Each case fails on the pre-fix code: the rollup tests on an unaligned
recompute window, the batch tests on the older stats: snapshot winning,
and the resting test on a series that stops at the fold horizon.
resolveRestingPulseSeries returned the resting branch as soon as a
single RESTING_HEART_RATE row existed and never consulted the PULSE
proxy again. Since the retention fold began minting derived resting
rows for the days it folds, a proxy account carries derived rows for
old folded days and nothing but raw PULSE for the recent ones — so the
visible series stopped dead at the fold horizon.
Merge per day instead: a day with a resting row uses it, a day without
falls back to the proxy. which stays a three-value labelling signal and
reports proxy as soon as one point is estimated, so a partly-estimated
series is never labelled resting heart rate.
Widen the intraday baseline read to pull PULSE history when the newest
resting row is stale, not only when the rows are few — the count gate
alone pinned the baseline to the fold horizon.
The suite was not timezone-pinned. CI runs UTC, so a whole class of
day-bucketing defect was invisible to the gate while a contributor outside
UTC saw a red suite on unmodified main. Verified: a UTC+14 host fails five
tests on an otherwise green tree. Pin TZ=UTC in both vitest configs; tests
that need a different HOST zone now set and restore it explicitly.
The resting-pulse fixtures passed offset-less ISO literals, which parse as
host-local, so they could not distinguish the Berlin day-key the
implementation uses from a UTC one — swapping the day-key's zone left the
file green. Build each instant explicitly in Berlin and add cases whose
local day and UTC day genuinely differ; that swap now fails two of them.
Delete the 'DST boundary (spring-forward)' compliance case. It passed no
timezone, so the slot builder took the legacy UTC path where the date
carries no transition, and it asserted totalExpected === 7 — which holds in
every zone and therefore could never see the double-emit its own comment
described. Threading a real zone does not rescue it: the assertion stays
true in Berlin, UTC, UTC+14 and UTC-11 alike. The property it claimed is
already pinned properly in the scheduling suite, which walks
buildCadenceTimeline with an explicit zone across both the 23 h
spring-forward and the 25 h fall-back day.
The generated-insight narrative layer built its user-facing sentences by
string interpolation and never routed through the i18n bundle, so a
non-English UI rendered English text spliced into localised copy — e.g.
"Higher activity steps tends to go with lower next-day weight" surfacing
mid-German on the Weight insight. Because those strings bypassed t(), the
locale-integrity guard could not catch them.
Route every correlation narrative through the server translator:
- Correlation discovery (daily lagged pairs + labs-vs-outcome) now takes
the reader's locale, resolved from the correlations route the same way
other insight generators resolve it. Sentence templates, the direction
word, and every channel label live under a new insights.correlation.*
namespace, translated in de/en/es/fr/it/pl. The three fixed hypotheses
(BP-compliance, mood-pulse, weight-weekday) and their weekday labels are
localised the same way; the analytics cache key now includes the locale
so a language switch cannot serve another locale's cached text.
- Metric labels resolve to stable localised channel labels; the never-
causal framing ("not a cause" / "an association, never a cause") and the
faint/moderate/high hedging tiers are preserved in every language.
English output is byte-for-byte unchanged. Adds a regression test pinning
German narration and asserting it is not the English string.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_018V8V9qapgHi7fhgtMJ8SkM
Refine the go-forward aggregated HR wire contract (iOS #34) from the never-
adopted hourly bucket to a 10-minute UTC bucket, so one contract serves both
the measurements-list de-explosion and the intraday-pulse 10-min curve.
- Batch route accepts stats:HKQuantityTypeIdentifierHeartRate:<10-min ISO-Z>
with avg + min/max, overwrite semantics, malformed-suffix rejection; the
validator is identifier-generic (allowlist) so respiratoryRate/SpO2 can join
later without a grammar change.
- The intraday reader classifies a day's PULSE rows three ways by externalId
shape (raw / uploaded 10-min bucket / server-folded hourly), builds the
10-min curve directly from uploaded buckets with the min/max envelope and
tension detection enabled, and overlays buckets over raw on the one
cutover-straddling day.
- DAY rollup min/max read COALESCE(value_min, value) so a bucket-native day's
band reflects the true intra-bucket extremes.
