Apple Watch Blood-Oxygen samples OXYGEN_SATURATION through the day and
overnight. The readings map to latest aggregation and sit in neither the
cumulative SUM drain nor the daily-mean drain, so every sample piled up raw
forever. Fold out-of-window per-sample SpO2 rows to one daily-mean stats:
row, soft-delete the raw rows, and preserve the daily min/max on the rollup
DAY bucket via a pre-fold recompute — the lowest sample is the overnight
desaturation nadir, the clinically meaningful figure the mean would hide.
Generalise the PULSE min/max preservation to a min/max-preserving set so
the pre-fold recompute and the skipped post-fold recompute cover both PULSE
and SpO2; resting-HR derivation stays PULSE-only. RESPIRATORY_RATE is left
to the existing daily-mean drain it already belongs to.
The comprehensive briefing's bounded feature read (extractFeatures) was
paid more than once where it should not be: the on-demand route and the
shared generator each run a downgrade ladder that re-reads with identical
arguments, and a nightly warm has no shared object across consumers in a
single tick.
Add a request/run-scoped feature cache: withFeatureCacheScope opens an
AsyncLocalStorage store, getCachedFeatures memoises the first compute per
(userId, day, includeRaw, sinceDays), gated on a cheap salient-input
fingerprint so a mid-scope ingest recomputes and a probe failure fails
safe. Outside a scope it is a pure passthrough. Wired into the
comprehensive generator, the on-demand POST handler, and the nightly
per-candidate loop + forceWarmUser. Coach keeps its own snapshot.
The slow-moving status input fingerprint covered the card's own metric
rows plus mood and height, but not the FDR discovery channels that also
feed the prompt via getRelevantCorrelationsForMetric. A correlation
newly surfacing off a behaviour channel (e.g. daylight -> next-day
weight) left the card's own rows untouched, so the input gate re-stamped
the stale assessment and the discovery never reached the prose.
computeStatusInputFingerprint gains includeCorrelationChannels: it widens
the same grouped probe by the discovery behaviour + outcome channels
(deduped, mood excluded as it is mood-entry backed), so a channel change
flips the hash. Wired into weight-status, the one caller that folds a
relations block.
The Heart sync recorded only the device's atrial-fibrillation verdict per
on-device ECG. Fetch each recording's full waveform via the Heart get
endpoint and store the raw micro-volt samples so a real trace can later be
rendered.
The sample array is sensitive health data: it is held AES-256-GCM encrypted
at rest in the new EcgRecording.waveformEncrypted Bytes column (fail-closed
crypto), with the sampling frequency, sample count, duration, lead, average
heart rate, and AFib verdict kept as plaintext descriptors. A re-sync upserts
on (userId, source, externalRecordingId) so a recording is never duplicated;
a waveform fetch failure never fails the verdict ingest. Rendering UI is a
follow-up.
Define the go-forward aggregated heart-rate upload shape so clients can
stop posting one Measurement per raw HealthKit sample. A heart-rate row
keyed `stats:HKQuantityTypeIdentifierHeartRate:<bucket-start-hour>`
carries the hour's average bpm as a single PULSE row and rides the
existing `stats:` overwrite path: a re-post within the hour overwrites
the value instead of duplicating, identical to the per-day cumulative
rows. The hour boundary is UTC so the key is timezone-stable.
The batch route rejects a row that targets the heart-rate bucket prefix
with a malformed hour suffix as a per-entry skip
(`malformed_hr_bucket_id`) rather than persisting an un-overwriteable
row; well-formed buckets, per-sample uuid ingest, and the per-day
cumulative overwrite path are all unchanged.
Average-only for now — the measurement row carries a single value
column, so hourly min/max would need a schema change and is left as a
follow-up. Documents all three externalId shapes plus the `updated`
status in the OpenAPI contract.
