`aggregate=daily|weekly|monthly` averaged step counts (and every
other cumulative HK type) instead of summing — partial-day rows
collapsed to a per-bucket mean rather than the daily total.
Five rows of 1000 steps reported 1000, not 5000.
Add `CUMULATIVE_HK_TYPES` in `apple-health-mapping.ts` listing the
five cumulative MeasurementTypes the iOS / Withings ingest path
emits (`ACTIVITY_STEPS`, `ACTIVE_ENERGY_BURNED`, `FLIGHTS_CLIMBED`,
`WALKING_RUNNING_DISTANCE`, `TIME_IN_DAYLIGHT`). The route picks
`SUM(value)` for those types and keeps `AVG(value)` for every spot
metric (BP, pulse, weight, BG, body fat, mood, sleep).
Two new integration cases pin the contract: a step day collapses
to the per-row sum; a pulse day still averages.
The `aggregate=daily|weekly|monthly` branch on `GET /api/measurements`
500'd in production for every grain. Two root causes that the
mocked-`$queryRaw` unit suite hid end-to-end:
1. `date_trunc(${truncUnit}, …)` passed the grain as a bound
parameter; Postgres rejects — the unit argument must be a SQL
literal. Switch to `Prisma.raw` for the unit string; safe because
the grain is upstream-restricted to the `AggregateGrain` Zod enum.
2. The `daily → day` mapping ignored the `weekly` and `monthly`
forms; Postgres rejects those as units. Map all three grains to
the singular Postgres unit (`day` / `week` / `month`).
The user-id cast `${type}::"MeasurementType"` also referenced a
non-existent type name; the actual Postgres enum is `measurement_type`.
Corrected alongside.
Add `tests/integration/measurements-aggregate-daily.test.ts` against a
real Postgres so every grain compiles + executes end-to-end. The
mocked unit suite stays for the route-shape contracts.
The batch ingest route lives under /api/measurements, not the Coach.
Aligns the errorCode with the sibling DELETE route, which already
emits measurement.delete.too_large.
The W17b/c sleep-stage migration widened the measurement unique
index to (user_id, type, measured_at, source, sleep_stage) with
NULLs treated as not-distinct, so three same-instant APPLE_HEALTH
weight rows now collide on insert. Derive a stable per-externalId
minute offset and stagger the seeded `measuredAt` accordingly so
the deletion-by-externalId contract is exercised without piggy-
backing on dedup behaviour the route doesn't care about.
W5 added `defaultWindow` to the coach-prefs schema with `"allTime"`
as its default, so the PUT handler now returns the canonical
defaulted shape even when the caller omits the field. Update the
integration round-trip to expect the defaulted form on both the
response envelope and the persisted row.
The hard-coded "2026-05-14T13:00:00.000Z" reading was due to fall out
of the snapshot's 14-day `recent` window two weeks after the suite
landed, deterministically breaking the assertion. Anchor the instant
to "today minus 2 days at 13:00 UTC" so it always sits inside the
window, then derive the expected Auckland / Berlin day-keys from
that instant. Keeps the test asserting the same tz-divergence
invariant without baking a calendar date into the suite.
Adds the integration suite for the detection worker against a real
Postgres testcontainer. Covers measurement-driven PRs (steps,
RHR, VO2 max), idempotency on re-run, silent-flag propagation,
and the drift guard that every PR-trackable metric type lands in
the scan loop.
Also patches a pre-existing schema gap: the
(userId, metricType, metricSlot, achievedAt) unique index on
personal_records is NULLS-DISTINCT in Postgres, so the index alone
does not dedup the measurement-driven rows (metricSlot = NULL).
The worker now does an application-level pre-flight findFirst on
the same composite key before each insert, keeping both the
workout path (index covers it) and the measurement path
(application-level guard) idempotent without a Migration.
New `syncUserSleep` routine pulls per-segment sleep data from
POST /v2/sleep?action=get and writes one Measurement row per stage
segment, tagged with the appropriate SleepStage enum:
state 0 (awake) → AWAKE
state 1 (light sleep) → CORE (HealthKit-aligned NREM 1+2)
state 2 (deep sleep) → DEEP
state 3 (REM) → REM
state 4 (synthetic) → ignored
The legacy ASLEEP and IN_BED enum slots stay reserved for HealthKit
ingest (pre-iOS-16 `asleepUnspecified` and iOS-16+ `inBed`).
ScanWatch nights with no REM segment simply omit the row rather than
synthesising an all-zeros entry — Withings drops the field, the writer
never sees it.
Idempotency rides on Migration 0055's five-column composite — a re-sync
of the same night UPDATEs every segment row in place rather than
inserting duplicates, even when Withings re-aggregates the night with
adjusted segment boundaries.
Sleep durations stored as canonical minutes (seconds ÷ 60, rounded) so
re-syncs don't flip values on floating-point noise.
New `syncUserActivity` routine pulls daily aggregates from
POST /v2/measure?action=getactivity and writes one Measurement row per
(date, metric) for three fields:
steps → ACTIVITY_STEPS (count)
distance → WALKING_RUNNING_DISTANCE (metres)
calories → ACTIVE_ENERGY_BURNED (kcal)
`elevation`, soft/moderate/intense/active duration and
`totalcalories` are deliberately skipped — no clean MeasurementType
counterpart today; revisit when v1.5 ships the iOS workout passthrough.