No schema change (value_min/value_max exist since v1.19.2). Reconciliation is
go-forward cutover; the nightly retention fold handles the raw backlog.
computeBpInTargetPct's same-calendar-day pairing fallback (for readings
whose sys/dia timestamps drift past the 5-minute session window) keyed
on toBerlinDayKey regardless of the caller's actual user. A non-Berlin
user's two same-local-evening readings straddling Berlin midnight (but
not their own midnight) were rejected as a pair, running the in-target
percentage on fewer readings than it should have — precisely the
population the cross-tz runtime guard in bp-in-target-fast-path.ts
force-routes to this same pairing fallback to protect.
Threads an optional tz through computeBpInTargetPct / collectBpPairs /
computeBpInTargetWindows (default Berlin for untouched legacy
callers), wires it through the fast-path's live fallback and the
comprehensive-insights route's own computeBpInTargetPct call — the
other caller with the user's tz already in scope.
Investigated but left the comprehensive route's resting-pulse-proxy
day-key and BP-medication-continuity day-key on their current UTC
convention: both are joined by an exact YYYY-MM-DD key against a
UTC-anchored partner (the mood rollup's bucketStart, and the
aggregator's date_trunc'd BLOOD_PRESSURE_SYS daily series). Switching
only one side to the user's tz would trade "evening readings shift a
day" for "evening readings mismatch their pairing partner" — a
different bug, not a fix. Documented in place; a real fix needs the
mood-rollup / aggregate tiers themselves to bucket per-user-tz.
Two bugs in the S11 intraday pulse seam:
- The PULSE/step reads queried a ±15h/39h padded superset around the
viewed day, then capped the row count ascending. On a dense account
the cap could be entirely consumed by the PREVIOUS local day's
samples before reaching the viewed day at all, truncating the chart
partway through the afternoon. Query the exact local-day window
(DST-aware) instead — the workout-overlap read keeps the wider
padding since it has no cap and a workout can legitimately span a
local-day boundary.
- The resting-baseline PULSE-proxy fallback bucketed every user's
samples by a hardcoded Berlin day, not the caller's own timezone,
shifting the personal floor the tension detector judges the day
against for every non-Berlin user. Threads `timezone` into
`resolveBaseline`'s `dayKeyOf`.
Two in-memory key builders joined their parts with a literal NUL
(`${a}\x00${b}`): the sleep writer-bucket key and the correlation
pair key. The embedded NUL made grep classify both files as binary, so a
plain `grep symbol src/**` skipped them silently.
Swap the separator for U+241F (␟, the unit separator). It cannot appear
in a `MeasurementSource` enum literal, a device-type tag, or a
correlation-channel name, so the key semantics are identical — the sleep
key still slices its source prefix unambiguously and the correlation Set
still excludes double-counts. Both keys are ephemeral (one pass, never
persisted), so the byte change is invisible to any stored state.
The medication-compliance engine lived in one 2,099-line file with 38
exports feeding eight surfaces (Coach prompt, BP-status gate, dashboard
pillar, per-medication tile, insight targets, doctor report, …). A single
edit intended for one surface could silently shift all of them.
Split along the existing internal seams into `analytics/compliance/`:
parsing, types, adapters, dose-status, occurrences, windows, cycle,
ledger, display. `analytics/compliance.ts` is now a thin barrel that
re-exports every public symbol, so no consumer import path changes. Pure
move — no logic edits; the tally, window ladder, ledger and cycle math
are byte-for-byte the code they were. Tests move alongside under
`compliance/__tests__/` and keep exercising the public barrel.
classifyPulse() labelled resting pulse < 60 "Bradycardia" and > 120
"Tachycardia", the latter painted destructive-red. The interpretation layer
already frames the same signal calmly for the same range ("below the
standard resting range (common in trained hearts)", neutral valence) — a
trained user at 55 bpm resting read a diagnosis-shaped verdict on one
surface and a calm contextual band on the other.
Rename the categories to "Below typical range" / "Above typical range"
(matching the interpretation layer's own wording) and step the high band
down from destructive/danger to warning/amber — still flagged, never a
verdict noun. Neither category paints the pill red anymore.
Adds prev/next-day paging to the intraday pulse "shape of the day" chart
(TileHeader right slot, next disabled at today) so a user can step back
through prior days on the existing date-scoped route.
