33b7e17ef9
- diet.protein_per_kg 2 -> 1.7 g/kg (evidence ceiling for trained/resistance-adapted adults) daily target 190-200 -> 165-175 g/day, ~80-90 g/meal - weekly non-whey protein floor 1330 -> 1190 g (170 g/day x 7), still excl whey - SKILL.md: RATIONAL PORTIONS hard rule (per-item max_per_meal caps, no single-ingredient overload, honest shortfall reporting); WEEKLY PROTEIN FLOOR (>=3 sources, none >50%) - inventory.json: per-item max_per_meal caps + rational_portions defaults table - scripts/verify_portions.py: regression probe for overload/cap violations - README + references synced to 1.7 g/kg; .idea/.agentbridge gitignored
325 lines
14 KiB
Markdown
325 lines
14 KiB
Markdown
# Meal Suggestion — Kitchen Inventory + High-Protein Meals
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An automated, research-grounded meal system for a single user (jp): a recovering
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burns victim on a **high-protein diet (~165–175 g/day)** who is also losing fat,
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and who wants to **avoid buying red meat**. It does two things on a schedule:
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1. **Daily meal suggestions** — two meals (lunch + dinner) built only from what
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is actually in the kitchen inventory, emailed every day at 09:00.
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2. **Weekly shopping list** — a £30 Lidl basket, themed around a randomly chosen
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world cuisine that week, emailed Mondays at 08:00.
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Sender: `hpm6@txt3.com` (the agent's Gmail, via `smtp.gmail.com:587`).
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Recipient: `jp@txt3.com`.
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> General guidance, **not medical advice** — defer to the user's clinical /
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> dietitian team; keep hydrated on a high-protein intake.
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---
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## Table of contents
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- [How it works](#how-it-works)
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- [Repository layout](#repository-layout)
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- [Core rules](#core-rules)
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- [Egg limit (hard rule)](#egg-limit-hard-rule)
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- [Weekly cuisine rotation](#weekly-cuisine-rotation)
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- [Inventory & meal history](#inventory--meal-history)
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- [Email format](#email-format)
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- [Automation (cron)](#automation-cron)
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- [Scripts](#scripts)
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- [Where to shop](#where-to-shop-eastbourne)
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- [On-demand usage](#on-demand-usage)
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- [Testing & regression guards](#testing--regression-guards)
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- [Git & sync](#git--sync)
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---
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## How it works
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The system is driven by a **skill** (`SKILL.md`) plus two cron jobs that load it.
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On each run the agent:
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- Reads the kitchen **`inventory.json`** (current stock).
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- **Daily:** searches the web for easy, tasty, high-protein budget recipes for
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inspiration, then builds two meals **strictly from in-stock items**, records
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them to `meal-history.json`, and emails them.
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- **Weekly:** picks a cuisine, builds a £30 Lidl basket themed around it, adds a
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per-store price comparison and a health-coverage note, and emails it.
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All generated meals obey the **strict inventory rule**: no ingredient may appear
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that is not already in `inventory.json`. Recipe ideas are only used as
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inspiration; if a recipe needs something not in stock, it is substituted with an
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in-stock item or dropped.
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---
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## Repository layout
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```
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meal-suggestion/
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├── SKILL.md # The operative spec: rules, format, automation
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├── README.md # This document
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├── .gitignore # Excludes live data (inventory/meal-history/cuisine-rotation)
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├── inventory.example.json # Schema example for inventory.json
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├── meal-history.example.json # Schema example for meal-history.json
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├── references/ # Knowledge base the agent reads when generating
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│ ├── email-template.md # HTML email scaffold (inline CSS, mobile-friendly)
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│ ├── food-health.md # Healing + 46yo health + easy/tasty meal research
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│ ├── protein-sources.md # Allowed proteins + example pairings
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│ ├── protein-targets.md # Protein math (1.7 g/kg)
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│ ├── meal-history.md # 7-day logger spec + reconcile-from-inventory logic
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│ └── eastbourne-shops.md # Shop price table (Lidl preferred)
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├── scripts/
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│ ├── pick_cuisine.py # Picks this week's world cuisine (seeded, varied)
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│ └── verify_eggs.py # Regression guard for the EGG LIMIT hard rule
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└── (live, git-ignored)
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├── inventory.json # CURRENT stock — drifts as the user eats/buys
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├── meal-history.json # 7-day rolling log of suggested meals
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└── cuisine-rotation.json # Current + recent weekly cuisine picks
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```
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The live skill directory is `/home/jp/.hermes/skills/meal-suggestion/`; this repo
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is a synced mirror under `~/IdeaProjects/meal-suggestion/`. The two stay in step
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(see [Git & sync](#git--sync)).