Rows anchor measuredAt at the day's 23:59:59 UTC end-of-day so the
Berlin-timezone analytics aggregator buckets them into the correct
local day even across DST shifts. Idempotency rides on the W17b
composite (Migration 0055, NULLS NOT DISTINCT) — repeat syncs of the
same date update value in place rather than inserting duplicates.
Park behaviour mirrors syncUserMeasurements: connections at
error_reauth short-circuit without making the upstream call.
The Withings Sleep v2 sync writes one Measurement row per stage segment
(AWAKE | CORE | DEEP | REM) for the same night, all sharing the legacy
four-column composite (user_id, type=SLEEP_DURATION, measured_at,
source=WITHINGS). Migration 0055 adds sleep_stage as the fifth axis and
recreates the unique index with NULLS NOT DISTINCT so non-sleep rows
(sleep_stage IS NULL) still dedup on the first four columns — same
effective semantics as before for every meastype other than SLEEP_DURATION.
Prisma's generated compound input requires non-null fields, so the
Withings sync's upsert is reshaped as findFirst + create/update for the
non-sleep path (sleepStage is always NULL there). The new five-column
upsert key is the canonical path for the Sleep v2 ingest landing in W17c.
Unit + integration coverage for POST /api/workouts/batch.
Unit (database-free, mocks the Prisma layer):
- 401 on unauthenticated calls
- 413 when Content-Length exceeds the 5 MB ceiling, with the
documented workout.batch.payload_too_large error code
- 429 when the rate-limit gate blocks the call
- 400 when the workouts array exceeds the 100-entry cap
- 400 when the Zod schema rejects the payload
- 400 when a route exceeds the 20 000-point cap
- Fresh entries marked inserted
- Pre-existing entries flagged duplicate without re-inserting
- Race-reconciliation downgrades inserted statuses to duplicate
when createMany.count is below the attempted-row count
- WorkoutRoute rows attached by FK after the workout createMany
Integration (real Postgres in a testcontainer):
- Happy-path single workout with nested route lands as a Workout
row + WorkoutRoute row + 1:1 FK + computed durationSec
- 100-workout batch with mixed routes lands all 100 workouts and
exactly the expected number of route rows
- Over-cap batch (101 workouts) returns 400 with
workout.batch.too_large
- Over-cap route (20 001 points) returns 400 with
workout.batch.invalid
- Re-posted batch surfaces as duplicates without inserting twice
- Idempotency-Key replays the cached envelope and sets the
X-Idempotent-Replay header
- Pre-seeded rate-limit row triggers 429 and writes nothing
- Narrow-scope Bearer token admitted on a route that declares no
required permission (the W10 fix-C correctness fix the iOS
narrow-scope sync depends on)
Concurrent-write integration coverage that validates the W10 fix-C
reconciliation pattern carries over correctly to the
/api/workouts/batch endpoint:
- Two batches with overlapping (userId, source, externalId) tuples
posted in parallel resolve to exactly one DB row per tuple (the
composite unique index enforces it; createMany.skipDuplicates
absorbs duplicate-key conflicts).
- Each response body's per-entry envelope sums to its own
aggregate counts — the invariant the iOS sync cursor relies on
to checkpoint correctly.
- Aggregate inserted counts across both responses equal the row
count actually present, cross-validating that createMany.count
is the truth source rather than the older
'stored vs not-stored' diff (which was a no-op under standard
Postgres semantics because every attempted row IS in the DB
after the call, written by whichever batch won the race).
- A two-batch shared-key fixture asserts the shared tuple lands
exactly once across both responses.
Also adds workouts and workout_routes to the integration suite's
truncate list so beforeEach() actually clears them between tests
rather than relying on CASCADE from users.
The previous race-reconciliation block compared post-insert rows in
the DB against the rows we attempted to insert, downgrading any
"inserted-but-not-stored" entries to "duplicate". Under standard
Postgres semantics that branch never fires: `skipDuplicates`
absorbs duplicate-key conflicts but the row is still present in the
table (written by the other batch that won the race). So every
attempted row was "stored" and the loop ran as a no-op, leaving
the per-entry envelope inconsistent with the aggregate counts when
two batches collide. The v1.5 iOS sync cursor depends on the
envelope sums matching the aggregate counts to checkpoint
correctly.
Pragmatic fix: trust `createMany.count` for the aggregate
`insertedCount` and downgrade exactly `toInsert.length -
insertedCount` per-entry "inserted" statuses to "duplicate". The
post-fix loop no longer touches `insertedCount` (it was already
correct from createMany) so the count cannot drift negative. Order
doesn't matter for the client — both statuses checkpoint past the
row and the DB ends up with the same single-copy state.
Concurrent-write integration test asserts the three invariants the
iOS sync cursor relies on: per-entry sums equal aggregate counts,
aggregate counts stay non-negative, and the DB row count matches
the combined `inserted` total.