Raises DENSE_INTRADAY_RETENTION_DAYS from 14 to 90 — a self-hoster's own
storage is the trade-off for three months of full 10-minute-resolution
history instead of two weeks. Days outside the window keep folding to
hourly-mean stats: rows as before; loadIntradayPulse now falls back to
that hourly tier when a day's raw samples are gone, so the navigator
shows a coarser shape instead of an empty chart. The tension-window
read is suppressed on hourly days — it needs per-sample resolution to
stay honest. A new resolution field on the DTO ("tenMin" | "hourly")
drives a small note in the chart.
Add an on-demand intraday layer to the pulse insight: 10-minute mean
heart rate for the viewed day, folded from raw samples via the read-swap
pattern (never persisted as 10-minute rollups for all history). Draw the
personal resting baseline and softly shade any sustained
elevated-at-rest stretch.
The tension signal is not raw heart rate — it is heart rate held above
the personal resting baseline while movement is low (the elevated-at-rest
window), so a workout or a walk never reads as tension. Detection is
deliberately conservative: baseline maturity, per-bucket sample density,
a mandatory step-based low-movement gate, and a minimum sustained
duration must all hold before anything is reported. Silence over
speculation.
Surface the same signal as a calm, non-diagnostic tension_window item in
the daily digest — at most once per day, honest-absent otherwise, gated
on the insights module and yielding the rail to time-sensitive actions.
Cautious copy across all six locales; framed as "possible tension", never
a clinical stress verdict.
The sleep source-discrepancy annotation now reaches the surfaces: SleepNight
carries the MAIN session's annotation (naps never cross-compare), the analytics
slim slice / dashboard snapshot / iOS summary thread it additively, and the
dashboard sleep tile renders the shared discreet marker (extracted from the
sleep panel — one implementation, two surfaces). Served totals unchanged,
pinned by tests.
Apple Health medications groundwork (server side of the medication-import
request): IntakeSource gains APPLE_HEALTH; medications accept an external
mirror identity (source-exclusive by policy) and dose imports carry the HK
dose-event UUID — both idempotent per stable key, with the concurrent-create
race resolved to the winner. Migration 0239, additive only. Entries without
the new fields behave byte-identically.
Hardening: doctor-report aggregation + PDF charts compute ranges with loops
instead of spread calls — a report over a sample-dense year cannot overflow
the call stack (the class fixed for the Google Health full sync).
A one-time background pass re-reads each connected account's Google Health
sleep history so nights stored twice before the sleep fix collapse to their
true total (new sleep_repaired_at marker, migration 0238; watermark-safe,
enqueued once at boot per un-repaired connection).
The sleep night read reports when two writers disagree about the same night —
the served total is unchanged, the disagreement rides along as an annotation
(sourceDiscrepancy on the night DTO) so clients can mark the number instead of
silently picking a side.
A GLP-1 medication whose weight has plateaued on the current dose says so next
to the estimated drug level (efficacy tab + insights) — a factual note from the
existing detector, association only, verb-guard covered.
Google Health diagnostics: the sync log now separates a daily-totals read that
returned nothing from one the importer could not parse
(googleHealth.rollup.emptyResponse vs droppedAll), and the connection test's
structure probe reports the raw response envelope key names when a rollup type
parses to zero — a per-account naming drift becomes visible from one report.
- getUserTodayBounds: a 25h fall-back day keeps a 23:30 dose inside today,
a 23h spring-forward day does not bleed tomorrow's 00:30 dose, ordinary
days stay 24h, and a negative-offset zone anchors on the local day.
- dailyComplianceRatesFromLedger: a Los-Angeles user's two same-local-day
doses land in ONE bucket where the old fixed-Berlin key split them.
- classifyIntakeTiming: an 08:00-local dose reads on_time with the user's
zone and very_late without it.
- hourInTz: reads the wall-clock hour in the given zone.
- hero-strip greeting: resolves the hour in the stored zone, not the
browser clock; existing greeting fixtures re-pinned to explicit UTC
instants mapped to Berlin wall-clock.
Five timezone-correctness fixes across the medication / compliance surfaces:
- getUserTodayBounds now derives both bounds through the DST-safe
startOfLocalDayInTz, so the today window is 23h on spring-forward and
25h on fall-back instead of a hardcoded 24h sampled at now. A 23:30
local dose no longer drops off the med cards, dashboard, PWA badge and
reminder idempotency near midnight on a transition day.
- dailyComplianceRatesFromLedger takes the user's zone and buckets each
per-day rate with userDayKey, so a non-Berlin user's evening dose is
filed on the local day it was due rather than the next Berlin day.
