القائمة
Food photo analysis and meal logging for ClawCoach. Send a photo of your meal and get instant macro breakdown via Claude Vision.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
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| name | clawcoach-food |
| description | Food photo analysis and meal logging for ClawCoach. Send a photo of your meal and get instant macro breakdown via Claude Vision. |
| homepage | https://github.com/clawcoach/clawcoach |
This skill handles food photo analysis via Claude Vision, text-based meal logging, and the confirmation flow.
All meals are stored in ~/.clawcoach/food-log.json with this structure:
{
"meals": [
{
"id": "2026-02-22-lunch-001",
"date": "2026-02-22",
"type": "lunch",
"status": "confirmed",
"items": [
{
"name": "grilled chicken breast",
"portion": "6 oz",
"calories": 280,
"protein_g": 52,
"fat_g": 6,
"carbs_g": 0
}
],
"total_calories": 520,
"total_protein_g": 62,
"total_fat_g": 14,
"total_carbs_g": 48,
"source": "photo",
"timestamp": "2026-02-22T12:35:00Z"
}
]
}
When the user sends a photo:
Analyze the image using your vision capabilities. Identify every distinct food item visible. For each item estimate:
Use your nutritional knowledge. For common foods, these are well-established values. Be conservative with portions if uncertain.
Present the results in the user's persona voice:
Handle response:
~/.clawcoach/food-log.json with status "confirmed"After confirmation, always show updated daily totals.
When the user describes food in text:
Categorize meals by time:
The user can override: "log this as a snack"
After any meal is confirmed, calculate and show:
~/.clawcoach/profile.json for targetsUse these as a baseline. Scale by estimated portion size.
| Food | Cal | Protein | Fat | Carbs |
|---|---|---|---|---|
| Chicken breast (grilled) | 165 | 31 | 3.6 | 0 |
| Salmon (baked) | 208 | 20 | 13 | 0 |
| White rice (cooked) | 130 | 2.7 | 0.3 | 28 |
| Brown rice (cooked) | 123 | 2.7 | 1.0 | 26 |
| Pasta (cooked) | 131 | 5 | 1.1 | 25 |
| Broccoli (steamed) | 35 | 2.4 | 0.4 | 7 |
| Egg (whole, large ~50g) | 155 | 13 | 11 | 1.1 |
| Avocado | 160 | 2 | 15 | 9 |
| Sweet potato (baked) | 90 | 2 | 0.1 | 21 |
| Greek yogurt (plain) | 59 | 10 | 0.7 | 3.6 |
| Banana (~120g) | 89 | 1.1 | 0.3 | 23 |
| Oats (cooked) | 68 | 2.4 | 1.4 | 12 |
| Bread (white, per slice ~30g) | 265 | 9 | 3.2 | 49 |
| Cheese (cheddar) | 403 | 25 | 33 | 1.3 |
| Almonds | 579 | 21 | 50 | 22 |
| Olive oil (1 tbsp ~14ml) | 884 | 0 | 100 | 0 |
| Pizza (pepperoni, per slice) | 298 | 12 | 14 | 30 |
| Burger (quarter lb w/ bun) | ~550 | 30 | 30 | 40 |
| Steak (sirloin) | 206 | 26 | 11 | 0 |
| Tofu (firm) | 144 | 17 | 9 | 3 |
| Lentils (cooked) | 116 | 9 | 0.4 | 20 |
| Milk (whole, 250ml) | 61 | 3.2 | 3.3 | 4.8 |
| Protein shake (~1 scoop) | ~120 | 25 | 1.5 | 3 |
For foods not on this list, use your general nutritional knowledge. Be transparent when estimating.
{date}-{meal_type}-{sequence}