Initial meal-suggestion skill (logic + template; live data git-ignored)

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# Live data — keep out of version control.
# Your current stock and 7-day meal log drift as you eat / the daily job runs.
inventory.json
meal-history.json

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# meal-suggestion skill
Kitchen-inventory + high-protein meal suggestion skill for Hermes Agent.
- Tracks a kitchen inventory (`inventory.json`).
- Emails **2 daily meal suggestions** (from stock) every day at 09:00.
- Emails a **weekly £30 shopping list** (Mondays 08:00) with a per-store
price comparison (Lidl preferred) and a plain-text fallback.
- Targets ~190200 g protein/day for a recovering burns victim (2 g/kg at
~95100 kg, age 46), avoids buying red meat, allows Amazon Prime + low-cost
condiments/flavourings/micronutrients when budget allows.
## Files
- `SKILL.md` — the skill (rules, shop logic, 7-day history removal flow).
- `references/` — email template, protein sources, Eastbourne shop ratios,
meal-history logger spec, protein-target notes.
- `inventory.json`**LIVE DATA** (your current stock). Git-ignored; a
`inventory.example.json` is committed as a template.
- `meal-history.json`**LIVE DATA** (rolling 7-day meal log). Git-ignored.
## Setup
1. Copy the skill into your Hermes skills dir:
```
cp -r meal-suggestion ~/.hermes/skills/
```
2. Create `inventory.json` from the example:
```
cp ~/.hermes/skills/meal-suggestion/inventory.example.json \
~/.hermes/skills/meal-suggestion/inventory.json
```
3. Ensure the email sender exists at `~/.hermes/.env`:
```
EMAIL_ADDRESS=hpm6@txt3.com
EMAIL_PASSWORD="your-app-password"
EMAIL_SMTP_HOST=smtp.gmail.com
EMAIL_SMTP_PORT=587
```
4. Place the send helper:
`scripts/meal/send_meal_email.py` (reads creds from `~/.hermes/.env`,
supports `--subject --html --text --to`).
5. Create the two cron jobs (Hermes `cronjob` tool):
- Daily 09:00: `0 9 * * *` — load skill `meal-suggestion`, read inventory,
build 2 meals, email to `jp@txt3.com`, record into `meal-history.json`.
- Monday 08:00: `0 8 * * 1` — load skill `meal-suggestion`, build £30 Lidl
list + comparison, email to `jp@txt3.com`.
See `SKILL.md` for the full behavior spec and the removal-from-history flow.
> General guidance, not medical advice — defer to clinical/dietitian team.

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---
name: meal-suggestion
description: "Kitchen inventory + high-protein meal suggestions. Tracks ingredients, suggests 2 daily meals from stock, and a weekly £30 shopping list. Emails jp@txt3.com from hpm6@txt3.com. For a recovering burns victim on a high-protein diet avoiding red meat."
version: 1.0.0
author: agent
license: MIT
---
# Meal Suggestion
## Context
User **jp** is a recovering burns victim who must eat a **high-protein diet** and wants to
**avoid red meat**. This skill keeps a running kitchen inventory and produces:
- **2 daily meal suggestions** (from what's in stock) — emailed every day at 09:00.
- **A weekly shopping list** on a **£30 budget** — emailed Mondays.
- **Sender:** `hpm6@txt3.com` (the agent's Gmail, via smtp.gmail.com:587).
- **Recipient:** `jp@txt3.com`.
## Inventory
File: `/home/jp/.hermes/skills/meal-suggestion/inventory.json`
Schema:
```json
{
"updated": "YYYY-MM-DD",
"diet": { "goal": "high-protein", "avoid": ["red meat"] },
"items": [
{ "name": "Eggs", "qty": 12, "unit": "count", "category": "protein", "notes": "" }
]
}
```
- `category` is one of: `protein`, `veg`, `fruit`, `dairy`, `grain`, `tinned`,
`frozen`, `condiment`, `other`.