- classifyIntakeTiming interprets the window HH:mm in an optional zone;
the achievements perfect-day check passes the user's zone and reads the
scheduled minute-of-day in-zone, so a dose far from UTC is graded
against local wall time.
- The /insights greeting resolves the hour in the user's stored zone via
the new hourInTz helper, matching the dashboard hero.
- The doctor-report and schedule-anchored compliance queries load
schedules through SCHEDULE_COMPLIANCE_SELECT instead of a broad
include, so a future engine column reaches both surfaces.
The Coach adherence storyline derived its rate from the raw coverage
rollup, whose denominator counts logged slots rather than scheduled
doses, so a user who logged only taken doses read ~100% and the dip gate
suppressed a real decline. Extract the dashboard tile's schedule-anchored,
cadence-aware compliance into one shared engine and route both surfaces
through it, so Coach and the dashboard report the same number.
Reference-band fills, classification tones, and the trend-chart palette
carried hardcoded hex that rendered identically in both themes and
glared on the light surface. Route them through the semantic and chart
CSS variables, which already hold per-theme values, so the light theme
gets the muted set and the dark theme stays byte-identical.
A cluster of related correctness gaps in the compliance denominator and the
insight surfaces that read it:
- Paused medications. A doctor-ordered pause flipped `active` off and stamped
`pausedAt`, but resume nulled `pausedAt`, so the interval was irrecoverable
and every paused day became a missed dose after resume — collapsing
adherence across the Health Score, the BP gate, the Coach snapshot and the
report. Persist pause intervals as durable eras (new `MedicationPauseEra`,
migration 0211), close the open era on resume, thread the eras through the
compliance context and drop slots inside a paused interval from the
denominator. Every compliance call site now fetches and passes the eras.
- Health Score eras. The Health-Score fast path was the only compliance
caller that skipped the shared schedule select and schedule revisions, so
after a schedule edit it scored past days against the current schedule
while every other surface used the historical era. Switch it to the shared
select and thread revisions (and pause eras) like the canonical path.
- Insight bucketing timezone. The per-metric status series bucketed every
user in Europe/Berlin, so a near-midnight reading landed in the wrong day
and the relative-day phrasing was off for non-Berlin self-hosters. Thread
the resolved user timezone and key off `userDayKey`.
- Correlation significance. User-facing correlations surfaced from five
paired points with strength read straight off the coefficient. Route them
through the rigorous engine (at least twenty pairs, Student-t p below 0.05)
so small-N coincidences no longer render as confident findings.
- Resting-pulse input. The mood-versus-"resting pulse" correlation fed the
raw PULSE day-mean, which folds in workout HR, under a "Resting pulse"
label. Feed `resolveRestingPulseSeries` (clean RESTING_HEART_RATE, else a
daily low-percentile proxy) so the label matches the input.
The rollup read path windows the 7/30/90-day regression on
startOfUtcDay(now - N days), while the live-SQL fallback filtered the
REGR_* aggregates on the wall-clock NOW() - INTERVAL bound. An account
crossing a coverage boundary (warm to cold) therefore saw the boundary
day's readings flip in or out of the slope window depending only on
whether the rollup tier was populated, returning a cache-dependent
slope for the same request.
Anchor both cold-fallback paths on date_trunc('day', NOW() AT TIME ZONE
'UTC') - INTERVAL 'N days', the SQL twin of startOfUtcDay, so warm and
cold return identical boundary-day membership. The avg7/avg30/median
windows stay wall-clock since the warm narrow query computes them the
same way.
The windowed slope / r2 / sd readers compose from the per-bucket
regression accumulators (migration 0190). Between a deploy and the
boot-backfill completing, a tenant's pre-0190 DAY buckets still carry
NULL accumulators, so composeWindowedRegression returns a full miss and
the slim / comprehensive readers emit a null slope. The null is the
honest answer until the backfill refills the accumulators, but the miss
was passing as a plain rollup read with no signal, against the no-silent-
cap rule.
Add hasPendingAccumulatorBackfill to the read tier and key a new
regression_source annotation off it (unavailable_pending_backfill vs
rollup) on both warm paths. No live-SQL fallback is added; the design
intentionally avoids the heavy scan.
The summaries slice (computeFromRollups) and the comprehensive aggregator
(buildFromRollups) each ran a narrow live $queryRaw over the raw
measurements partition on EVERY warm-rollup request to fold slope7/30/90
and r2_7/30/90 via REGR_SLOPE / REGR_R2 - the un-eliminated live scan on
the happy path.
