Tre leve aggiuntive che migliorano la personalizzazione del piano dopo
le tre del commit precedente (BF%, deficit, condizioni mediche).
1. Storia delle diete precedenti (adattamento metabolico)
- Profile.dietHistory ∈ {NONE,SOME,EXTENSIVE,SEVERE} cifrato at-rest
- bmrAdjustForDietHistory: 0.97 / 0.93 / 0.85 — aggiustamento BMR per
riflettere l'adattamento metabolico osservato in studi a lungo termine
(Fothergill 2016 Biggest Loser, Rosenbaum 2008)
- Select in ProfileForm con copy diretto sulla "questione yo-yo"
2. Schedule allenamento (kcal extra training-day)
- Preferences.trainingDays Int[] (0=Lun..6=Dom)
- Preferences.trainingType ∈ {CARDIO,STRENGTH,MIXED,SPORT}
- Preferences.sessionMinutes Int?
- extraKcalForSession: equazione MET (Ainsworth 2011) con MET prevalenti
8/5/6/7 a tipo. Output arrotondato a 25 kcal per evitare false-precisioni
- Plan generation aggiunge l'extra solo nei training days
- Chips Lun-Dom + select tipo + input durata in PreferencesForm
3. Frequenza pasti preferita
- Preferences.mealsPerDay Int? (1..4)
- mealShareForFrequency: 1=solo cena, 2=pranzo+cena, 3=no spuntino, 4=default
- Quando mealsPerDay è impostato e non c'è fastingProtocol attivo,
sostituisce la share del protocollo (il digiuno IF ha precedenza)
- Slot a share=0 saltati alla creazione (niente colazione/spuntino "vuoti")
Schema migration 20260429220XXX_add_lifestyle_fields.
Smoke verificato via API: con mealsPerDay=3 e nessun protocollo IF, ogni
giorno del piano ha esattamente 3 pasti (Colazione+Pranzo+Cena, niente
Spuntino). 54/54 unit test verdi (11 nuovi).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Tre leve per migliorare l'accuratezza del piano oltre Mifflin-St Jeor.
1. Composizione corporea (US Navy + Katch-McArdle)
- Profile: neckCm/waistCm/hipsCm opzionali in input
- bodyFatPct calcolato lato server con la formula US Navy metrica
(Hodgdon-Beckett 1984) e cifrato at-rest come dato sanitario
- BMR usa Katch-McArdle (FFM-based) quando bodyFatPct è noto, Mifflin
altrimenti — più accurato del 5-10% sui casi fuori-norma
- Test: estimateBodyFatPercentageUSNavy + calculateBmrKatchMcArdle
2. Deficit dinamico
- Profile.targetWeeklyLossKg (kg/settimana, opzionale)
- computeDailyKcalTarget calcola il deficit da kg/sett ×7700/7 con due cap
di sicurezza: 30% TDEE (Schoenfeld 2014) e 1% peso/sett (Helms 2014)
- plan.routes lo usa al posto del -500/-200 hard-coded
- Test: 6 casi (mantenimento, transizione, intensiva, cap peso, cap TDEE,
default mancante)
3. Condizioni mediche strutturate
- Profile.medicalConditions (array JSON cifrato)
- 11 condizioni: 7 adattabili (tiroide → BMR -10%, diabete II, IBS,
dislipidemia, ipertensione, reni → cap proteine 0.8 g/kg, fegato →
1.0 g/kg) + 4 escludenti (gravidanza, allattamento, diabete I, disturbi
alimentari)
- PATCH /me/profile/conditions per salvataggio mirato dall'onboarding
- hasExcludingCondition: plan.routes restituisce 409 medical_block se
attiva una condizione incompatibile
Onboarding allargato a 6 step: aggiunto "Condizioni mediche" tra Profile
e Preferences. Step labels e numeri rinumerati.
Schema migration 20260429203451_add_profile_health_fields.
