clawcoach-food

# ClawCoach Food — Photo Analysis & Meal Logging This skill handles food photo analysis via Claude Vision, text-based meal logging, and the confirmation flow. ## When to Activate - User sends a photo — assume it is food unless context clearly suggests otherwise - User types a food description ("I had 2 eggs and toast for breakfast") - User says "log [food]" or "I ate [food]" - User wants to edit or delete a previous meal ## Data Storage All meals are stored in `~/.clawcoach/food-log.json` with this structure: ```json { "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" } ] } ``` ## Photo Analysis Flow When the user sends a photo: 1. **Analyze the image** using your vision capabilities. Identify every distinct food item visible. For each item estimate: - Name (be specific: "grilled chicken breast" not just "chicken") - Portion in common units (oz, cups, pieces, slices) - Calories and macros (protein, fat, carbs in grams) Use your nutritional knowledge. For common foods, these are well-established values. Be conservative with portions if uncertain. 2. **Present the results** in the user's persona voice: - List each item with portion and macros - Show meal total - Show daily running totals (consumed / target / remaining) - Ask: "confirm? (yes / edit / redo)" 3. **Handle response:** - **"yes" / "confirm"** — Write the meal to `~/.clawcoach/food-log.json` with status "confirmed" - **Correction** (e.g., "the rice was brown rice" or "it was more like 8oz") — recalculate and present updated totals - **"redo"** — ask for a new photo or text description 4. After confirmation, always show updated daily totals. ## Text-Based Logging When the user describes food in text: 1. Parse the food items and estimate portions from the description 2. Calculate macros for each item using your nutritional knowledge 3. Follow the same confirmation flow as photo analysis ## Meal Type Auto-Detection Categorize meals by time: - Before 10:00 = breakfast - 10:00 - 14:00 = lunch - 14:00 - 17:00 = snack - After 17:00 = dinner The user can override: "log this as a snack" ## Editing and Deleting - "Delete my lunch" — find today's lunch entry, remove it from food-log.json - "I think that was more like 400 calories" — update the specific meal entry - "What did I eat today?" — list all confirmed meals for today with totals ## Daily Totals After any meal is confirmed, calculate and show: 1. Read profile from `~/.clawcoach/profile.json` for targets 2. Sum all confirmed meals for today from food-log.json 3. Display: - **Consumed**: X cal | Xg protein | Xg fat | Xg carbs - **Target**: X cal | Xg protein | Xg fat | Xg carbs - **Remaining**: X cal | Xg protein | Xg fat | Xg carbs ## Edge Cases - **Blurry or unclear photo**: "I can't quite make out the food. Try a better lit photo, or just tell me what you had." - **Non-food photo**: "That doesn't look like food! Send a photo of your meal, or type what you ate." - **Unknown food**: Ask the user for clarification rather than guessing wildly. - **Multiple items unclear**: "I can see chicken and something else — is that rice or pasta?" - **No portion visible**: Use standard serving sizes and note: "I estimated a standard portion — let me know if it was more or less." ## Nutritional Reference (Common Foods per 100g) Use 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. ## Important - Always present macros rounded to whole numbers - Always show daily running totals after confirming a meal - The persona voice comes from clawcoach-core — match it in all responses - Never log a meal without user confirmation - Generate unique meal IDs as: `{date}-{meal_type}-{sequence}`