The Apple Health batch endpoint accepted 500-row payloads with no
per-user write cap. A leaked wildcard iOS token could sustain
unbounded inserts (500 rows × N batches/sec) and degrade the
database for every other user on the host.
Gate the write path with the shared `checkRateLimit` helper at
60 batches/min/user — generous for legitimate iOS sync (the
HealthKit observer coalesces well below one batch/minute on a
quiet device, and 60/min × 500 rows = 30 000 rows/min headroom)
and tight enough that a misbehaving client bottoms out within a
minute. Returns 429 with an unambiguous message so the iOS
client can back off and retry rather than assume the row landed.
Integration test exercises the over-limit path by pre-seeding the
`rate_limits` counter at the cap.
The W7 per-user-tz sweep threaded `userTz` through every aggregator on
the analytics route except `berlinIsoWeekday()` — the module-level
`Intl.DateTimeFormat` stayed pinned to `Europe/Berlin`. A user in
`Pacific/Auckland` whose 23:30 weight reading lands at 12:30 the same
day in Berlin had their Monday-local reading bucketed under Sunday's
weekday column. Pearson/ANOVA on the wrong weekday.
Replace the pinned formatter with a per-tz memoised lookup, rename the
helper to `isoWeekdayInTz()`, and feed `userTz` through the call site.
Also rename the misleading `dateFromBerlinKey()` → `dateFromDayKey()`
since the keys it consumes are already anchored to the user's tz
upstream.
Integration test covers the non-Berlin path: 28 weight readings at a
UTC instant where the Berlin and Auckland weekdays disagree; the
correlator reaches the gate with every seeded row counted, confirming
the helper used the user's tz to bucket.
Lock the GET /api/analytics wire-up to the new two-axis picker with a
fixture-driven test that drives a real Postgres testcontainer + the
production handler. Four scenarios on the same Berlin day:
1. Plain default user (single source, no override) — picker passes
through; v1.4.25-today behaviour stays a regression sentinel.
2. Per-metric override (sleep: [WITHINGS, APPLE_HEALTH]) — flips
the default APPLE_HEALTH-first ladder; Withings row wins.
3. Per-device default (no user override) — Apple Watch row beats
iPhone row under same source on default ladder (watch first).
4. User flips device ladder to [phone, watch] — iPhone row wins.
Wire-up: analytics' fetchMeasurementSeriesChunked now selects
deviceType + type on every chunk so the picker can read both axes.
ChunkedRow gains two fields; all existing aggregation paths continue
to compile and the integration suite stays green (6/6 passing across
analytics-sleep-stages.test.ts + source-priority-two-axis.test.ts).
Unit tests already cover the picker's internal edge cases (45 unit
across helper + algorithm); this file is the end-to-end guard.
7 conflict files resolved by taking the upstream/HEAD side (which carries
the W4d/W5/W6c/W3f feature additions). Stashed-side changes that were
genuine new features re-land in subsequent commits if any were lost.
This sweeps up the loose state the W4e+W5e+W5d combined agent left
mid-stash. Resolves develop's working tree for clean push.
The Settings → Dashboard sub-section's Save button silently 422'd once
the user had touched any per-chart overlay popover. Root cause was a
Zod v4 semantics change: `z.record(z.enum(KEYS), ...)` now requires
every enum key to be present in the input, where Zod v3 treated the
same shape as a partial record. Real-world Save payloads only carry
the chart keys the user actually toggled, so every Settings → Dashboard
Save attempt with one or two `chartOverlayPrefs` entries failed with
`expected: object, path: ["chartOverlayPrefs", "<missing-key>"]` and
the toast surfaced "Layout konnte nicht gespeichert werden".
Fix uses `z.partialRecord(z.enum(KEYS), ...)` which preserves the
original v1.4.18 intent — per-chart opt-in overlay prefs, missing keys
filled by the resolver. The inner object now also accepts the
`comparisonBaseline` field so a Settings save preserves the per-chart
comparison toggle the user set via the chart-card popover (otherwise
Zod's default strip behaviour wiped it on every save).
New integration suite pins:
- partial chartOverlayPrefs round-trips
- per-chart comparisonBaseline survives a Settings save
- empty chartOverlayPrefs still persists (fresh accounts)
- widget toggle changes land in the DB
Up to v1.4.24 the snapshot's day-key and weekday labels ran through
utcDayKey() / utcWeekday() / isoWeekKey(), so a 23:50 Pacific/Auckland
reading was filed under the next UTC day and the Coach replied with
the wrong calendar. The pipeline now reads User.timezone (alongside
the existing coachPrefsJson read so the read budget is unchanged) and
threads it through every bucketing helper (dailyMeans, bucketWeekly,
buildDailyValueRows, buildDailyBpRows) plus the medication-compliance
day-roll-up and the Apple Health additive blocks.
The prompt-budget calculator (src/lib/ai/coach/budget.ts) is unaffected.
The ledger still uses UTC midnight for spend roll-over because the
operator's LLM bill cycles on UTC; only the SNAPSHOT itself shifts to
the user's calendar. The provenance counts are row counts, not day
counts, so no provenance drift either.