- Keep `qty` as a number with a `unit` (`count`, `g`, `ml`, `pack`, `can`, `tbsp`, etc.).
### Updating the inventory (you own this)
- When the user says they **used/consumed** ingredients, decrement or remove the
matching item(s) with the `patch` tool, then bump `updated` to today.
- When the user **bought** items, add or increase them.
- Do **NOT** auto-consume on a daily suggestion — the user tells you what was
actually eaten. The daily email only *proposes* meals.
## Meal suggestion rules
- Suggest **two meals** per day (e.g. lunch + dinner) using only items currently in the inventory.
- **Maximize protein** per meal; lead with a protein source.
- **Avoid red meat for PURCHASES** (beef, lamb, pork, venison, bacon, gammon) — the
weekly shopping list must NEVER suggest red meat to buy.
- **If red meat is already in the inventory, it stays usable** in daily meal
suggestions so it isn't wasted. Deprioritize it behind the high-protein
non-red-meat options, but do NOT exclude it just because it's red meat.
- Preferred proteins (lead with these): eggs, chicken, turkey, fish, prawns, tofu,
tempeh, lentils, beans, chickpeas, Greek yogurt, cottage cheese, quark, skim milk,
whey, tinned tuna/salmon, edamame, halloumi.
- **Protein target:** ~**190200 g/day** (user ~95100 kg × 2 g/kg — burns recovery +
preserving lean mass while losing ~15 kg fat). Aim each meal at **~90100 g protein**
and **STATE the per-meal and daily protein totals** in the email. If 2 meals can't
reach ~190 g with current stock, say so and suggest a third hit (whey shake, extra
eggs, Greek yogurt) to close the gap.
- **Weight-loss framing:** keep meals calorie-moderate — bulk with veg, go easy on oven
chips, white bread, and oil; lead with lean protein. Fat loss comes from a mild calorie
deficit, NOT from cutting protein.
- **Note:** this is general guidance, not medical advice — defer to the user's
clinical/dietitian team and keep hydration up on a high-protein intake.
- Each meal block: **name**, the **ingredients + approx amounts** used, a short
**23 step method**, and the **protein total (g)**.
- If the inventory is too sparse for a real meal, say so and list the top 23
things to buy.
## Email format
Send via the helper (it reads SMTP creds from `~/.hermes/.env`):
```bash
python3 /home/jp/.hermes/scripts/meal/send_meal_email.py \
--subject "Your Meals for Today — <date>" \
--html /tmp/meal_today.html \
--to jp@txt3.com
```
HTML must be self-contained (inline CSS), mobile-friendly, dark-on-light, with a
header, the two meal cards, and a footer note
("Reply to tell me what you used and I'll update the inventory").
Use the scaffold in `references/email-template.md`.
## Weekly shopping list (Mondays)
- Budget **£30** total. Use realistic UK supermarket prices (Tesco/Asda/Sainsbury's).
- Prioritize protein, then veg/fruit, then staples. Show item, est. price, and a
running total that lands in range.
- Email subject: `Weekly Shopping List — <date>`.
- This does **not** modify the inventory.
- **Micronutrients & vitamins (user is 46):** you MAY include 12 low-price
health-support items on the weekly shop when budget allows under £30, to support
overall health alongside the high-protein diet. Sensible, evidence-aware picks for a
46-year-old on high protein with limited red meat: vitamin D (low sun exposure risk),
omega-3 (fish-oil or flax/chia), magnesium (recovery/sleep), and a B12 source if
relying on eggs/dairy over meat. Prefer food-first (oily fish, leafy greens, seeds);
only add a supplement line (e.g. "Vitamin D3 10002000 IU", "Omega-3 caps") when
budget permits and label it clearly as a general-health suggestion, NOT medical advice.
Keep each low-cost and behind protein + veg + staples in priority.
