- 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.
A medication can declare itself as-needed: no schedules, never due,
never reminded, excluded from every compliance rate — but intakes log
ad-hoc, consume inventory exactly like scheduled doses, and the
history stays. The wizard offers it as a cadence choice and round-
trips it on edit; card, table and detail show a calm marker where the
next dose normally sits, the take-all dialog never collects one, and
the supply runway stays unknowable by construction. (#316)
A writer whose stage rows all share one timestamp carries night totals,
not segments — reconstructing them as segments paints every stage
flush against the night's right edge. The session picker now prefers a
writer with genuinely timed rows among the granular candidates, so a
stage summary backfilled for a night an actually-timed writer also
recorded no longer evicts the real timeline; summary-only nights still
resolve. The hypnogram itself degrades a summary-shaped session to the
stage breakdown instead of drawing the false skyline.
Per-status texts check AI consent before the unchanged-data refresh can
re-stamp them, the comprehensive fingerprint folds in the comparison
baseline and generation language so toggling either regenerates once,
and profile, threshold and source-priority writes evict the analytics,
targets and derived caches they feed. CSV export neutralises spreadsheet
formula prefixes on free-text cells while numeric columns stay typed,
the derived batch validates its type token against the measurement enum
and carries a per-user rate limit, and a dose synced from the phone app
counts as the interactive write it is. Background cache refresh
failures log a structured event instead of vanishing, the warm queue
runs visit-triggered jobs alongside the nightly walk, the formatter
memo evicts one entry instead of flushing wholesale with its option
objects frozen, the targets cold build bounds its fan-out, and time in
bed unions every writer's envelope while stages stay with the richest
recorder.
Sleep nights collapse per writer instead of per source: several
HealthKit apps land behind the same source value, so a phone's coarse
awake and in-bed blocks could blend into or fully constitute a night
whose stages another writer had recorded. The winning writer per
session is the one with the most distinct granular stages, then the
user's source ladder, and its rows are kept whole. The device type is
threaded through every sleep read including the stage stacked bar, and
the sync overlap for late-arriving nights widens from one day to seven
so a night scored after the cursor passed is fetched on the next tick —
assembly is read-time, so affected nights heal without manual repair.
Mood notes expand to their full text in the list on desktop and touch,
replacing the hover-only tooltip, and the mood CSV export carries a
note column.
A typed apiFetch wrapper owns the envelope unwrap, the ok-check and the
error read for every client call — two hundred call sites across the
app migrate onto it and a lint rule keeps raw api fetches out for good.
The legacy timezone helpers fold into the tz module and test fixtures
drop personal names.
Editing a schedule's times no longer rewrites the past. Each material
change archives the outgoing cadence as a dated revision, and every
band consumer — history, compliance, write attribution, the auto-miss
cutoff — mints past periods from the schedule that was valid at the
time, so a dose era taken at its then-correct times stays on time
forever. The repair script can infer historical eras from consistent
old anchors behind an explicit flag. The welcome tour scrolls its
target into view, flips above it when space below runs out and falls
back to a centred sheet on any viewport, so no step can strand its
buttons below the fold. The avatar menu drops the about entry — that
lives in settings.
A night with coarse apple-health samples next to granular watch data
showed only awake and asleep — the per-session source pick now prefers
the source that knows its stages. Tour popovers clamp into the
viewport, wrap their footer and fall back to a bottom sheet on narrow
screens. Settings and admin sections share one alignment rule — icon
column left, everything else flush on the content column — with neutral
header icons, no duplicated section titles under the shell heading, and
every select on the account-style idiom with a visible chevron. The
dashboard's customize icon matches insights, the target-settings link
leaves the home charts, and the mood heatmap adopts the damped fills
the other mood charts already use.
An off-schedule row now tells the user when the dose had been due, and
its row menu offers to attribute it to that slot when the slot is still
unserved. A pinned intake is a deliberate decision with a visible badge,
it always counts as taken late — never on time — and the pin can be
released again. The read model binds pinned rows by their slot anchor so
a pin outside the catch-up window survives reloads, and the suggestion
respects the schedule's own windows instead of a hard-coded tolerance.
The clock format followed the UI language with no way out — an English
interface forced AM/PM everywhere. A new profile preference (automatic,
24-hour, 12-hour) feeds every formatter through the shared locale
context, persists on the user row and rides the profile endpoints. The
insight pill list in settings gains the same eye toggle the overview
tiles have, so ordering and visibility live in one place; the page-side
'manage detail pages' block folds into a link there. Includes the
locale bundles for both features and the regenerated API contract.