Drop the six REGR_* columns from both narrow queries and compose the
windowed slope / r2 (and the population sd via composeRegression) from
the per-bucket accumulators stored in measurement_rollups. The 90-day
DAY buckets are loaded once (already loaded in comprehensive; one bounded
findMany added in the slim slice), source-collapsed to the canonical
source, then summed over the day-aligned 7/30/90-day sub-windows. A
window whose buckets lack accumulators (pre-backfill) composes to null,
the same shape the empty REGR_* FILTER returned, so a transitional read
never returns a wrong partial regression.
median (PERCENTILE_CONT) and the exact |z|>2 anomaly count stay on the
minimal live query - both are non-composable across buckets. The cold
coverage-miss path keeps the live REGR_* regression. Annotate
slope_source:"rollup" + median_source/anomaly_source:"live" so a
regression to the heavy path stays observable (no-silent-cap rule).
The warm narrow query and the cold heavy query each referenced the
canonical-source subquery twice — once in the window_stats CTE and once in
the outer body — so the DISTINCT-ON pick over the live 90-day rows ran twice
per rebuild. Extract canonicalMeasurementsCte (the SELECT body without the
alias wrapper), bind it once as WITH cm AS (...), and select FROM cm m from
both window_stats and the outer aggregate. Output is identical; the dominant
self-join runs once.
canonicalMeasurementsFrom now wraps the same body, byte-stable for the
single-reference call sites (pinned by a new parity test).
Add a covering partial index over (user_id, type, measured_at DESC) WHERE
deleted_at IS NULL (migration 0183). The hot reads all filter deleted_at and
order measured_at DESC, but the base index is ASC and excludes deleted_at, so
every type not served by the two existing partial indexes pays a heap re-check
of deleted_at over its partition. The covering partial removes the re-check for
the DISTINCT-ON-latest, list and series reads.
Cap the cold-fallback all-time aggregate in summaries-slice at a 15-year
window. It sits far beyond any real history, so it never changes a real
all-time count/min/max/mean; it exists only so a coverage-miss cold read can't
trigger an unbounded full-partition scan.
STRESS_SCORE has no source-priority ladder, so metricKeyForType returns null
and the SQL source collapse falls to an alphabetical rank-90 tiebreak. It is
safe today because the only producer is the COMPUTED HRV-derived proxy, but
the instant a device-native producer (Oura daily_stress) is enabled both rows
survive and blend nondeterministically.
Add a stress metric key with an OURA-above-COMPUTED default ladder, wire it
through metricKeyForType and RANKED_TYPES, and surface it in the Sources
settings (all six locales). A guard test asserts every RANKED_TYPES member
resolves to a non-null metric key so a future ranked type can't ship unladdered.
Regenerate the OpenAPI for the additive source-priority key.
The raw BP pulls in the comprehensive aggregator and the bp-in-target live
fallback read every source's row for BLOOD_PRESSURE_SYS/DIA. BP is a
multi-source metric — a Withings reading mirrored into Apple Health is two
rows for one event — so each shared reading was counted twice in the
in-target denominator and twice in the recency-weighted grade. The rollup
branch of the same fast-path reads source-collapsed measurement_rollups, so a
rollup-warm account and a rollup-cold account returned different BP
percentages and grades for identical data — a web/iOS and cold/warm parity
break.
Route both raw pulls through canonicalMeasurementsFrom so the cold/live path
picks the ladder-winning source per (type, day), matching the warm/rollup
path. Per-event rows of the winning source survive the collapse, so the
downstream 5-minute pairing still sees individual readings.
One-shot prettier pass so the new format:check gate starts from a clean
baseline. Formatting only — no behaviour change. Generator-owned and
vendored artifacts stay untouched via .prettierignore.
Drop steps from the signals-of-day set: Apple Health steps ingest as
many intraday stats-prefixed samples, so the newest raw row is a
partial-day fragment, not a daily total — same exclusion already applied
to per-night sleep. Add a glucose signal off the canonical stored value
(the model reads the snapshot, not display units) so the block matches
the priority comment that already claimed it; drop the dead sleep entry
from SIGNAL_PRIORITY. Track the raw extreme magnitude when keeping the
most extreme recent anomaly so a larger anomaly is no longer dropped by
comparing against an already-rounded value. Thread the injected clock
through trendSlope so the emerging-trend cutoff is deterministic under a
test clock. Rename the anomaly day-count to anomalyDaysAgo so the
snapshot hash staleness-tiers it instead of letting the raw count drive
the fingerprint. Cap the returned set at three to match the schema.