- **Condiments & flavourings:** you MAY include a small item or two from the
spice/sauce/condiment aisle (e.g. fresh herbs, lemon, soy, spices, stock cubes,
passata, a hot sauce) so meals are more interesting — keep each low-price and only
if budget allows under £30. These are optional "interest" buys; protein + veg +
staples come first.
## Where to shop (Eastbourne) — single-shop, per-store totals
User is in **Eastbourne**. Local options: **Lidl, Sainsbury's, Co-op, Tesco Express,
and a local Londis** (good deal on milk: 2L £1.40). Memberships: Tesco Clubcard, Co-op member.
**User preference (confirmed): Lidl is the PREFERRED shop.** It's a weekly trip so the
extra distance is acceptable; Lidl gives the best value AND leaves budget for essential
micronutrients and the occasional treat. The other stores (Tesco Express, Sainsbury's,
Co-op, Londis) are shown ONLY for comparison, and as the fallback for days he doesn't
want to make the longer journey.
Grounded in Which? 2026 monthly price index (93-item basket; Lidl £160.70 baseline):
- Lidl ≈ 1.00x — **CHEAPEST, preferred** (whey, eggs, chicken, lentils, frozen veg, milk, tuna, bananas, plus fruit/veg for micronutrients + a treat)
- Tesco superstore w/ Clubcard ≈ 1.17x; **Tesco Express** adds convenience premium → ~1.22x WITH Clubcard
- Sainsbury's w/ Nectar ≈ 1.17x
- Co-op ≈ 1.30x nominal — membership = annual dividend, not instant discount
- Londis ≈ 1.251.35x indicative; milk cheap but full basket pricier → top-up only
**Weekly email MUST:**
1) Build ONE single-shop basket available at **Lidl** (the default recommended shop).
2) Show a **"Same basket — where else?" comparison table** (Lidl / Tesco Express Clubcard
/ Sainsbury's Nectar / Co-op member / Londis) with estimated totals + delta vs Lidl.
Label as ESTIMATES from Which? 2026 ratios + known local prices (Londis milk £1.40),
NOT live scans. Do NOT run a live web search.
3) **Recommend Lidl** as the primary shop — note it's a weekly trip so distance is fine
and it best fits the budget incl. micronutrients/treats. List the others as fallback
only ("if you'd rather not make the trip: Tesco Express is closest").
4) Single-shop the list — don't split across stores UNLESS a specific item's local price
is **definitely known** to be lower elsewhere (e.g. Londis milk 2L at £1.40 is a
confirmed cheaper line). Estimated basket ratios alone are NOT grounds to split.
5) You MAY suggest ordering certain items via **Amazon Prime** when it's clearly better
value (e.g. whey protein 1 kg is often cheaper per gram on Prime than in-store). If
used, show the Prime item separately and note it's a delivery, not a store trip.
6) Robustness: the comparison table must be clearly visible. ALSO attach a plain-text
alternative (send_meal_email.py --text) so the comparison survives even if the mail
client strips HTML tables.
## Split-store & Amazon Prime rules
- **Default: single shop at Lidl.** Do NOT split the basket across stores based only on
the estimated Which? 2026 ratios — those are approximations. Splitting is allowed ONLY
when a **specific item's local price is definitely known** to be lower elsewhere
(e.g. Londis milk 2L at £1.40 is a confirmed cheaper line, so milk could be a Londis
top-up). State the known price when you do this.
- **Amazon Prime:** you MAY suggest ordering specific items via Amazon Prime, but ONLY
when it is **genuinely better value or more convenient** — do not assume Prime is
automatically cheaper. Reality check (2026): Lidl whey is ~£9.99/500g (≈£20/kg);
Prime branded whey (Bulk/Myprotein) is typically £18£27/kg, so it's roughly comparable
and Lidl often wins on a single trip. Suggest Prime for whey ONLY when (a) a confirmed
deal drops it below Lidl's per-kg price, or (b) the user prefers delivery over the trip.
When suggesting, show both prices side by side and state which is cheaper. Show any
Prime item as a separate "delivered via Prime" line, distinct from the in-store Lidl list.