44/44 unit test verdi.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Finora il fastingProtocol era una preferenza salvata ma ignorata dal
planner — ogni giorno generava 4 pasti. Ora cambia struttura per protocollo
e per giorno della settimana.
@ketopath/shared/planner
- protocolPlanForDay(protocol, dayOfWeek) → { share, kcalMultiplier }
- 14:10 → tutti e 4 i pasti, share default
- 16:8 → niente colazione: pranzo 50%, spuntino 10%, cena 40%
- 18:6 → niente colazione: pranzo 55%, spuntino 5%, cena 40%
- 20:4 → solo spuntino+cena (10/90)
- ESE 24h → mercoledì kcalMultiplier=0 (giorno saltato), altri default
- 5:2 → lunedì + giovedì kcalMultiplier=0.25, share 100% cena
- 7 unit test in protocol.test.ts
apps/api/plan
- POST /me/meal-plans: legge preferences.fastingProtocol, deriva il piano
per ogni giorno, salta MealSlot con share=0 e giorni a kcalMultiplier=0
- GET /me/meal-plans/current: include fastingProtocol nella risposta
- baseDailyTarget restituito invariato per il client
apps/web
- /plan mostra "Finestra alimentare 16:8" sotto il titolo della settimana
- plan-week distingue i giorni "fasting" (digiuno completo) e "leggeri"
(5:2 fasting day) con copy dedicato; rimuove totali calorici inappropriati
- i18n: Plan.protocolLabel + Plan.fastingDay/lightDay
Smoke tested: settato 16:8 da /profile, rigenerato il piano, verificato
che l'etichetta appaia e che ogni giorno abbia esattamente 3 pasti
(Pranzo / Spuntino / Cena, niente Colazione).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
ADR 0003: VAPID self-hosted today, DeviceToken model agnostic to
platform so iOS/Android (Expo/APNs/FCM) plug in as new senders later.
Backend (apps/api/src/modules/notifications)
- sender.ts: NotificationSender interface, WebPushSender via VAPID
- notifications.routes.ts: GET /me/notifications/config, POST/DELETE
/me/device-tokens, PATCH /me/notifications/settings, POST /me/notifications/test
- scheduler.ts: node-cron Mon 09:00 Europe/Rome for weekly weigh-in
reminder; auto-cleanup of expired tokens on 404/410
- env: VAPID_PUBLIC_KEY/PRIVATE_KEY/SUBJECT (all optional → push gracefully off)
Frontend
- public/sw.js minimal (push + notificationclick)
- lib/notifications/push-client.ts: subscribe / unsubscribe / getCurrentSubscription
- profile/notifications-{actions,panel}.tsx: editorial panel with toggles,
device list, "send test", per-device removal
- pushReady requires both permission AND active subscription (covers the
case where the user revoked the SW but kept the browser permission)
Schema
- DeviceToken { userId, platform, endpoint, p256dh, auth, token, userAgent,
createdAt, lastSeenAt } with unique(userId, endpoint)
- ExtendedPrismaClient type exported from @ketopath/db
- NotificationSettings zod schema in @ketopath/shared
Tooling
- lint-staged: split .js out of eslint glob so service worker is only
formatted (it lives outside the TS project)
i18n
- Notifications namespace (it) with typed error keys
Smoke tested: POST /me/device-tokens 201, POST /me/notifications/test 200,
real push delivered to a macOS Chrome device.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
@ketopath/shared:
- tracking/schema.ts — Zod schemas for WeightEntry input (weight, optional
measurements/notes/energy/sleep/hunger, photo URLs) and FastEvent start /
update, plus PROTOCOL_DEFAULT_MINUTES table
- planner/macros.ts — macrosForPhase(): protein 1.6-1.8g/kg, netCarb 25/60/120g
by phase, fat = remainder (PRD §9.3)
- planner/matchmaking.ts — pure matchMeals() that filters by exclusion tags,
phase compatibility and meal category, then scores by euclidean distance
from the meal's macro target with a 1.5 penalty for recently-consumed recipes;