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---
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## Core rules
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- **High-protein target:** ~165–175 g/day (≈1.7 g/kg at ~95–100 kg, for burns
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recovery + lean-mass preservation during ~15 kg fat loss). Aim ~90–100 g per
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meal and **state the per-meal and daily protein totals** in the email.
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- **Weight-loss framing:** mild calorie deficit via bulking with veg and going
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easy on chips/bread/oil — **not** by cutting protein.
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- **Red meat:** already in stock is *usable* (use it up, deprioritised), but the
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shopping list must **never suggest buying red meat** (beef, lamb, pork,
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venison, bacon, gammon).
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- **Strict inventory rule:** both daily meals are built ONLY from items in
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`inventory.json`. Nothing invented, assumed, or added.
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- **Tasty & varied:** the agent does a 1–2 query web search for easy, high-protein
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budget meals and draws on real recipes so meals aren't the same plate repeated.
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Prefers no-cook / one-pan / 10–15 min methods.
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- **Health coverage:** meals/items favour wound-healing nutrients (Vit C, Zinc,
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Vit A, Copper, Vit K, iron+VitC) and 46-year-old health (Vit D, B12,
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Magnesium, Omega-3) plus mental + visual acuity (leafy greens, eggs/choline,
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berries, walnuts, olive oil, lutein/zeaxanthin, omega-3 DHA). Noted as gentle
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"health boost" lines, not medical advice.
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---
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## Egg limit (hard rule)
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Eggs were previously overloaded (a day suggested 8 eggs across two egg-bearing
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meals). This is now a **hard cap**, enforced three ways:
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1. **In SKILL.md:** *max 4 eggs per meal; only ONE of the two daily meals may
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contain eggs — the other must be egg-free.* If a meal needs more protein than
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4 eggs supply, close the gap with lentils/beans/halloumi/cheese/tinned fish/
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whey — never a 5th+ egg. This overrides the "lead with eggs" preference.
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2. **In inventory.json:** `diet.egg_rules` carries `max_per_meal: 4` and
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`max_meals_per_day_with_eggs: 1`; the Eggs item note states the cap. Every run
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reads the limit from the data itself.
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3. **In scripts/verify_eggs.py:** a regression guard that checks the persisted
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history against `diet.egg_rules` and exits non-zero on violation. Run it after
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any change to inventory/meal-history or the daily job, and before sending a
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regenerated day's email.
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---
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## Weekly cuisine rotation
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To keep shops and meals varied over time, each week's list is themed around a
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**randomly chosen world cuisine**, driven by `scripts/pick_cuisine.py`.
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- **Stable within a week:** the pick is seeded by the week's Monday ISO date, so
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re-runs / retries of the Monday job never flip the cuisine mid-week.
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- **Varied over time:** the last 4 chosen cuisines are excluded from the pool
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(no back-to-back repeats).
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- **Persisted:** writes the choice to `cuisine-rotation.json`
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(`week_monday`, `cuisine`, `theme_items`) so the **daily job can read it** and
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cook on-theme meals from the same week's buys.
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- **Cuisine pool (all Lidl-achievable on ~£30, high-protein, red-meat-free by
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design):** Mexican/Tex-Mex, Greek/Mediterranean, Indian/South Asian, Thai, East
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Asian/Japanese, Middle Eastern/Levantine, Italian, Korean.
