluation: Good blood glucose control, continue

For more examples, see examples.md.

Medical Safety Boundaries

Cannot Do:

• Provide specific medication dosage adjustment recommendations
• Directly prescribe or recommend specific medications
• Replace doctor's diagnosis and treatment decisions
• Predict disease prognosis or complication occurrence

Can Do:

• Provide blood glucose monitoring records and trend analysis
• Provide HbA1c tracking and achievement status
• Provide complication screening records and reminders
• Provide hypoglycemia event records and analysis
• Provide lifestyle recommendations and medical visit reminders

Emergency Medical Indications:

• Severe hypoglycemia (unconsciousness, coma)
• Diabetic ketoacidosis (nausea, vomiting, abdominal pain, deep breathing)
• Hyperosmolar hyperglycemic state (severe dehydration, confusion)
• Infection with fever and blood glucose >16.7 mmol/L