Apply safeJson's opt-in maxBytes ceiling to the body-accepting batch
and export routes that lacked one. The cap measures the raw text
before JSON.parse, so an over-limit payload returns a clean 413
without buffering onto the heap.
- workouts/batch: reuse the existing 5 MB ceiling so chunked uploads
with no Content-Length are bounded too.
- measurements/batch: 4 MB — an order of magnitude above a 500-entry
batch's few-hundred-KB worst case.
- export/health-record: 64 KB — the selection payload is small and
bounded.
Each cap is a DoS ceiling sized well above any legitimate payload,
never a tight bound on a real batch.
The v1.10.0.2 kill-switch defaulted the drain OFF after the P2002 fold
collision. With the fold reworked to coexist with the canonical daily row
and integration-tested against real rows, flip the default back ON
(DENSE_INTRADAY_RETENTION_ENABLED=true unless explicitly set to false). The
boot-discovery still defers past the startup storm via the boot-delay so it
never contends for the connection pool on a data-heavy tenant; the nightly
03:50 walk and the per-user handler run again.
The dense intra-day retention fold minted its daily-mean stats: row with
an externalId-keyed upsert. On real data a row already occupies the
canonical local-noon instant — a sibling daily stats: row or a per-sample
HRV/PULSE reading that fell on noon — so the upsert lookup missed (the
existing row carries a different externalId) and the INSERT then violated
the (user_id, type, measured_at, source, sleep_stage) unique index with
P2002. The mocked unit tests could not surface it.
Resolve the canonical row by the measured_at composite the collision is on
(sleep_stage IS NULL for these continuous types, matched via the
NULLS NOT DISTINCT index) and adopt it in place — refresh the mean, stamp
the canonical stats: externalId, un-tombstone — or create it when absent.
Exclude the adopted row id from the per-sample soft-delete so a noon-instant
sample becomes the daily row instead of being tombstoned.
Add a testcontainer integration test that seeds the colliding shape (a
pre-existing canonical-instant row plus out-of-window per-sample rows) and
pins no-P2002, coexistence, the noon-sample case, idempotency, and the
retention bound. Update the unit coverage for the adopt-in-place path.
Extend the symmetry suite to assert both cards render the byte-identical
next/last slot wrapper (same reserved min-height, spacing, muted colour,
next-then-last order, no em-dash placeholder, no brighter foreground
token) and a constant-height bottom-pinned body across oral / injection
/ GLP-1 / PRN / one-shot, including the compliance-skeleton path. Update
the dose-accent assertions onto text-dose-accent and the GLP-1 rotation
test onto the folded-into-line nudge. Clock stays pinned.
Route both the generic and GLP-1 cards through the shared next/last
slot, ending the divergence that made two meds of different types read
differently in the same grid row:
- the GLP-1 card showed last-then-next; both now show next-then-last;
- its next line painted text-foreground/85; both now use the muted token;
- its inner spacing was space-y-1; both now use space-y-3.5;
- it always rendered the next line and printed a literal em-dash when
there was no next injection; both now gate the line on an actual next
and drop the placeholder.
Make CardContent a flex column and pin the action row with mt-auto.
Combined with the reserved next/last slot and the constant-height
compliance skeleton, every card body is now equal height, so the pin
aligns the take/skip buttons across a grid row without opening the void
that an unequal-height pin produced before.
Fold the GLP-1 injection-site rotation nudge into the upcoming-injection
line instead of a separate bordered block, so the GLP-1 card keeps the
same row inventory and height as the generic card.
Repoint both cards' dose accent onto text-dose-accent, drop the GLP-1
compliance query's active-only enabled guard so both cards make the same
calls, and share the weekday-label helper.
The medication cards stamped the upcoming schedule dose with Tailwind
stock text-purple-400, which reads ~3.1:1 on the white Alucard light
card and fails WCAG AA for body text. Add a theme-aware --dose-accent
token: the exact text-purple-400 oklch in dark mode (so the dark card
stays pixel-identical) and a darker AA-safe purple on the light card,
mirroring how the semantic feedback tokens land each tone above AA in
both themes. The cards switch to text-dose-accent in the follow-up
commit.