- When neither applies, keep everything in the one Lidl list.
## 7-day meal history (for inventory removal)
A rolling log lives at `meal-history.json` (same skill dir). The **daily job UPSERTS**
its two meal entries each run (replaces any same `date`+`meal`, so re-runs don't
duplicate) and **prunes entries older than 7 days**. Each entry:
`{ date, weekday, meal: "lunch"|"dinner", name, items: [{name, qty, unit}] }`.
Only substantive food items are logged — pure condiments (oil, salt, pepper, spices,
garlic, soy, etc.) and the optional "third hit" snack are NOT logged. Units match
`inventory.json` where possible.
**On-demand removal (user says e.g. "remove Wednesday's dinner from inventory"):**
1) Resolve the weekday/date to the matching entry (weekday is relative to today; if
ambiguous, ask). 2) For each `item` in that entry, find the matching inventory entry
by name (case-insensitive). 3) Subtract `qty`; if the result is ~0 or negative,
remove the inventory entry; else update it. 4) Skip any item NOT present in inventory
(e.g. a suggested-but-never-bought item) and say so. 5) Bump `updated` to today.
6) Confirm what was removed. The user can also say "remove all of <day>" to drop both
meals, or name a specific item to override.
## On-demand (chat)
If the user lists ingredients in chat, add them to the inventory and optionally
give an immediate 2-meal suggestion. If they ask "what should I eat today?", read
the inventory and suggest now (and offer to email it).
## Automation
Two cron jobs (created via the `cronjob` tool), both loading this skill:
- Daily 09:00 — `0 9 * * *` — 2 meal suggestions.
- Monday 08:00 — `0 8 * * 1` — weekly £30 shopping list.
Delivery is `local` because the email itself is the deliverable; check
`cronjob action=list` / logs if a send ever seems missing.
## References
- `references/protein-sources.md` — allowed proteins + example pairings.
- `references/email-template.md` — HTML email scaffold.

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{
"updated": "YYYY-MM-DD",
"diet": {
"goal": "high-protein",
"reason": "recovering burns victim — healing well, preserving lean mass",
"avoid_purchase": ["red meat"],
"age_years": 46,
"bodyweight_kg": "95-100",
"protein_per_kg": 2,
"protein_target_g_per_day": "190-200",
"weight_loss_goal_kg": 15,
"notes": "2g/kg for burns recovery + lean-mass preservation during ~15kg fat loss. Fat-loss comes from a mild calorie deficit (bulk with veg, limit chips/bread/bread/oil), NOT from cutting protein. Red meat already in stock is usable but never re-bought. General guidance, not medical advice — defer to clinical/dietitian team; keep hydrated."
},
"items": [
{ "name": "Eggs", "qty": 14, "unit": "count", "category": "protein", "notes": "" },
{ "name": "Chicken breast", "qty": 1, "unit": "count", "category": "protein", "notes": "whole breast, ~120-150g" },
{ "name": "Whey protein powder", "qty": 1000, "unit": "g", "category": "protein", "notes": "high-protein staple; ~25g protein per scoop" },
{ "name": "Tinned tuna in veg oil", "qty": 1, "unit": "can", "category": "tinned", "notes": "protein" },
{ "name": "Milk", "qty": 1, "unit": "litre", "category": "dairy", "notes": "" },
{ "name": "Greek yogurt", "qty": 1, "unit": "pot", "category": "dairy", "notes": "high protein" },
{ "name": "Cottage cheese", "qty": 1, "unit": "pot", "category": "dairy", "notes": "high protein" },
{ "name": "Red lentils", "qty": 500, "unit": "g", "category": "grain", "notes": "protein-rich" },
{ "name": "Frozen mixed veg", "qty": 1000, "unit": "g", "category": "frozen", "notes": "calorie bulk, cheap" },
{ "name": "Broccoli", "qty": 2, "unit": "count", "category": "veg", "notes": "small heads" },
{ "name": "Carrots", "qty": 800, "unit": "g", "category": "veg", "notes": "" },
{ "name": "Sweet potatoes", "qty": 3, "unit": "count", "category": "veg", "notes": "" },
{ "name": "Onions", "qty": 6, "unit": "count", "category": "veg", "notes": "" },
{ "name": "Bananas", "qty": 5, "unit": "count", "category": "fruit", "notes": "" }
]
}

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{
"note": "Rolling 7-day log of suggested meals. See SKILL.md / references/meal-history.md. This is an example/empty template — the live file is git-ignored.",
"entries": []
}

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# Where to Shop — Eastbourne (value research, 2026)
User is in Eastbourne. Local options: Lidl, Sainsbury's, Co-op, Tesco Express
(closest), and a local Londis (milk 2L £1.40). Memberships: Tesco Clubcard, Co-op member.