The medication detail clients computed the supply headline in the browser
via summariseSupply, risking web/iOS drift and pulling the shared math
into the client bundle. The GET /api/medications/[id]/inventory route now
computes the canonical SupplySummary server-side through summariseSupply
(the single source of truth) and ships it in the DTO; the Bestand and
Übersicht surfaces render the ready figures. Adds the MedicationSupplySummary
schema to the inventory list response and regenerates the OpenAPI contract.
The muted mood treatment (opacity-55 on the tag bars, fillOpacity 0.55 on the
distribution and weekday charts) read as a rendering glitch rather than a
deliberate calm tint. Drop the dimming so every mood bar paints at full
saturation in its level hue; the guard test now asserts the dimming stays gone.
A separate mood colour concept can be revisited later.
summariseSupply is rendered by the medication detail client surfaces, so the
v1.18.11 underflow wide-event it called pulled node:async_hooks into the client
chunk and failed the production build. Split the observability out: the helper
stays a pure clamp, a new pure detectSupplyUnderflow reports a would-be negative
pool, and the low-stock job emits the medication.inventory.underflow event at
its request-scoped seam where annotate can actually fire.
The codex vision gate accepted any gpt-5 prefix, which included the gpt-5-codex
specialist slugs that the surrounding contract documents as text-only. Each lab
OCR upload on such a slug burned a doomed image attempt before falling back.
Exclude the -codex slugs from the gate so multimodal gpt-5.x slugs still report
vision while the codex specialists stay on the text path.
The split commits added the directory barrels but left the original
single-file modules in the tree; Node resolves the .ts file ahead of the
directory index, so the barrels were shadowed. Remove the originals so
the split modules are the live source.
The v1.18.11 briefing now folds illness-episode and cycle state into the
prompt via buildBriefingIllnessCycleContext, which resolves module gates
through memoizePerRequest and queries cycleProfile. The generate route test
mocks neither getEvent nor the cycle/illness models, so every case threw once
the new call path ran. Stub the context module to no output and add the
getEvent export to the logging-context mock so these cases stay scoped to the
provider and cache behaviour they assert.
Weight and BMI move on a weekly cadence, but the per-metric generators
rebuilt the full snapshot (bounded findMany + per-series rollup reads +
correlation math) every day and relied on the post-build content-hash gate
to skip only the model call. Add an input gate that runs first: a single
grouped probe over the salient inputs (per-type count + newest reading, plus
mood for weight and the profile height for BMI) fingerprints what the
snapshot would read. On a non-forced run whose fingerprint matches the cached
row, the cached assessment is re-stamped under today's key and the whole
build is skipped. A miss falls through to the normal build and the existing
post-build gate.
Consent is checked before any re-date so a revoked-consent user never has
stale text presented as current. Forced runs never gate but still record a
fresh fingerprint for the next day.
The 02:00 status cron now runs generateStatusBatchForUser for every eligible
user: it builds the seven per-metric snapshots once and issues a single
provider call for the metrics still needing the model, fanning each summary
back into the same per-metric cache rows the standalone generators write.
The six later per-metric crons (02:05-02:30) keep their drivers but now hit
the calendar-day cache the batch already filled, so they resolve as cache
reads and only cover the edges — a user discovered after 02:00, a metric the
batch omitted, or a batch-call failure (which the batch falls back per metric).
Reproducibility and the consent/grounding gates are unchanged: the batch runs
through runStatusCompletion, which still pins the reference seed.
Drops the now-unused per-metric general generator and recordRun plumbing.
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).
The daily_cardiovascular_age collection reports a years-unit arterial-age
estimate that maps directly onto the existing VASCULAR_AGE metric, so no
migration is needed. Resilience stays out: it is a categorical level with
no numeric home and would require a new type plus a categorical column.
The Heart List endpoint returns a per-recording AFib verdict from the
ScanWatch family that no sync fetched. Capture each recording as an
IRREGULAR_RHYTHM_NOTIFICATION event row carrying the device's own verdict
in rhythm_classification, mirroring the Apple Health categorical-event
treatment. Reuses the existing enum, column, and constraint, so no
migration. Fires on the measure webhook path, which shares the metrics
scope the Heart List endpoint needs.