Integration test pins the boundary: a 13:00 UTC May 14 reading (=
01:00 NZST May 15) appears under "2026-05-15" in the Coach snapshot
for a Pacific/Auckland user. The same instant in Berlin would land on
May 14; the test asserts the snapshot does NOT bucket there.
Existing 88-test coach unit suite stays green (the mocked user row
returns no timezone, so the snapshot falls back to Europe/Berlin and
the v1.4.24 byte-shape holds).
HealthKit's API does not surface a stream of deleted UUIDs, so the iOS
HealthLog client performs a periodic 30-day reconciliation: it diffs
HealthKit's current UUID set against the server's externalIds and
posts the surplus here. This endpoint deletes the user's matching
rows and never touches another user's data (Prisma's deleteMany with
the userId predicate is the cross-user 404 guard).
Contract:
- Body: { externalIds: string[] } with min 0, max 500 entries.
- Auth: requireAuth() — session cookie or bearer.
- Empty array: returns { deletedCount: 0 } with 200 (no-op, not a
failure — matches the ingest path's symmetric tolerance).
- Over-cap: 422 with errorCode "measurement.delete.too_large" so
the iOS client can surface a specific diagnostic.
Integration coverage: happy path, cross-user 404 guard, empty array,
and batch-cap rejection. The cap (500) mirrors POST /measurements/batch
so the two surfaces share one operational ceiling.
OpenAPI: registered as DELETE on /api/measurements/by-external-ids
with the Measurements tag; req/res schemas reuse the same z.array cap
the runtime validator enforces. openapi.yaml regenerated.
Four chart components (HealthChart, MoodChart, MedicationComplianceChart,
ComplianceLineChart) now accept a userTimezone prop, default
"Europe/Berlin" for backwards compat. Inside each chart, the X-axis
tick formatter, tooltip date label, and per-day bucketing all run
through a tz-aware makeFormatters(locale, userTz) instance instead of
the legacy formatDateShort() which pinned to Europe/Berlin.
Mount sites that already pull useAuth() pass user?.timezone:
dashboard /page.tsx, trends-row, recommendation-card,
insight-advisor-card. Ad-hoc usages without a user (storybook-style
or test harnesses) keep the default Europe/Berlin rendering
bit-for-bit.
The HealthChart's daily-aggregation key (toDayKey) was also rewritten
to depend on the userTimezone prop so a 23:50 Pacific/Auckland reading
buckets to the Auckland day instead of the Berlin day for chart data
display. The TanStack Query cache key gains userTimezone so a tz
change inside a session re-fetches and re-buckets correctly.
Tests: 109 chart-component tests stay green.
The four routes that bucket by Berlin calendar day (dashboard summary,
medication intake, analytics correlations and sleep, insights targets)
now read userTz from the authenticated User and pass it through
userDayKey(). Streaks and consistency strips for a Pacific/Auckland user
land on their Auckland-day, not the legacy Berlin-day.
The aggregation logic is unchanged — only the bucket key function
swaps from berlinDayKey(date) to userDayKey(date, userTz). Existing
Berlin users see no behaviour change (Europe/Berlin is the schema
default).
Integration test extended with a two-case assertion: the userDayKey()
boundary case (13:00 UTC May 14 → 2026-05-15 Auckland vs 2026-05-14
Berlin) and the dashboard summary route returning a non-zero streak for
an Auckland account with three consecutive Auckland-day measurements.
v1.4.25 W7 phase 7 — proposal §6.4 test strategy applied.
Seven cases cover the full per-user-tz pipeline against the
integration testcontainer:
1. CSV export for an Auckland user emits '+12:00' on measuredAt,
never the bare 'Z'. This is the issue #167 fix from the user's
end-to-end perspective: an Auckland user's exported spreadsheet
carries unambiguous local time.
2. CSV export for an Asia/Tokyo user emits '+09:00' (no DST in
Japan, deterministic offset year-round).
3. CSV export with no userTz (legacy library callers — admin tools,
canonical backup-on-disk) keeps the 'Z' suffix. Protects the
backward-compatibility path.
4. PUT /api/auth/me/timezone writes the new zone, the user row
reflects it, AND the in-process resolver cache returns the new
value immediately (the route invalidates on write — proves the
evict path works without waiting 60s for the TTL to roll).
5. PUT /api/auth/me/timezone rejects an invalid IANA zone with
422 and does not touch the column.
6. POST /api/auth/register captures a browser-detected zone from
the signup payload onto User.timezone.
7. POST /api/auth/register falls back to Europe/Berlin when the
payload's zone is invalid. The 'admin server default'
intermediate fallback layer is exercised by the unit suite —
the integration test runs against a testcontainer whose
migration history doesn't carry every AppSettings column,
so setting a non-NULL default would error before the route
runs. Documented inline.
The Coach snapshot's UTC bucketing (proposal §3 symptom 9) is
intentionally NOT asserted — that surface is deferred to a
follow-up wave because the snapshot's day/week bucketing pipeline
is a separate refactor that touches the prompt budget calculator.
The two failing cases in tests/integration/coach-prefs.test.ts were invoking
the route's GET handler with zero arguments — `(GET as () => Promise<Response>)()`.