## Price index (Which? 2026, ~93-item standard basket; Lidl = £160.70 baseline)
| Supermarket | Basket | vs Lidl | Notes |
|---|---|---|---|
| Lidl | £160.70 | 1.00x | Cheapest discounter; furthest from user |
| Tesco (Clubcard) | £188.45 | 1.17x | Clubcard Prices = real discount |
| Sainsbury's (Nectar) | £187.86 | 1.17x | Mid; Nectar needed for this price |
| Tesco Express | ~£196203 | ~1.221.26x | Superstore + convenience premium; Clubcard applies |
| Co-op | ~£209+ | ~1.30x | Membership = annual dividend, not instant |
| Londis | varies | ~1.251.35x | Milk cheap (£1.40/2L); full basket pricier |
## Multipliers used for per-store estimates in the weekly email
- Lidl: 1.00
- Tesco Express (Clubcard): 1.22
- Sainsbury's (Nectar): 1.17
- Co-op (member): 1.30 (dividend softens over the year, not at till)
- Londis: 1.30 indicative, flagged rough
## Recommendation logic (single shop)
- Default: **Tesco Express** — closest to user + Clubcard Prices narrow the gap.
Pragmatic given limited mobility during burns recovery.
- If user prioritises price over proximity: **Lidl** (~£6 cheaper on a ~£28 list).
- Co-op only if already there for something else; Londis for milk/top-ups.
## Why proximity matters here
User is a recovering burns victim — a long trip to Lidl may not be feasible daily/weekly.
The ~1722% price premium of Tesco Express is often worth the saved trip. The email
states this trade-off explicitly so he can choose.

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# HTML Email Template (inline CSS, mobile-friendly)
Copy this scaffold, fill the meal sections, and save to `/tmp/meal_today.html`
(or `/tmp/meal_shop.html` for the weekly list) before sending.
```html
<!DOCTYPE html>
<html lang="en">
<head><meta charset="utf-8"><meta name="viewport" content="width=device-width, initial-scale=1"></head>
<body style="margin:0;padding:0;background:#f4f6f8;font-family:-apple-system,Segoe UI,Roboto,Helvetica,Arial,sans-serif;color:#1f2933;">
<table role="presentation" width="100%" cellpadding="0" cellspacing="0" style="background:#f4f6f8;padding:16px 0;">
<tr><td align="center">
<table role="presentation" width="100%" cellpadding="0" cellspacing="0" style="max-width:600px;background:#ffffff;border-radius:12px;overflow:hidden;box-shadow:0 1px 4px rgba(0,0,0,0.08);">
<tr><td style="background:#0f766e;padding:20px 24px;color:#ffffff;">
<h1 style="margin:0;font-size:20px;">Your Meals for Today</h1>
<p style="margin:4px 0 0;font-size:13px;opacity:0.9;">Tuesday, 25 August 2026 · high-protein · no red meat</p>
</td></tr>
<tr><td style="padding:20px 24px;">
<!-- MEAL 1 -->
<div style="border:1px solid #e4e7eb;border-radius:10px;padding:16px;margin-bottom:16px;">
<h2 style="margin:0 0 6px;font-size:17px;color:#0f766e;">🍽 Lunch — Meal Name</h2>
<p style="margin:0 0 8px;font-size:14px;color:#52606d;"><strong>Ingredients:</strong> 3 eggs, 100g spinach, 1 tbsp olive oil</p>
<p style="margin:0;font-size:14px;color:#3e4c59;line-height:1.5;"><strong>Method:</strong> 1) … 2) … 3) …</p>
</div>
<!-- MEAL 2 -->
<div style="border:1px solid #e4e7eb;border-radius:10px;padding:16px;margin-bottom:16px;">