The targets route held a ~1.4k-line domain function in the handler body.
Move buildTargetsResponse into src/lib/targets/build-response so it sits
beside the other targets helpers and can be unit-tested without the route
shell; the route is now auth -> cachedSwr(buildTargetsResponse) -> apiSuccess.
Follow the as-needed compliance source pin to the new file location.
Compliance streaks, the measurement-consolidation day key, and the
correlations weekday helper each carried their own Intl formatter
(en-CA / sv-SE / short-weekday). Delegate them to userDayKey and
wallClockInTz so every day-bucket key stays byte-for-byte aligned and the
locale decision lives in one place.
An active illness/condition episode annotates, it never penalises: the
measured number is untouched, only the narrative changes.
- rest-mode.ts: one server-authoritative resolver (module-gated, fail-soft)
for "is the account in Rest Mode + which episodes back it". iOS mirrors the
resolved context, never recomputes the suppression.
- health-score: /api/analytics attaches a value-free Rest Mode annotation;
computeHealthScore stays pure (score never adjusted).
- recovery-score: computeRecoveryScore carries the Rest Mode context as of the
scored day; the persisted blend is unchanged.
- coach-nudge: pause cadence-nudges during an active episode (new
skippedDuringIllness counter, gate sits before the trigger search).
- achievements: bridgeFrozenStreakGaps freezes (does not break) every
day-streak across illness days; never invents a streak, a non-illness gap
still breaks.
- coincident-deviation: reframe a fired flag as illness-explained; vital
numbers untouched. Surfaced as a neutral line on the insights card.
- coach snapshot: illness history + active illness as load-bearing context so
the coach knows about Rest Mode (no decrypted note reaches the prompt).
- FHIR: illness episodes map to Condition (generic disease root, label on
code.text, patient-reported/unconfirmed) + a bounding Encounter.
- doctor-report: module-gated illness section in the aggregator + PDF table
(retrospective, neutral palette); FHIR Condition section in the bundle.
i18n x6 for the report + reframe copy. Tests: score-annotation-not-
penalisation, streak-freeze, coach-nudge pause, FHIR Condition/Encounter
mapping, doctor-report inclusion, Rest Mode resolver. typecheck/lint/test
green, openapi in sync, knip clean.
The per-day compliance series in the medication-compliance insight snapshot
divided every event-day by the schedule count, treating each calendar day as
fully dose-due. A weekly-cadence medication (a Monday-only schedule, a
bi-weekly interval) therefore had its series read off-cadence weekdays as
misses, contradicting the canonical compliance30 value shown in the same
snapshot.
Route the per-day series through the unified dose-history ledger that already
backs compliance7 / compliance30: add dailyComplianceRatesFromLedger, which
groups the ledger's scheduled slot rows by day and scores each day with the
same taken / (taken + missed) tally — on-time-plus-late numerator, skip /
ad-hoc / upcoming exclusions — that tallyLedgerRows applies to the window
rates. Only days the cadence actually expected a dose produce a point, so a
non-due day can no longer be counted as a miss, and the per-day series and
compliance30 are computed from one ledger and cannot disagree.
The insight generator now derives both the canonical compliance results and
the ledger from a single buildMedicationComplianceBundle pass instead of two
calculateCompliance calls plus a hand-rolled per-day map.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The Personal Health Score weighted the 0.20 mood-stability pillar
unconditionally — the fast-path read mood entries regardless of the
account's module state, so a user who turned the mood module off was
still scored (and silently penalised or rewarded) by a pillar hidden
everywhere else in the product. The dashboard already blanks the mood
tile and the coach snapshot unions mood out; the score ring and the
insights card pillar list did not.
Thread a default-on `moodEnabled` flag through the fast-path. When the
caller resolves the mood module as disabled the helper skips the mood
read entirely and leaves the series empty, so `moodStability` returns
null and the existing proportional null-redistribution re-scales the
surviving pillars to sum to 100. The analytics route resolves the
module server-side and threads the flag; the insights card hides the
Mood row via a new SSR-safe `useModuleEnabled` accessor so it never
advertises a pillar the account turned off.