The briefing only reached the dashboard as the hero's lowest-priority
verdict, which the severity ladder almost always pre-empted, so a fresh
briefing was invisible above the fold. Lift its own signals (falling back
to key findings) onto the hero as a self-gating strip beneath the verdict
row, reusing the insights briefing's tone-bar row language. Placement
only: the verdict ladder and the briefing content are unchanged.
The dense intra-day retention drain folds out-of-window per-sample PULSE rows
to one daily-mean row to bound the high-frequency ingest. The mean-only fold
erased the two clinically-meaningful daily figures derived from the raw
stream: the resting estimate (20th-percentile of each day's PULSE, the
fallback for users without a native resting series) and the daily min/max held
in the persistent rollup DAY bucket.
Preserve both in the PULSE facet of the fold:
- Recompute the PULSE DAY rollup from the raw rows before the fold, while they
are still live, so the bucket keeps the true intraday min/max/mean; skip the
post-fold recompute that would collapse them.
- For users with no native resting series, mint one derived RESTING_HEART_RATE
row per folded day from the day's 20th percentile, sourced COMPUTED so it
never collides with measured resting rows and reads back as the clean
resting series. Users with a native series are skipped to avoid
double-counting; the probe is memoised per user.
Add a per-day failure boundary so one poisoned day can no longer abort the
whole walk. Surface the derived-resting count through the handler return,
the wide-event annotation, and the worker log.
Add a labs block to the coach snapshot so the assistant can answer
questions about the user's lab results. Each entry is the most recent
reading per biomarker over the last 12 months (capped), carrying the
resolved name, value, unit, reference range, in/out-of-range verdict,
and measured date. Qualitative readings (e.g. negativ) are included
with a neutral range status. Values resolve server-side via the same
helpers the labs API uses, and the system prompt instructs the model to
quote them verbatim and never invent a lab number, so the block stays
grounded. The free-text qualitative result is sanitised before it can
reach the prompt; the encrypted note is never read.
The Coach page opened a blank new chat regardless of where the user came
from. Make it a deep-link target: a `?c=<id>` query param opens that
thread on mount, and absent it the page auto-opens the user's most-recent
conversation. "Most recent" is the `updatedAt desc` head of the rail
list, so the same thread opens on web and mobile.
The shared conversation surface grows two additive props
(`initialConversationId`, `autoOpenMostRecent`) that feed its existing
selection state; the history drawer's selection stays the single source of
truth. The drawer surface is unchanged — both props default off and the
rail list is only fetched when auto-open is requested.
Add a central sanity gate in summariseSupply, the single helper every
supply readout flows through. A corrupt or legacy row with a non-finite
or negative unit count could pool straight into the headline and surface
a nonsensical negative Bestand; the helper now floors the pooled
remaining, total and expired figures at zero and emits a
medication.inventory.underflow wide-event when a raw value would have
gone negative, so the underlying data defect stays observable.
closes#31
Serve achievements via SWR and precompute Berlin day-keys to kill the per-row
Intl cost; switch dashboard/summary to cachedSwr; lazy-load three charts that
bypassed the dynamic boundary.
Bound the comprehensive briefing's feature read to 400 days while keeping
all-time extremes honest via a full-history groupBy, and append module-gated
illness and cycle context to the briefing prompt.
Achievements: the bucket was 60 s hard-TTL while the app-wide unlock
notifier polls every 2 minutes, so every poll landed on an expired
entry and fired a cold ~400 ms rebuild in the foreground. Add a
10-minute stale-while-revalidate window and read the route through
cachedSwr; the route already persists pendingUnlocks outside the cached
factory, so a stale serve never skips an unlock write.