Extract the medication-card middle slot into a shared
<MedicationNextLastSlot> so the generic and GLP-1 cards render an
identical next/last region — same order (next then last), same
text-muted-foreground colour, same space-y-3.5 spacing, same reserved
min-height, and the same gating (the caller passes a next line only when
one should show; the part never prints a placeholder). A shared
useWeekdayLabel helper collapses the two weekday i18n key families onto
the abbreviated form so the same weekday no longer renders 'Monday' on
one card and 'Mon' on the other.
Add a MedicationComplianceSkeleton that reserves the compliance block's
footprint while the per-card query is in flight or returns null, so a
card without compliance is no longer ~5rem shorter than its grid-row
sibling.
The reminder worker failed to start in the production bundle with
`ReferenceError: Cannot access 'l' before initialization`, taking every
nightly pg-boss job down with it (score jobs + dense-intraday retention).
Root cause is a value-level import cycle between `consolidation-base.ts`
and `drain-per-sample-cumulative.ts`: each imported values from the other.
The bundler merges the tightly-cyclic pair into one module body and hoists
`DRAIN_CUMULATIVE_CUTOFF_HOURS = CONSOLIDATION_GRACE_CUTOFF_HOURS` ahead of
the constant it reads, so the eager read hits a temporal dead zone. It only
surfaced in the production build because dev/test run the modules unbundled.
Hoist the shared leaf — `CONSOLIDATION_GRACE_CUTOFF_HOURS`, the `PerSampleRow`
shape, and the timezone day-math helpers — into a new dependency-free module
`consolidation-tz.ts`. Both sides now import from the leaf, removing the cycle
at its root. Re-export the moved names from their former homes so every
existing import site resolves unchanged.
The semantic-token swap means the trend arrow/delta now emit
text-success/text-warning (pixel-identical in dark, AA-safe in light), and
the batched derived route joins the insightStatus allowlist alongside the
single route. Update the trend-card sentiment-colour assertions and the
coach-route gate inventory accordingly.
Only Sleep and Readiness reached a provenance surface; the other nine
shipped a number with the cited standard buried in a code comment. Give
every derived metric a path to its inputs + method + cited standard:
- Recovery, Stress and Strain get a ScoreAnatomyView detail page and a
tappable ring (they were read-only dead-ends). Stress surfaces its
'HRV-derived proxy, NOT an EDA/galvanic measurement' caveat; Strain
cites the TRIMP load model; Recovery the HRV-guided recovery literature.
- The vitals tiles (baseline, HRV balance, BMI, fitness age, vascular age)
gain an info explainer affordance carrying the method + standard, since
they render as tiles with no detail page.
- The coincident-deviation flag gains a dashboard tile (shown only when it
fired) with the same explainer (median ± k·MAD basis).
- A single standards map (src/components/insights/derived/standards.ts)
pins each metric's method copy key, standard name and a real linkable URL
(DOI / WHO / Wikipedia) so the citation a metric exposes stays one source.
Add the per-metric method/caveat/description copy across all six locales.
Map storage units to display symbols so a baseline tile reads '36.6 °C',
not '36.6 celsius'. Show the band word under the strip rings so a value
reads 'low 62', not a bare reddish 62. Drop the empty dashed sparkline
placeholder when no trailing series exists rather than reserving dead
space, and give the tile a series + provenance slot for when one does.
The Insights cold mount fired 14+ independent GET /api/insights/derived
requests — Readiness, Sleep and the vitals baselines are compute-on-visit,
and all of them share one Prisma pool. That is the pool-starvation class
that surfaces as the app hanging then recovering.
Add GET /api/insights/derived/batch?metrics=a,b,c[:type] that resolves the
requested metrics server-side under a bounded p-limit(4) with the profile
loaded once via the shared loadBaselineProfile, returning a map of the same
flat Derived<T> envelope keyed by the request token. Add the useDerivedBatch
hook + the insightsDerivedBatch query-key factory entry; the single-metric
route + hook stay for the per-score detail pages. The single route now also
adopts loadBaselineProfile instead of re-inlining the profile read. Honors
the existing 8s ceiling, retry:0, replace-with-fallback, and warms nothing
on visit. Register the new route in the OpenAPI contract.
The band primitives (score ring, coverage dots, contributor bars,
provenance chips + standard link, sparkline tint, trend arrow/delta)
painted straight from the raw `--dracula-*` variables, which carry no
`:root.light` override. On the white card the Alucard light theme uses,
the green/orange/yellow cleared roughly 1.1-1.5:1 — under AA — and the
`bg-dracula-yellow` confidence dot read near-invisible. The file comment
claimed they 'track automatically'; they did not.