The apiHandler wrapper at src/lib/api-handler.ts:46-47 reads args[0].url to
build the Wide Event `http.path`, so the call threw
`TypeError: Cannot read properties of undefined (reading 'url')` before the
route body ever ran. Other integration tests already pass a real Request to
GET (see analytics-health-score, chart-overlay-prefs); aligning this test to
the same pattern restores parity with production where Next.js always
invokes route handlers with a Request.
The api-handler wrapper itself was left untouched — defending against a
caller passing undefined would mask the same bug in any future test.
Mostly table column normalisation under docs/audit/ + planning, object-
literal expansion in src/lib/ai/coach/snapshot.ts after the W4 F6 Apple
Health metric block landed, and small wrap/unwrap line adjustments in
the device + APNs routes / tests touched across W3/W4/W5 sessions.
No behavioural change.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Reviewer note: W5 H7 wrote Coach assistant prose plaintext into
recommendation_feedback.recommendation_text. Same prose lives
encrypted in coach_messages — backups captured the leak.
Migration 0042_coach_feedback_message_ref adds nullable coachMessageId
(FK + cascade) and drops recommendation_text. Aggregator joins +
decrypts on read; admin view reads through the same path.
Fixes: Sr-H3 (Wave-6 v1.4.23 senior-dev review)
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Reviewer note: src/app/api/analytics/route.ts fanned out 17+
unbounded prisma.measurement.findMany per request — growth linear
in HealthKit-days. Replace with prisma.groupBy where possible;
chunked-paged with take=5000 where running-window slope or paired
correlations require row-level access. Wide-event annotation
analytics.bp_aggregate.row_count for slow-query attribution.
Fixes: Sr-H1 (Wave-6 v1.4.23 senior-dev review)
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The dispatcher's APNS branch only fires when a NotificationChannel of
type APNS exists for the user, but no production code path created one.
Every iOS install needed a manual settings toggle that doesn't exist,
making the v1.4.23 W3 APNs cascade unreachable in real traffic.
When `POST /api/devices` accepts an apnsToken, eagerly upsert the
channel row with an encrypted empty config — the per-device token and
environment live on the Device row by design, so the channel only
exists to flip the dispatcher's gate. Mirrors the legacy Telegram
on-first-dispatch auto-migration but eager so the very first reminder
after registration routes through APNs.
Adds an integration test that registers a device with apnsToken and
asserts the channel row exists, registers without one and asserts
absence, and re-registers the same apnsToken and asserts idempotency
(channel count stays at one).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The v1.4.22 prose rewrite shipped without a way for users to signal
whether the new tone is landing. v1.4.23 H7 closes that loop with a
light-touch thumbs row + an admin first-week dashboard.
Schema: extend `RecommendationFeedback` with a polymorphic
`target_type` column (default "recommendation" so legacy rows stay
representative) plus a nullable `reason` field. New index on
(target_type, created_at) so the aggregator can scan per-surface
buckets without a full sweep. Migration `0040_recommendation_feedback_target_type`.
Route: POST /api/insights/chat/messages/:id/feedback. Body
{ rating: "helpful" | "unhelpful", reason?: string }. Verifies
ownership (404 on cross-account messages — no existence leak),
decrypts the message body for the dedup key, and writes the row with
target_type="coach" + a metric-source string encoding the user's
active prefs (`coach:tone=warm:verbosity=default`). Per-user 60/h rate
limit. 409 on a P2002 (already_rated) so a double-click is a no-op.
Aggregator: new `buildCoachFeedbackBuckets()` slices Coach rows by
(promptVersion, tone, verbosity). The summary blob the worker writes
to AppSettings.adminAiInsightsFeedbackSummary now carries both
`buckets` (pre-existing) and `coachBuckets` (H7 addition). Targets
the same singleton row so no second worker handler is needed.
Admin view: `/admin/coach-feedback` (new section slug) renders the
Coach buckets as a small DataTable (prompt version × tone × verbosity
× helpful × not-helpful × n × helpful-rate). Helpful-rate column
tinted via Dracula tokens (green ≥80%, yellow ≥50%, orange below).
First useful question this answers: "Is the v1.4.22 prose rewrite
landing well, or did the warm tone overshoot?" If the helpful-rate
for PROMPT_VERSION 4.23.x drops below 50% within the first 100
ratings, v1.4.24 walks the persona back.
UI: `<ThumbsUp>` / `<ThumbsDown>` buttons (lucide icons, no emoji)
under each persisted assistant bubble. Streaming bubbles + refusals
+ error bubbles skip the row so users can't rate before the message
lands on disk. Localised "Thanks for the signal." after submit.
OpenAPI: spec carries the new POST route + the request schema.
Coverage now includes the H4 + H7 routes — three additions over
v1.4.22 baseline.
Tests +9 unit (aggregator Coach-bucket slicing, admin section
render-paths) plus an integration round-trip for the route.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The v1.4.22 B5 audit removed the placeholder cog from the Coach
drawer header because it had no real wiring. v1.4.23 H4 returns
the cog with an actual settings surface backed by a per-user
preferences row.
Schema: nullable JSONB column `users.coach_prefs_json` (migration
0038_coach_prefs). Null = legacy v1.4.22 defaults; non-null carries
`{ tone, verbosity, excludeMetrics, showEvidenceByDefault }` validated
by the Zod schema in `src/lib/validations/coach-prefs.ts`.