Golden fixtures pin mood-on vs mood-off to different, correctly
re-weighted scores and assert the disabled read is never issued.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Polar exposes only per-stage duration totals, so its mapper already
reconstructs a contiguous CORE-DEEP-REM order exactly like WHOOP and flags
each segment reconstructed. The night reader's honesty allow-list only held
WHOOP, so a Polar-won night was served with reconstructed:false — presenting
a synthetic stage order to web and iOS as if it were the device's measured
timing. Add POLAR to the allow-list so the layout is labelled approximate.
Polar's total_interruption_duration carried the night's awake time but was
dropped, so every Polar night read as fully consolidated (awakeMinutes:null,
awakenings:0) with overstated asleep-vs-in-bed efficiency. Lay it as a
leading AWAKE segment so the asleep stages partition the remaining window and
the reader surfaces real awake time.
WHOOP and Polar independently implemented the same contiguous-timeline walk.
Extract a shared reconstructContiguousSleepTimeline helper under src/lib/sleep
and call it from both; each mapper keeps only its field normalisation. Oura's
measured 5-min hypnogram is a different algorithm and is left untouched.
The dashboard snapshot and the /api/mood/analytics route each carried a
hand-copied rollup read, coverage fallback, and daily summarize of the
same numbers. Two reads of one metric is the seam where the dashboard
tile and the insights mood sparkline can drift apart.
Extract buildMoodDailySeries as the single mood engine and route both
callers through it, so the same mood number reads identically on the
dashboard, the insights surface, and the iOS client.
WHOOP's v2 API returns only per-stage sleep duration totals — no onset
timestamps, no hypnogram endpoint. The mapper stamped all five stage
totals on the one sleep-END instant, so the hypnogram reconstructed
every stage as a span touching the night's right edge: bars stacked
right-aligned with no clock times whenever WHOOP was the sole source.
Lay the asleep stages back-to-back from sleep onset in a fixed
physiological order (AWAKE lead, then CORE → DEEP → REM), emitting one
timed row per segment with measuredAt at that segment's end and a
distinct indexed externalId. IN_BED stays a single envelope row over the
whole window. The existing reader and renderer are untouched — they now
see distinct per-segment instants and place each block at its own time.
The order is synthesised, not measured, so every reconstructed row is
flagged and the night DTO carries a per-session `reconstructed` boolean
(GET /api/sleep/night, regenerated OpenAPI). The client renders the
hypnogram but labels it an approximate layout and never recomputes;
real-series sources (Apple Health, Withings, Fitbit) stay false.
The mobile settings test asserted three integration pills; Polar, Oura and
Nightscout bring the list to six. Remove the unused Oura and Polar field-map
documentation constants and the unused advanced-indices interface the dead-code
gate flagged.
Add WHOOP-native DAY_STRAIN (0-21) to the Coach snapshot as a dedicated
dayStrain block, kept distinct from the computed STRAIN_SCORE (0-100) and
preferred native-over-computed, mirroring recovery resolution. Document the
glucose.clinical panel (TIR/GMI/eA1C/CV) plus the stillLearning and
isSpotEstimate gates in the system prompt, and the native dayStrain scale in
the derived paragraph. Extend the DE and FR/ES/IT/PL evidence-block unit lists
with mg/dL, mmol/L and min so a non-English coach can cite glucose and duration
values. Export GLUCOSE_PANEL_WINDOW_DAYS as the single source for the 30-day
clinical-panel window and import it across the analytics route, dashboard
snapshot, and Coach snapshot. Compute the derived metrics concurrently.
Hard-coding isSpotEstimate: true mislabels a dense Nightscout CGM stream
(~288 readings/day) as a spot estimate and undersells the data in the
clinical panel and coach. Compute readings-per-day over the covered span
and treat the series as continuous below the spot caveat once it clears a
~hourly bar (24 readings/day); sparse spot fingersticks keep the caveat.
The panel only renders the spot-reading line when isSpotEstimate, and the
OpenAPI field relaxes from a literal-true to a boolean.
Review follow-up to the shared entry-instant guard. The past-floor refine
re-ran the full plausibility predicate, so a future-dated instant tripped
both refines and the 422 carried a nonsensical "too far in the past" message
alongside the correct future one. The floor refine now checks the past bound
alone; a future value emits only the future message, matching the pre-refactor
single-message contract.