Point BAND_NUMBER/PROGRESS/BORDER/VAR, the coverage-meter dot tint, the
provenance cyan chips, the sparkline stroke, and sentimentColorClass at
the semantic `--success`/`--warning`/`--destructive`/`--info` tokens
instead. Those alias the same Dracula tones in dark mode (pixel-identical
there, the primary target) but carry the darker AA-safe values under
`:root.light`. Clamp the score-ring provisional caption to one line so a
longer localised string cannot wrap over the ring arc.
WRITABLE_MEASUREMENT_SOURCES was a dead export whose docblock claimed it
gated the single-entry POST, but the schema only refined out COMPUTED —
WITHINGS and IMPORT stayed client-writable, so a client could attribute a row
to a source the server owns (the Withings webhook / CSV importer) and pollute
the per-source canonical picker. Wire createMeasurementSchema.source to a Zod
enum built from the now-correct {MANUAL, APPLE_HEALTH} allowlist; the enum
subsumes the old COMPUTED refine. Regenerate the OpenAPI contract.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The readiness and coincident-deviation composites passed historyDays =
windowDays (a constant) into deriveCoverage, pinning historyFraction to 1 so
a 7-day and a 30-day blend reported identical confidence. Pass the real
distinct-history-days backing the composite (the depth of the
best-supported present contributor) so confidence tracks actual depth.
The readiness provenance source was derived only from RHR/HRV/respiratory, so
a blend backed solely by sleep + mood could mislabel as DAY. Fold the present
sleep + mood provenance in so the source chip matches what actually backed
the headline.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The sleep-score consistency + timing sub-scores measured the midpoint as a
linear minutes-of-day difference, so a sleeper whose midpoint straddles
midnight (and any night across a DST shift) read a spurious ~24-hour spread
that inflated the SD and timing distance. Measure the midpoint on the
circular 24-hour clock (mod 1440) — a circular mean for the habitual midpoint
and a circular distance for the SD and timing offset.
Efficiency clamped asleep > in-bed (overlapping HealthKit stages) silently to
100, masking a data problem. Handle the overlap explicitly: a small overshoot
caps at the AASM ceiling of 100 (asleep cannot exceed time in bed), a gross
overshoot drops the sub-score because the in-bed denominator is not usable.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
computeHrvBalance read recentAvg = baseline.value.center, which is the band
midpoint by construction and therefore always inside [low, high] — so the
"low" and "unbalanced" arms were dead and the card could only ever read
"balanced". Compute recentAvg from the last <= 7 DAY means (the recent
trend) and place that against the longer-window personal band, so a
suppressed recent trend flags "low" and an elevated one flags "unbalanced".
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The Recovery/Stress/Strain crons fire in the small hours (04:45-04:55
Europe/Berlin, ~03 UTC) but scored the CURRENT UTC day, only a few hours
old: Strain missed the just-completed day's workouts and Stress saw a
near-empty intra-day SDNN set and falsely gated as insufficient. Score the
day that just ended (now - 1 day) across all three engines and their
measuredAt / externalId day stamps.
Resolve the previous-day key in one place by extracting the shared score-row
helpers the three engines each duplicated: scoreDayKey / scoreMeasuredAt /
scoreExternalId, the idempotent upsertScoreRow, and the cohort runScoreBatch
tally loop into src/lib/insights/score-row.ts; and loadBaselineProfile into
the baseline engine (the three byte-identical profile loaders + the partial
strain variant now route through it). The derived route should adopt
loadBaselineProfile too.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
When a derived wellness score (readiness or recovery) crosses a notability gate
— outside the green band AND confidence at least medium — the insights
generator now appends a SYSTEM CONTEXT block so the briefing can narrate the
shift observationally. Mirrors the GLP-1 plateau detector's append mechanism:
reads the one derived contract, returns null (the common case) at zero token
cost, and instructs the model to frame the signal as an observed pattern, never
a diagnosis or a dose recommendation. Add the readiness/recovery sourceMetric
enum values plus their briefing href + icon + trend-chart mappings.