The auto-miss cron stamped every pending row missed a flat day after
its slot even though weekly schedules stay takeable for days, touched
tombstones because it never filtered deleted rows, and a verdict stuck
even after the dose was taken. The cron now derives its cutoff from the
schedule's window reach, skips deleted rows and bumps the sync counter,
and a take clears the auto-miss flag. Editing a schedule tombstones the
open pending rows of the old anchors and reconciles a stale window onto
the new times. The bulk write path attributes takes through the same
band engine as the single-intake routes and accepts forceSlotInstant
per entry. Configured dose windows now reach every compliance call site
through one shared schedule select, and the card window pill takes a
timezone, treats a degenerate window as a point and counts dose times
instead of schedule rows.
The medication list fired one compliance request per card every 30
seconds, and each request scanned the medication's full intake history
and expanded the recurrence calendar five to six times. The endpoint now
mints bands once per request, serves the sub-windows from that single
ledger, bounds the event read to a year of selected columns and sits
behind a write-invalidated 15-minute server cache; the cards poll at
five minutes. The dashboard drops two redundant checklist queries by
reading counts from the snapshot, the BMI chart derives from the weight
series instead of refetching it, the detail page no longer serialises
behind the auth probe and seeds its query from the list row. Expensive
analytics reads gain a shared per-user rate limit, and the service
worker stops serving cross-version shells, enables navigation preload
and trims caches in one pass.
A server-minted pending row (taken_at null, not skipped, not auto-missed)
was scored missed the moment its slot time passed, so the history tab and
the compliance rate punished doses that were still takeable under the
band model. Pending rows now read upcoming until the band's overdue end;
auto-missed keeps its terminal verdict. Pending rows outside the minted
band window are dropped instead of surfacing as phantom ad-hoc lines.
The dose-window editor pulled DOSE_WINDOW_DEFAULTS from
@/lib/analytics/compliance, dragging the server-only scheduling graph
(which imports node:async_hooks) into the client bundle. Turbopack
rejected the client chunk; tsc does not model the boundary so the type
check stayed green.
Move the constant into a leaf module with no server imports and
re-export it from compliance so the server path is unchanged. The
client-reachable editor now imports the leaf directly.
Thread the persisted `doseWindows` through the shared band minter so the
on-time band for a dose time uses its explicit `[start, end]` range
(minted DST-correctly on the slot's local day) instead of the symmetric
±1h default; the late tail stays cadence-derived. A `normaliseDoseWindows`
helper coerces the stored JSON into a clean entry list, dropping anything
malformed so the read/write paths never defend against an arbitrary shape.
Every band consumer reads the same field: the dose-history endpoint, the
compliance %, the cadence timeline (card last/next dose), and the
write/edit slot attribution all resolve through one minter, so the
history view and the rate can never disagree. The write/edit and
health-score schedule selects now pull the column.
The medication compliance percentage and the history view drew their
per-dose attribution from four different matchers — the ±12h pairDoses
proximity used by calculateCompliance, the deriveDoseStatus bands (open
dose only), the 3h+120min classifyIntakeTiming heatmap heuristic, and a
raw takenAt-IS-NOT-NULL per-day rollup. They could and did disagree: a
dose could read "taken late" in the rate while the history called it an
off-schedule ad-hoc take.
Route the rate through the shared cadence-aware band minter +
reconstructDoseHistory so the percentage is a tally over the SAME ledger
the history view renders. The same intake can no longer be taken in the %
and ad-hoc in the ledger.
- calculateCompliance: when a medication context is supplied, the
count fields (taken / skipped / missed / rate) come from
tallyComplianceFromLedger. Numerator = taken_on_time + taken_late (a
late dose still counts as taken — the taking-vs-timing split is kept
available); denominator = taken + missed; skipped, ad-hoc, upcoming and
whole PRN groups are excluded; rate capped at 100. The streak still
walks the cadence timeline. Context-less pure-math callers keep the
legacy timeline tally byte-stable.
- complianceChips + missedDoses: adherence rate + missed count come from
the same ledger when an engine context is threaded.
- /api/medications/[id]/compliance heatmap: the per-day timing split and
missed marks are bucketed from the one ledger instead of the per-day
classifyIntakeTiming + expectedSlotCountForDay walk, so the cells agree
with the headline rate.
- medication_compliance_rollups stays a raw cross-medication daily
coverage count, documented as distinct from the band-attributed % (the
band minter is per-cadence and cannot run inside a single SQL tally).
Downstream readers (health score, insight compliance status) keep calling
calculateCompliance; their numbers shift to the honest band-attributed
values. Some currently-counted off-time takes (e.g. an 11:29 take of a
07:00 dose) now read ad-hoc with the slot missed rather than taken-late —
the configurable per-dose window is the lever to widen the on-time band.
Tests: the irregular twice-daily, single-time-late heatmap, and legacy
parity fixtures are updated with rationale for the intended number
changes; new tally tests pin the taking/timing split, the skip / ad-hoc /
upcoming / PRN exclusions, auto-missed=missed, the 100% cap, rolling
retrospective families, and the cross-consistency invariant.
Marc-André Bombeck