Also harden the Health-Score BP inputs and de-duplicate the tile-window
derivation surfaced in the same review:
- the prior-week graded score now keys off the prior-week window's own
sufficiency rather than the current window's, so the week-over-week graded
delta never pairs a confident current value against a thin-sample prior one;
- the BD-Zielbereich 90-day count + effective span derive through one shared
`deriveBpWindow90` helper, so the dashboard snapshot and the analytics thick
slice can never compute the gate or the label span differently.
The BD-Zielbereich tile narrated a static "· 90 T" scope even for a user
with only a few weeks of history or a handful of readings — a headline that
reads like a stable quarter-long average when it is really a thin sample.
Add a shared, reusable window-confidence helper that, given a window length
and the readings observed inside it, returns the EFFECTIVE label span (the
real calendar span capped at the window, so "· 23 T" until ~90 days of
history exist) and a sufficiency flag (false below five readings). The helper
is metric-agnostic so the glucose time-in-range / GMI and sleep tiles can
reuse it.
Wire it into the in-target headline: below the confidence floor the tile
shows "sammelt noch Daten" instead of a hard percentage, with the dynamic
span label; above it the percentage shows with the real span. The
Health-Score BP pillar reads the same sufficiency notion through the shared
input builder, so a thin-data user no longer gets a confident pillar grading
off a few readings — the all-time rate still rescues a deep-history account
with a quiet quarter. The 90-day pair count and effective span thread from
the analytics route and the dashboard snapshot through to the tile.
The doctor-report PDF and FHIR export tallied raw intake rows — taken when
takenAt was set, else skipped, else missed, with every row counting toward the
denominator. That double-counted cross-source duplicate rows (a reminder row
and an API row for the same slot both read as taken), ignored band timing (a
pre-window or ad-hoc take counted as a plain take, a pending row counted as a
miss regardless of the cutoff), and honoured no cadence, so off-week rolling or
cyclic days could enter the tally. A clinician comparing the printed adherence
% against the app's medication detail page could see two different numbers for
the same drug.
Route the report through the same dose-ledger compliance the detail page uses:
per scheduled medication, mint the cadence-aware bands over the report window
and tally taken / missed / skipped from the unified dose-history ledger, with
the denominator being taken + missed so the renderers' taken/total rate equals
the ledger rate. PRN / as-needed medications stay excluded. The compliance
assembly is extracted into a pure, unit-tested `buildLedgerCompliance` helper;
the medication query now loads the archived schedule eras and the report reads
the user timezone so past days attribute against the schedule that was live
then.
The Personal Health Score was assembled differently by its two callers. The
analytics route (the Insights card) graded the BP pillar off one window and
passed the prior-week values for the week-over-week delta; the dashboard
snapshot (the hero ring) graded it off a different window and omitted the
prior-week values, so the ring's delta zeroed BP out and the pillar's presence
gate could flip. The same user could see two different scores and two
different bands on two surfaces.
Extract `buildHealthScoreBpInputs` — one pure builder that turns the current
and prior-week in-target envelopes into the BP-pillar inputs (the 90-day rate
with an all-time fallback, the graded clinical-proximity score, and the
prior-week counterparts for the delta). Both callers now run the same two
in-target probes and feed the pillar through this builder, so the window
choice, the fallback, the graded-score wiring and the delta inputs are
identical by construction and can never drift between the surfaces again.
The dashboard ring now runs the prior-week probe it previously skipped, so its
week-over-week delta reflects BP movement to match the Insights card.
The "BD im Zielbereich" share was narrated on three different windows on the
same screen: the dashboard headline read the trailing 30 days, the dashboard
Health-Score BP pillar read all-time, and the analytics route's pillar read
all-time while its headline read 30 days. A user could see one in-target rate
on the tile and a pillar graded off a different window directly above it.
Standardise the headline, the Health-Score BP pillar input, and the
week-over-week delta on a single trailing-90-day window everywhere — a span
wide enough to stay stable yet recent enough to track current control.
`computeBpInTargetWindows` and the rollup fast-path now both surface a
`last90Days` window; the analytics route and the dashboard snapshot route the
headline and the pillar through it, and both feed the pillar from the identical
value so the dashboard ring and the insights card can never disagree.
Label the window in the tile ("BD-Ziel · 90 T") so the scope is visible; the
30-day figure stays as the short-horizon caption and the all-time aggregate
stays carried for the detail view. Visible-number change is expected: the
headline now reflects the quarter rather than the month.
Marc-André Bombeck