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- **Themes without breaking rules:** the cuisine leads protein/veg/condiment buys
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with its `theme_items`, but still respects £30 budget, protein-first, healing/
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46yo coverage, Lidl-default, and never-buy-red-meat. Pure flavour buys
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(spices/sauces/lime/herbs) are the optional low-price "interest" items.
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The weekly email subject/header shows `Cuisine: <name>`.
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---
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## Inventory & meal history
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**`inventory.json`** — current stock. Schema:
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```json
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{
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"updated": "YYYY-MM-DD",
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"diet": {
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"goal": "high-protein",
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"avoid_purchase": ["red meat"],
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"egg_rules": { "max_per_meal": 4, "max_meals_per_day_with_eggs": 1,
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"note": "..." },
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"age_years": 46, "bodyweight_kg": "95-100",
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"protein_per_kg": 2, "protein_target_g_per_day": "190-200",
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"weight_loss_goal_kg": 15
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},
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"items": [
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{ "name": "Eggs", "qty": 10, "unit": "count", "category": "protein",
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"notes": "Hard cap: max 4 eggs per meal; only ONE of the two daily meals may use eggs." }
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]
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}
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```
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- `category` ∈ `protein, veg, fruit, dairy, grain, tinned, frozen, condiment, other`.
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- **You own the inventory.** When the user says they *used/consumed* ingredients,
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decrement/remove them (via the `patch` tool) and bump `updated`. When they
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*bought* items, add/increase them. The daily email only *proposes* meals — it
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does **not** auto-consume.
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**`meal-history.json`** — rolling 7-day log. The daily job **UPSERTS** today's two
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entries (replaces same `date`+`meal`, so re-runs don't duplicate) and **prunes**
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entries older than 7 days. Each entry:
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```json
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{ "date": "YYYY-MM-DD", "weekday": "Thursday",
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"meal": "lunch", "name": "Halloumi & Red Lentil Power Bowl (egg-free)",
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"items": [{ "name": "Halloumi", "qty": 100, "unit": "g" }] }
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```
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Only substantive food items are logged — pure condiments and the optional
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"third hit" snack are not. This log is what the on-demand inventory-removal
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feature reconciles against.
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---
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## Email format
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Sent via `python3 /home/jp/.hermes/scripts/meal/send_meal_email.py` (reads SMTP
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creds from `~/.hermes/.env`). Both HTML (inline CSS, mobile-friendly, dark-on-light)
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and a plain-text alternative are produced so the plan survives HTML-stripping
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clients.
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- **Daily:** header (date + `high-protein · ~165–175g/day · no red meat bought`),
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two meal cards (name, ingredients, 2–3 step method, protein total, short
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"health boost" note), footer (`Reply to tell me what you used and I'll update
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the inventory`).
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- **Weekly:** shopping table (item, est. price, running total ≤ £30, Total row),
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header with `Cuisine: <name>`, a "health coverage" note (healing + brain + eyes
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+ 46yo + cuisine theme), a "Same basket — where else?" per-store comparison
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table, and a "Same basket — where else?" plain-text mirror.
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---
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## Automation (cron)
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Two cron jobs (created via the `cronjob` tool), both loading the
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`meal-suggestion` skill:
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| Job | Schedule | Purpose |
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|-----|----------|---------|
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| Daily meal suggestions | `0 9 * * *` | 2 in-stock meal suggestions → email |
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| Weekly shopping list | `0 8 * * 1` | £30 cuisine-themed Lidl basket → email |
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Delivery is `local` (the email is the deliverable); check `cronjob action=list` /
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logs if a send seems missing. The weekly job runs `pick_cuisine.py` **first**,
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then themes the basket; the daily job reads `cuisine-rotation.json` and prefers
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on-theme cooking while still obeying the strict inventory rule and the egg cap.
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---
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## Scripts
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### `scripts/pick_cuisine.py`
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Picks this week's cuisine.
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- `python3 scripts/pick_cuisine.py` — pick (or reuse this week's) and persist.
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- `python3 scripts/pick_cuisine.py --dry-run` — print only, do not write.
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- Prints JSON: `{"week_monday", "cuisine", "theme_items", "reused"}`.
