Diet and Nutrition Tracking Skill

Record daily meals through photos or uploads, automatically analyze nutritional content, and track nutritional intake.

Core Flow

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User Input → Identify Operation Type → [add] Analyze Image → Nutrition Analysis → Save Record
                              ↓
                         [history/status/summary] → Read Data → Display Report

Step 1: Parse User Input

Operation Type Recognition

Input Keywords	Operation Type
add	add - Add diet record
history	history - View history records
status	status - Nutrition statistics
summary	summary - Nutrition summary

Meal Classification (Based on Meal Time)

Time Range	Meal Type
05:00 - 09:59	Breakfast
10:00 - 14:59	Lunch
15:00 - 16:59	Afternoon Tea
17:00 - 21:59	Dinner
22:00 - 04:59	Late Night Snack

Step 2: Check Information Completeness

For add operation, required:

•image - Food photo path

For add operation, optional:

•meal_time - Meal time (defaults to current time)

For history/status/summary operations:

•No parameters required, optional time range

Step 3: Interactive Prompts (If Needed)

Scenario A: No Image Provided

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Please provide a food photo. You can drag and drop or specify the path.

Scenario B: Invalid Image Path

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Cannot read the image. Please check if the path is correct.
Supported formats: JPG, PNG, WebP

Scenario C: Invalid Time Format

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Invalid time format. Please use HH:mm or YYYY-MM-DD HH:mm format
Example: 12:30 or 2025-12-30 12:30

Step 4: Generate JSON

Diet Record Data Structure

json

{
  "id": "20251231123456789",
  "record_date": "2025-12-31",
  "meal_time": "12:30",
  "meal_type": "Lunch",
  "image_path": "food.jpg",
  "foods": [
    {
      "name": "Rice",
      "portion": "1 bowl (about 150g)",
      "weight_estimate": 150,
      "cooking_method": "Steamed",
      "confidence": 0.95
    }
  ],
  "nutrition": {
    "calories": {
      "value": 485,
      "unit": "kcal"
    },
    "macronutrients": {
      "protein": { "value": 15.2, "unit": "g" },
      "fat": { "value": 18.5, "unit": "g" },
      "carbohydrate": { "value": 60.3, "unit": "g" },
      "fiber": { "value": 6.2, "unit": "g" }
    },
    "vitamins": {
      "vitamin_a": { "value": 245, "unit": "μg" },
      "vitamin_c": { "value": 35, "unit": "mg" }
    },
    "minerals": {
      "calcium": { "value": 45, "unit": "mg" },
      "iron": { "value": 2.8, "unit": "mg" }
    }
  },
  "health_score": {
    "overall": 7.5,
    "balance": 8.0,
    "variety": 7.0,
    "nutrition_density": 7.5
  }
}

Step 5: Save Data

•Generate file path: data/diet-records/YYYY-MM/YYYY-MM-DD_HHMM.json
•Create month directory (if not exists)
•Save JSON data file
•Update global index data/index.json

Execution Instructions

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1. Parse user input, identify operation type
2. For add operation:
   a. Use Read tool to read image
   b. Analyze food types and portions
   c. Calculate nutritional content
   d. Save record to data/diet-records/
3. For history operation: Display diet history
4. For status operation: Display nutrition statistics
5. For summary operation: Display nutrition summary

Nutrition Reference

Common Staple Food Portions

•1 bowl rice ≈ 150g (180 kcal)
•1 bowl noodles ≈ 200g (220 kcal)
•1 steamed bun ≈ 100g (220 kcal)

Meat Portions

•Pork 100g ≈ 250 kcal
•Chicken 100g ≈ 130 kcal
•Fish 100g ≈ 100 kcal

Vegetable Portions

•Leafy vegetables 1 serving ≈ 200g (40 kcal)
•Root vegetables 1 serving ≈ 200g (80 kcal)

Adult Daily Nutrition Recommendations

Macronutrients

•Calories: 1800-2400 kcal
•Protein: 55-75 g
•Fat: 55-75 g
•Carbohydrates: 250-350 g
•Dietary Fiber: 25-35 g

Major Vitamins

•Vitamin A: 700-900 μg
•Vitamin C: 100 mg
•Vitamin D: 10-20 μg

Major Minerals

•Calcium: 800-1000 mg
•Iron: 12-18 mg
•Zinc: 10-15 mg

For more examples, see examples.md.