Routes: GET + PUT `/api/auth/me/coach-prefs`. PUT validates the body,
persists the canonical defaulted form, and emits an
`auth.me.coach-prefs.put` annotation with the four-knob meta. OpenAPI
registry covers both verbs; the spec regenerates without drift.
Coach prompt builder: `getCoachSystemPrompt(locale, prefs)` prepends a
per-user OVERRIDE paragraph for non-default tone (neutral / concise)
and verbosity (brief / detailed). Concise tone forces brief verbosity
regardless of the explicit selection — concise == short. Default
prefs leave the prompt unchanged so the v1.4.22 train stays in place.
Snapshot builder: reads the prefs row BEFORE any measurement query
and intersects `excludeMetrics` with the resolved scope. The model
never sees data the user opted out of — that's the load-bearing
order: filter first, query second.
UI: settings cog in the drawer header opens a right-edge `<Sheet>`
with three Select pickers (tone, verbosity) and one Switch column
(per-metric exclusions + showEvidenceByDefault). Save calls the PUT
route and invalidates the `["coach-prefs"]` query so the next reply
honours the new defaults without a reload. EN + DE i18n keys for
every label and hint.
Message-thread reads the same `["coach-prefs"]` cache and toggles the
`open` attribute on the evidence `<details>` element when
`showEvidenceByDefault` is true.
Tests +24 unit (coach-prefs schema, system-prompt prefix, snapshot
mock for new prefs row). Integration round-trip seeds a session,
PUTs a non-default prefs shape, asserts the GET reflects the saved
values + the DB row carries the canonical defaulted form.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The W2-of-v1.4.20 BD-Zielbereich fix needed the complete sys + dia
series to compute the all-time + prior-month + prior-year windows,
so it pulled both tables via single-shot `findMany`. For a 5-year
power user (~9 000 rows per side) that's a 50-100 ms Prisma round-
trip and a ~2 MB working-set allocation per /api/analytics request.
Switch to a cursor-paged 5 000-row chunked read via the new
`fetchBpSeriesChunked()` helper. The accumulated `BpReading[]` is the
same shape `computeBpInTargetWindows()` already consumed; the
working-set ceiling is now `BP_CHUNK_SIZE` instead of unbounded. Safety
bound at 1 000 pages = 5 M rows so a cursor-staleness bug can't loop
forever.
Wide-event annotation `analytics.bp_in_target.row_count` (+ per-side
`sys_rows` / `dia_rows`) lets ops attribute slow requests to outlier
users without rerunning the DB queries.
Integration test seeds a 6 000-row dataset (3 000 sys + 3 000 dia)
spanning a chunk boundary and asserts the response shape stays the
same — last30Days, last7Days, allTime windows all carry the
hand-derivable percentages.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
23 unit tests under `senders/__tests__/apns.test.ts` exercise:
* env-var loader — all-or-none guard, inline-PEM `\n` unescape, file
fallback path, cache, APNS_PRODUCTION override
* Provider lazy-init + per-gateway cache (sandbox vs production stay
isolated; APNS_PRODUCTION funnels every send through production)
* permanent-failure detection (`Unregistered`, `BadDeviceToken`,
`DeviceTokenNotForTopic` flip `shouldDisable: true`; transient
reasons stay false)
* `sendViaApns()` dispatcher entry — fan-out, dead-row cleanup,
hard-vs-soft channel-reject classification, HTML stripping
3 integration tests under `tests/integration/apns-dispatch.test.ts`
drive the real dispatcher against a Postgres testcontainer with a
stubbed `@parse/node-apn` Provider:
* Round-trip: notification fans out via APNs and the channel-state
machine records `lastSuccessAt` + clears any cooldown
* Failure path: `Unregistered` deletes the dead Device row,
auto-disables the channel with the captured reason, and writes the
`notification.channel.auto_disabled` audit-log entry
* Cascade: a disabled APNS channel falls through to Telegram on the
next dispatch — the apns send-mock stays untouched
Adds `senders/__mocks__/apns.ts` — a deterministic mock with queued
per-token responses + recorded calls so future test files can swap the
real sender for a fixture-driven double without touching `@parse/node-apn`.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The W2 commit shipped with `as never` casts on the request + params
arguments, which let the runtime test pass but failed strict tsc
because `apiHandler<() => Promise<Response>>` narrows the wrapper's
signature down to its inner handler's. Cast through `unknown` so the
wrapper-side `request.url` read works and tsc is satisfied.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Apple Health stores sleep as one Measurement row per stage per night,
so the existing single-value SLEEP_DURATION summary would treat each
stage as its own datapoint and grossly understate the per-night total.
The route now sums per Berlin day before summarising — one summary
datapoint per night, value equal to total minutes asleep.
A new optional `sleepStages` block surfaces the per-stage breakdown
over the trailing 30 days when stage-tagged rows exist (and `null`
otherwise so the existing UI keeps painting the totals-only path).
The block reports total minutes, the night count covered, and the
per-stage minute sums so the upcoming insights surface can render
"averaged across N nights" captions truthfully.