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- Seeded by the week's Monday → stable within a week; excludes the last 4
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cuisines → no back-to-back repeats.
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### `scripts/verify_eggs.py`
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Regression guard for the EGG LIMIT contract. Reads `inventory.json`
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(`diet.egg_rules`) and `meal-history.json`, checks no meal exceeds
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`max_per_meal` and no day exceeds `max_meals_per_day_with_eggs`. Exits non-zero
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on violation. Run after any change to the egg logic or before sending a
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regenerated day.
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---
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## Where to shop (Eastbourne)
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User preference (confirmed): **Lidl is the preferred shop** — a weekly trip, so
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the extra distance is fine; best value and leaves budget for essential
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micronutrients and the occasional treat. Others (Tesco Express, Sainsbury's,
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Co-op, Londis) are comparison/fallback only.
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Grounded in Which? 2026 (93-item basket; Lidl ≈ £160.70 baseline):
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- Lidl ≈ 1.00x — cheapest, preferred
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- Tesco superstore w/ Clubcard ≈ 1.17x; Tesco Express ≈ 1.22x
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- Sainsbury's w/ Nectar ≈ 1.17x
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- Co-op ≈ 1.30x (membership = annual dividend)
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- Londis ≈ 1.25–1.35x (milk 2L £1.40 is a confirmed cheaper line)
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The weekly email shows a "Same basket — where else?" comparison (Lidl / Tesco
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Express Clubcard / Sainsbury's Nectar / Co-op member / Londis) as **estimates**
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from the Which? 2026 ratios + known local prices — no live web search. Default is
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a single Lidl shop; split only when a specific item's local price is *definitely*
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known lower.
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---
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## On-demand usage
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- **"What should I eat today?"** — read `inventory.json`, suggest now, offer to email.
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- **"Remove Wednesday's dinner from inventory"** — resolve the entry, decrement
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each logged item from `inventory.json` (remove if ~0), skip items not present,
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bump `updated`, confirm. Works per-item and partial-consumption overrides too.
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- **Adding stock** — list items in chat; they're added to `inventory.json` and an
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immediate 2-meal suggestion can follow.
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---
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## Testing & regression guards
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- `python3 scripts/verify_eggs.py` — asserts the EGG LIMIT holds across
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`meal-history.json` using the persisted `diet.egg_rules`. Should print
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`PASS: egg limit OK (max 4/meal, max 1 egg-meal/day)`.
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- The cuisine picker is deterministic per week (Monday-seeded) and was verified to
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produce no consecutive repeats across 8 simulated weeks.
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---
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## Git & sync
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This repo (`~/IdeaProjects/meal-suggestion/`) is the version-controlled mirror of
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the live skill (`/home/jp/.hermes/skills/meal-suggestion/`).
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- **Live data is git-ignored:** `inventory.json`, `meal-history.json`,
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`cuisine-rotation.json`, and `__pycache__/`. Only the spec, references,
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examples, and scripts are committed.
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- **Sync workflow:** copy the changed source files (currently `SKILL.md` and
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`scripts/`) from the live skill dir into this repo, then commit. Keep
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`.gitignore` excluding live data in both places.
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```bash
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# from /home/jp/.hermes/skills/meal-suggestion
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cp SKILL.md /home/jp/IdeaProjects/meal-suggestion/SKILL.md
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cp scripts/pick_cuisine.py scripts/verify_eggs.py \
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/home/jp/IdeaProjects/meal-suggestion/scripts/
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# commit the mirror
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cd /home/jp/IdeaProjects/meal-suggestion
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git add -A && git commit -m "Sync: egg-limit hard rule + weekly cuisine rotation"
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git push
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```
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Version history of the mirror:
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- `72ce56e` Initial meal-suggestion skill (logic + template; live data git-ignored)
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- `c5f4fb1` Sync: food-health research, mackerel, easy/tasty + acuity, weekly health-coverage
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- `9e44876` Sync: strict inventory-only rule for daily meals
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- *(current)* Sync: EGG LIMIT hard rule + weekly cuisine rotation + scripts
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