DEFAULT_MEAL_SHARE constant (25/35/10/30 %)
- 5 new unit tests cover exclusion, phase, recency, topN, category mismatch
apps/api:
- modules/tracking/weight.routes.ts — GET /me/weight-entries (last 60),
POST /me/weight-entries with upsert on (userId, date); encrypted fields
serialised to/from JSON strings
- modules/tracking/fast.routes.ts — GET, POST (start) and PATCH (update) on
fast events; symptoms stored as encrypted JSON
- modules/plan/plan.routes.ts — POST /me/meal-plans:
- reads profile + preferences, computes BMR (Mifflin-St Jeor), TDEE, daily
kcal target with the phase-dependent deficit, then macros via macrosForPhase
- upserts a MealPlan rooted at Monday-of-this-week, wipes prior slots, and
fills 28 slots running matchMeals per (day, meal) with a recent-2-day
rolling exclusion list to keep variety
- selected recipe + 4 alternatives per slot
- GET /me/meal-plans/current returns the active plan with selected/alternatives
@ketopath/db:
- prisma/seed-recipes.ts — 16 italian keto recipes (4 per meal type) with
estimated macros per serving and phase compatibility
- prisma/seed.ts — idempotent insertion (skip on existing name match)
Verified end-to-end with sign-up → create profile (Michele PRD persona) →
generate plan: 28 slots filled, daily target 1399 kcal / 137 P / 83 F / 25 C,
matchmaking distributes 4 different breakfasts across the first 4 days as
the recent-consumed penalty kicks in.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
@ketopath/shared — new module profile/schema:
- profileInputSchema (Zod): age 18-110, gender, height 120-230 cm, weights
35-300 kg, activityLevel, optional targetDate
- GENDERS / ACTIVITY_LEVELS string-literal arrays for UI iteration
- Re-exported from @ketopath/shared
apps/api — new module modules/profile:
- PUT /me/profile: requireAuth, validates body via profileInputSchema, upserts
the row, returns the saved profile + derived { bmr, tdee, activityMultiplier }
(BMR/TDEE computed via @ketopath/shared)
- GET /me/profile: requireAuth, returns the same shape, 404 when missing
- Decimal columns serialised back as numbers
apps/web — new /profile page:
- src/app/[locale]/profile/page.tsx (server): redirects unauthenticated users
to /sign-in, calls fetchProfile to hydrate the form
- profile-form.tsx (client): react-hook-form + zodResolver bound to the same
shared schema, native styled selects for gender/activityLevel until shadcn
Select arrives, post-submit panel showing BMR/TDEE/multiplier
- actions.ts: server actions saveProfile / fetchProfile that proxy the call
to API_URL via cookie passthrough (no CORS, no exposed token)
- Home page gains a "Completa il tuo profilo" CTA when signed in
- API_URL env var added to .env.example
- Italian copy in messages/it.json under Profile
Verified end-to-end with the "Michele" PRD persona (49, M, 170cm, 76kg, SEDENTARY):
BMR = 1583 kcal, TDEE = 1899 kcal, multiplier 1.2 — matches the unit tests.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Vitest:
- Workspace at root (vitest.workspace.ts) running per-package configs
- packages/shared/vitest.config.ts with v8 coverage and 70% thresholds
- Root scripts: test / test:watch / test:coverage
Nutrition module in @ketopath/shared:
- calculateBmr (Mifflin-St Jeor) + calculateTdee with activity multipliers
- ACTIVITY_MULTIPLIERS constants matching CLAUDE.md domain knowledge
- 14 unit tests covering Michele/Laura PRD personas, all sex variants,
every activity level, and input validation (100% coverage on src/nutrition)
Playwright in apps/web:
- chromium-only project, webServer auto-boot of pnpm dev
- e2e/home.spec.ts smoke test asserts Italian copy and disclaimer
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