Two integration tests cover both shapes — a four-stage night
aggregating to 880 minutes with a populated stages map, and a
manual-source no-stage row keeping `sleepStages` at null.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
`POST /api/measurements/batch` accepts up to 500 HealthKit-shaped
entries per call, runs each through the new mapping helper, and writes
them under `source = APPLE_HEALTH` with the inbound sample UUID as the
external id. The composite unique index on
`(user_id, type, source, external_id)` does the per-entry dedup;
`Idempotency-Key` covers the batch-level retry case so the iOS observer
queue can replay in flight without double-writing.
Per-entry status (`inserted` / `duplicate` / `skipped`) lets the
client advance its sync cursor accurately even when individual rows
land on different paths. Skip reasons cover unknown HealthKit
identifiers and out-of-plausible-range values so a single bogus sensor
reading never rejects an otherwise clean batch.
Insertion uses chunked `createMany` with `skipDuplicates: true` so a
race between two concurrent retries reconciles cleanly via the unique
index instead of failing the transaction. Wide Event annotation logs
`processed / inserted / duplicates / skipped` for ops visibility.
Six integration tests against a real Postgres testcontainer cover the
happy path, the per-entry duplicate path, the over-cap 422, mixed
unmappable + out-of-range entries, per-stage sleep rows, and
`Idempotency-Key` replay.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The `setOnboardingPendingCookie` helper was called from six different
auth routes (login, passkey-verify, register, password, /me,
/onboarding/complete) by convention. A future auth surface (SSO,
magic link, social login) added without remembering the helper would
silently re-introduce the dashboard flash that v1.4.22 C4 was
designed to fix.
Make `onboardingPending` a required parameter on `createSession`
(not optional) so issuing a session without anchoring the cookie is
type-impossible. The five primary auth surfaces now thread the
user's `onboardingCompletedAt == null` value through; the
`/api/auth/me` mirror remains as a fall-back for legacy sessions
that predate the cookie. The `/api/onboarding/complete` clear stays
where it is — it is a value flip after a DB write, not a session
issuance.
Three new integration tests pin: createSession sets the cookie when
pending, clears it when completed, and destroySession clears it
alongside the session cookie.
Closes Sr-H1.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
When the model emits only a `---KEYVALUES---` block with no leading
prose (or a malformed block missing the closing marker), the
post-strip prose is empty. The previous fallback chained back to
`rawReply`, surfacing raw sentinel markers to the user. Replace with
a structured `coach.provider.empty` error frame so the UI renders
the localised provider-error copy instead of leaking the markers.
Add a regression integration test pinning that the streamed body
never contains `---KEYVALUES---` for a sentinel-only reply, and that
no assistant message is persisted in this branch.
Closes Code-H1.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Add a text-marker sentinel parser (`---KEYVALUES---` … `---END---`)
that strips the Coach's evidence block out of the prose before it
streams to the client, validates each line against a Zod schema, and
attaches the parsed entries to `provenance.keyValues`. The persisted
envelope round-trips so the disclosure renders on conversation
reload. Hard-capped at 8 lines and 1 KB to guard against
prompt-injection padding; malformed blocks log a wide-event and pass
the prose through unchanged.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Up to v1.4.19 the BD-Zielbereich tile pinned 50/50/50 because the
route routed the headline through `windows.last30Days?.pct` — making
the headline a literal copy of the `30T` sub-value. v1.4.19 A1
re-anchored the headline to all-time so the three windows could
diverge. That fixed the algorithmic pin but introduced an emotional
problem: the headline became the slowest-moving aggregate possible,
punishing users who had recently dragged their compliance up. A user
seeing 7d 50 % / 30d 50 % alongside a stubborn 11 % all-time read it
as "your work doesn't count yet."
Re-anchor the headline to `windows.last30Days?.pct` and surface
all-time as a third sub-value (`bpInTargetPctAllTime`) so power users
still see the long-arc number without it dominating. The integration
test pins the new contract: with three legitimately divergent windows
the route's `bpInTargetPct` equals `last30Days.pct`, and the new
all-time field carries the historical figure.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The route now builds the four-component Health Score input from the
already-fetched BP figure plus a fresh weight + mood + medication
intake fetch (last 30 days, plus a 7-day-shifted snapshot for the
delta). The response gains a `healthScore: { score, band,
components, delta } | null` field; null when no component is
computable so the UI hero panel can hide cleanly.
The wide-event annotation carries `healthScore.score` + `band` +
`delta` so admin-app-logs can attribute coverage without DB queries.
The previous-week BP rate reuses the all-time figure (it's a slow-
moving aggregate; rewinding it cheaply isn't possible without a
full historical re-pair). Delta therefore primarily reflects week-
over-week movement in weight / mood / compliance — the components
that actually move on a weekly cadence.
Integration coverage seeds three synthetic-data shapes against the
postgres testcontainer:
- strong-positive → green band (>= 75)
- empty user → null healthScore
- compliance-only → bp/weight/mood null, compliance weight 1.0
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
GET /api/insights/chat returns the caller's conversations newest-first
with cursor pagination (default limit 20, hard cap 50). Each row
carries id, title, timestamps, and a message count so the rail can
render without paying the per-message decrypt cost.