Achievements builder: the vitals array ran through several full-array
passes, each re-deriving a Berlin day-key (and hour) per row via
Intl.DateTimeFormat. Compute each row's day-key once and thread the
parallel array into the green-day, weekly-consistency, engagement, and
hidden passes; the hidden pass reuses a single precomputed hour array.
Results are byte-identical to the per-row derivation (parity test added).
dashboard/summary: read through cachedSwr so the iOS-polled endpoint
serves its existing 1 h stale window instead of re-paying the cold
rebuild every 60 s on the plain cached path.
Charts: route the three recharts consumers that bypassed the shared
next/dynamic boundary (lab biomarker chart, sleep stage stacked bar,
recommendation rationale charts) through dynamic imports with matching
loading skeletons, taking recharts off the first-load JS for
/labs/[id], /insights/sleep, and the insights recommendations surface.
Bound the comprehensive briefing's feature read to a 400-day window instead of
walking the full measurement history on every generation. All-time min/max/avg
are sourced from one grouped aggregation over the whole history, so the
allTime* fields stay honest while the unbounded row materialisation is gone;
the oversize downgrade ladder remains as the safety net.
Fold illness-episode and cycle state into the briefing prompt, reusing the
server-authoritative builders the Coach already assembles. Both are
module-gated and cost nothing for users without them, so a mid-illness or
mid-cycle user finally gets context-aware prose.
Surface non-ok geo-lookup responses as a warning instead of swallowing them,
make the lookup provider/URL override explicit, and whitelist TRUST_CF_CONNECTING_IP
+ the geo env in compose so the real visitor IP is stored behind Cloudflare.
Fold image input into the Codex client (input_image over the ChatGPT-OAuth
responses endpoint, no API key); make the codex vision gate model-aware; resolve
labs OCR to vision mode for multimodal codex with safe text/local-OCR fallback.
The ipwho.is default rejected server-side egress with a 403 on the free
plan, which the resolver swallowed as a clean miss, so the admin
login/audit overview rendered "—" for every session. Switch the default
online provider to ip-api.com (the parser already accepts its
status/countryCode shape) and surface a non-ok HTTP status (403/429/5xx)
as a wide-event warning instead of returning null silently, so a future
provider rejection is visible.
Whitelist TRUST_CF_CONNECTING_IP, IP_GEO_LOOKUP_URL and
IP_GEO_LOOKUP_DISABLED in the compose environment block and document them
in .env.production.example so a Cloudflare-fronted deployment can store
the real visitor IP rather than the edge address.
Image input rides the ChatGPT-OAuth codex/responses endpoint via the
input_image content block (protocol spec 2b) — no vision API key. The
codex client folds params.images into input_image blocks alongside the
input_text; text-only calls keep the prior byte-identical wire. The
vision gate now resolves codex capability against the working slug
(GPT-5.x / gpt-4o-class multimodal) instead of a blanket false, with the
OCR capability resolver feeding the codex slug rather than the user's
aiModel. A non-multimodal slug or an image-block rejection degrades to a
clean extract failure / local-OCR text mode.
Rework the Coach page to a ChatGPT-style IA: drop the top header, make the
composer the control hub (+ actions, settings, mic), open history as a left
slide-in drawer, and keep the composer one constant width across new-chat and
active conversation. The FAB drawer surface is untouched.
Drop the dedicated page's top header bar and the conversation-history
strip. The composer now carries the controls: a leading actions menu
(new chat + open conversations) and a settings deep-link beside the mic
and send. Conversation history opens as a left slide-in drawer that works
on phone and desktop.
Pin the composer to one centred, max-width-capped column shared with the
thread so its width stays constant from the new-chat hero into an active
conversation. The drawer surface keeps its own header and body chrome
unchanged.
Data-loss fix, measurement consolidation, AI grounding, full-page Coach, local OCR, Withings sleep vitals, and broad polish. Six upfront audits + diff review; CI green.
Marc-André Bombeck