<h2 style="margin:0 0 6px;font-size:17px;color:#0f766e;">🍽 Dinner — Meal Name</h2>
<p style="margin:0 0 8px;font-size:14px;color:#52606d;"><strong>Ingredients:</strong></p>
<p style="margin:0;font-size:14px;color:#3e4c59;line-height:1.5;"><strong>Method:</strong> 1) … 2) …</p>
</div>
</td></tr>
<tr><td style="background:#fafbfc;padding:14px 24px;border-top:1px solid #e4e7eb;font-size:12px;color:#7b8794;">
Reply to tell me what you used and I'll update the inventory. — your meal agent
</td></tr>
</table>
</td></tr>
</table>
</body>
</html>
```
For the **weekly shopping list**, replace the meal cards with a table:
`Item | Est. price | Running total`, a `Total: £XX.XX` row, and a one-line note on
what it covers (protein-first). Keep the same header/footer style.

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# Meal-history logger (used by the daily job)
After composing the two meals (lunch + dinner) and BEFORE sending the email, the daily
job must record them into `meal-history.json` (same skill dir) so the user can later say
"remove <day>'s <meal> from inventory" and have precise items deducted.
## Entry shape
```json
{
"date": "2026-08-27",
"weekday": "Thursday",
"meal": "lunch" | "dinner",
"name": "Human-readable meal name",
"items": [ { "name": "Name as in inventory.json", "qty": 1, "unit": "count" }, ... ]
}
```
## Rules
- UPSERT: if an entry with the same `date`+`meal` already exists, replace it (don't
duplicate on re-runs).
- PRUNE: drop any entry whose `date` is more than 7 days before today (keep a true
rolling 7-day window).
- Log ONLY substantive food items actually used in that meal — enough to decrement
inventory accurately. Do NOT log pure condiments (olive oil, salt, pepper, spices,
garlic, soy sauce, miso, honey, etc.) and do NOT log the optional "third hit" snack.
- Item `name` values should match `inventory.json` names closely (case-insensitive match
on removal) so removal works: e.g. "Chicken breast", "Eggs", "Tinned tuna in veg oil",
"Dried red lentils", "Sweet potatoes", "Aubergine", "Red cabbage", "Green pesto",
"Leeks", "Orange bell pepper", "Cooked beetroot", "Microwave rice", "Cheese", etc.
- Use units consistent with inventory.json (count / g / can / portion / pieces / jar).
For a half-item use 0.5 (e.g. half a sweet potato = qty 0.5 unit "count").
- Bump the top-level file with no extra schema — keep the `entries` array only.
- This does NOT modify inventory.json (that only happens on explicit user removal).
## Example
Composed lunch "Chicken & Pesto Roast Veg Bowl" using chicken breast (1), sweet potato
(½), aubergine (½), red cabbage (150 g), green pesto (1 tbsp ≈ 0.1 jar) → record those
five items under meal "lunch" for today's date/weekday.

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# Allowed Protein Sources (no red meat)
High-protein foods to favor, with rough protein density and typical cheap UK buys.
Use these when suggesting meals and when building the weekly shopping list.
## Animal (non-red-meat)
- Eggs — ~13g protein each; cheapest protein there is. Buy 1215 packs.
- Chicken breast / thigh — ~30g per 100g raw. Buy 500g1kg trays.