GET /api/insights/chat/[id] fetches one conversation with every
message decrypted in memory before serialisation. Provenance metadata
round-trips alongside the assistant turns.
DELETE /api/insights/chat/[id] hard-deletes the thread; the FK chain
cascades the message rows.
Cross-user lookups map to 404, never 403, so the existence channel
never leaks across accounts.
6 integration tests cover the list ordering, owner-only filter,
decryption round-trip, and the 404 boundary on both verbs.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The route gates on requireAuth (cookie or bearer), enforces the daily
token budget, runs the prompt-injection / off-topic refusal scanner,
and only then walks the user's provider chain.
The conversation is created via withIdempotency() when no
conversationId is supplied, so a retry under the same Idempotency-Key
replays the original assistant reply rather than spinning up a second
thread. Existing-thread turns skip the wrap.
Replies stream as SSE: one "token" frame per word-sized chunk, then a
"provenance" frame describing the windows + metrics the assistant
could see, then a "done" frame carrying the persisted message id.
Provider failure cascades to a single "error" frame and the assistant
message is never persisted. Conversation history is capped at 20 turns
in the prompt window via a synthetic summary placeholder so cost stays
bounded.
`buildCoachSnapshot()` reuses the analytics features pipeline so the
Coach narrates the same numbers the dashboard tiles render.
`getCoachSystemPrompt()` extends the strict-insight ground rules with
conversational framing while keeping the zero-hallucination rule.
5 integration tests pin the round-trip, refusal short-circuit, budget
429, foreign-conversation 404, and validation 422 paths against the
postgres testcontainer.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Persist Coach chat threads with AES-256-GCM-encrypted message bodies
and a per-user, per-day token-spend ledger. Encryption reuses the
active ENCRYPTION_KEYS entry so rotation continues to work without a
backfill. metric_source_json carries provenance labels only (window +
metric names, never raw values), keeping it queryable for analytics.
Cascade-on-user-delete is wired through the FK chain so GDPR delete
removes Coach data with the rest of the account. The integration-suite
truncation list picks up the new tables.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Marc reported the BD-Zielbereich tile pinned at exactly 50/50/50 for
7T, 30T, and the headline ("total") on his real production data — the
fourth attempt at this surface (v1.4.15 → v1.4.16 → v1.4.18 → v1.4.19).
Root cause: the analytics route routed `bpInTargetPct` (the headline)
through `windows.last30Days?.pct` — a literal copy of the `30T`
sub-value. Since `computeBpInTargetWindows` only returned 7d + 30d
windows, the headline could never legitimately differ from `30T`. For
Marc's real data (572 paired readings since 2022, recent 30d = 50 %,
all-time ≈ 11 %) the tile read 50 % / 50 % / 50 % and looked
algorithmically pinned — exactly the symptom he reported.
The previous three passes treated this as either a predicate bug
(v1.4.16 ceiling-vs-narrow-band, real and merged) or a missing
`avg7`/`avg30` wiring (v1.4.18, also real and merged). Both fixes
landed correctly, but neither addressed the headline duplication.
Fix:
- `computeBpInTargetWindows` now returns a third `allTime` window
that aggregates EVERY paired reading in the input series.
- The analytics route fetches all paired BP rows (no 30-day cutoff)
and routes the headline through `windows.allTime?.pct`. The route
only re-pairs once internally so the cost is paid once per request.
- The 7T / 30T sub-values are unchanged (still windowed slices of
the same input).
Failing test reproduces the bug with Marc's data shape (`allTime` MUST
not equal `last30Days` once older history is present); fix turns it
green. Integration test seeds 40 paired readings against real Postgres
and asserts all three windows compute independently.
Hand-counted against Marc's prod data:
- 7T: 50 % (1/2) — matches what he sees, real coincidence
- 30T: 50 % (5/10) — matches what he sees, real coincidence
- Headline: ~11 % (62/572) — was 50 %, now correct
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Pre-existing format drift accumulated across v1.4.x; running
prettier brings the whole tree back to baseline so future diffs
read clean. No behaviour change.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Two trigger fixes so the new achievements actually fire end-to-end.
The doctor-PDF hidden Easter-egg used to watch a non-existent
`doctor-report.export` audit action. The real route emits two:
`doctor-report.generate` (the JSON helper) and
`doctor-report.pdf.generate` (the PDF route). Either now counts.
The locale-flip hidden Easter-egg used to watch
`settings.locale.update`, which no endpoint emits — the locale
field shares the catch-all `profile.update` audit row with every
other profile field. Profile-update now emits a separate
`settings.locale.update` row when (and only when) the locale value
actually changes (compares the new value to the prior persisted
locale, suppresses the row when they match), with the from/to
values in the details payload for traceability.
Already-existing TanStack Query invalidation map covers the new
metrics: `measurementDependentKeys`, `moodDependentKeys`, and
`medicationDependentKeys` already include
`queryKeys.gamificationAchievements()`, so any measurement / mood /
intake mutation triggers a refetch and the route persists the new
unlock to `UserAchievement` (existing v1.4.15 mechanism).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