- Turkey breast / mince — lean, ~29g per 100g.
- White fish (cod, haddock, basa) — ~20g per 100g; frozen fillets are cheap.
- Salmon (fresh or tinned) — ~2025g per 100g; tinned in spring water is budget-friendly.
- Tinned tuna — ~25g per 100g drained; ~£1/can.
- Prawns — ~20g per 100g; frozen raw prawns often <£3/300g.
- Quark / cottage cheese — ~1214g per 100g; very cheap per gram.
- Greek yogurt (0%/low fat) — ~10g per 100g; buy large tubs.
- Skim milk / semi-skimmed — ~3.4g per 100ml.
- Whey protein powder — ~25g per scoop; good staple for hitting targets.
## Plant
- Tofu (firm) — ~1217g per 100g; ~£1.50/block.
- Tempeh — ~19g per 100g.
- Edamame (frozen) — ~11g per 100g.
- Lentils (dry or tinned) — ~9g per 100g cooked; very cheap.
- Chickpeas (tinned) — ~8g per 100g; ~50p/can.
- Beans (kidney/black/butter) — ~8g per 100g; ~50p/can.
- Peanut butter (no added sugar) — ~25g per 100g; cheap calorie+protein.
## Example pairings (per meal)
- Eggs + Greek yogurt + spinach/peppers (omelette + side).
- Chicken + lentils + veg (stir-fry / bowl).
- Tofu + edamame + rice/quinoa (buddha bowl).
- Tinned tuna + cottage cheese + salad.
- Salmon + boiled eggs + greens.
- Whey shake + banana + peanut butter (snack/breakfast).
- Prawns + chickpeas + tomato (stew).
- Turkey mince + beans + tinned tomatoes (chilli).
## Rough UK prices (guide for the £30 list)
Eggs (12) ~£2.20 · Chicken 1kg ~£4.50 · Greek yogurt 500g ~£1.50 ·
Cottage cheese 300g ~£1.20 · Tofu 396g ~£1.50 · Lentils 500g ~£1.00 ·
Tinned tuna x2 ~£2.00 · Frozen veg 1kg ~£1.20 · Eggs, milk 2L ~£1.50 ·
Whey 1kg ~£12 (occasional) · Bananas ~£0.90 · Chickpeas x2 ~£1.00 ·
Quark 250g ~£1.10 · Frozen edamame 300g ~£1.80.

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# Protein Targets — Burns Recovery & Fat Loss
User profile this skill was tuned for: recovering burns victim, healing well,
~95100 kg, wants to lose ~15 kg fat while **preserving lean mass**.
## Target math
- Burns recovery + lean-mass preservation during a deficit: **2 g protein per kg
bodyweight per day**.
- At 95100 kg → **~190200 g/day**.
- Split across 2 main meals: aim **~90100 g per meal**; any remainder comes from a
third hit.
- **Recompute whenever the user reports a new weight:** target = weight_kg × 2.
Keep `diet.bodyweight_kg`, `diet.protein_per_kg`, and
`diet.protein_target_g_per_day` in inventory.json in sync with that.
## Fat-loss lever
- Fat loss = a MILD calorie deficit, NOT protein cutting. Bulk meals with veg; limit
oven chips / white bread / added oil; lead with lean protein.
## Closing the gap (third hit)
When 2 cooked meals fall short of the daily target, name one cheap, fast hit:
- Whey protein shake (1 scoop ≈ 25 g) — most cost-efficient per gram; ideal staple.
- Extra eggs (1 egg ≈ 13 g).
- Greek yogurt 150 g (≈ 15 g) or cottage cheese / quark.
- Tinned tuna (≈ 25 g) or skim milk.
## Why red meat is excluded from BUY lists
User prefers to stop buying red meat (lamb / pork / beef / bacon / gammon). Red meat
ALREADY in stock is still cooked and suggested so it isn't wasted — it is never
re-purchased. Encode this as: usable-if-in-stock, never-re-buy.