Surface the server-derived nightly scores (recovery / stress / strain) in the
health-record export without polluting the clinical layer. The aggregator now
emits a wellnessScores summary (latest / avg / min / max / count per score over
the window) built from the already-fetched COMPUTED rows. The PDF renders them
in a clearly-labelled "Wellness summary" section, separate from the clinical
vitals table, with a "descriptive, not a clinical assessment" disclaimer. The
FHIR bundle emits one Observation per score under the survey category with a
text-only concept and the same disclaimer as an Annotation note, so a viewer
never mistakes a band for a diagnosis.
Add a "derived" block to the Coach snapshot: one tiny object per high-signal
derived metric (readiness, recovery, sleep, stress, strain, HRV balance,
cardio-fitness band, vascular-age delta) carrying value + band + confidence +
historyDays — never the raw series. A fully-populated block is ~250 tokens,
comfortably inside the snapshot budget. Insufficient metrics are omitted so the
model never sees no-data noise; each metric's compute is fault-isolated so a
transient failure on one never sinks the turn. Gated on the underlying signals
staying in scope. The system prompt now documents the block and frames the
bands as descriptive composites, not clinical findings.
Add a wellness-scores section to the vitals dashboard: a row of score rings for
Readiness, Recovery, Sleep, Stress, and Strain. Every ring is
data-availability-gated — a score with no underlying data simply does not
render, so the strip never shows an apologetic empty ring. Readiness and Sleep
are tappable and route to their existing score-anatomy detail pages; the
persisted nightly scores render read-only. Every ring reads the one
/api/insights/derived route through the shared useDerivedMetric hook.
Register RECOVERY_SCORE / STRESS_SCORE / STRAIN_SCORE as derived metrics that
read the nightly-persisted COMPUTED Measurement rows — a passthrough, never a
recompute. The dispatcher routes the three ids to a thin reader that returns
the latest score, a trailing-window trend, and a direction-aware band (stress
and strain invert, so a high stress reads red). This lets every surface — the
dashboard, the Coach snapshot, the doctor report — consume the scores through
the one Derived<T> route + hook rather than each growing its own read path.
Regenerate the OpenAPI enum, which picks up the three ids from the registry.
Two parallel loaders for the generic derived-metric route had grown — a
components-local hook keyed on a 4-element tuple and a hooks/ hook keyed on a
3-or-4-element tuple. Both shared the ["insights","derived",metric,…] prefix
with different tuple shapes, which silently poisons the TanStack cache between
surfaces. Collapse to the single components-local hook (auth-gated, 8 s client
ceiling, retry-free) on the one insightsDerived factory key; the fourth slot is
always present so the metric prefix can no longer carry two shapes.
Wire the two nightly score passes and the dense intra-day retention drain
into the worker. The stress (04:50) and strain (04:55) crons each get a
queue, a schedule, and a single-flight handler; the dense-retention drain
gets a per-user backfill queue with boot discovery (like mean-consolidation)
and folds its steady-state nightly walk onto the existing drain-cumulative
tick, after the daily-mean fold.
A queue not registered in allQueues silently never drains, so a source-grep
guard pins every registration site for all three jobs.
Derive a daily cardio-load proxy from the per-workout heart-rate series
plus active energy. Each workout's HR series scores via Banister's
gender-weighted exponential TRIMP over the fractional heart-rate reserve
(Tanaka age-predicted HRmax, the user's resting HR); the day's TRIMP totals
map to a 0-100 saturating scale. Days with no usable HR series but a
non-trivial active-energy total fall back to an energy-only proxy, with the
path recorded in the result.
Stored as a COMPUTED STRAIN_SCORE row, idempotent per user per day, gated
when neither a usable HR series nor active energy is present.
Standard: Banister 1991; Morton, Fitz-Clarke & Banister 1990 (TRIMP);
Tanaka, Monahan & Seals 2001 (HRmax).
Apple Watch has no electrodermal sensor, so there is no direct stress
measurement to read — what HealthKit does give is discrete SDNN samples
through the day. Derive an honest HRV-through-day PROXY: a suppressed,
below-baseline intra-day SDNN is a recognised marker of higher sympathetic
load. The provenance and label say "HRV-derived proxy" and never imply a
galvanic/EDA reading.
The engine reuses the shared vitals-baseline math (the same SDNN baseline
the wellness index reads), maps the day's below-baseline suppression to a
0-100 score, and stores it as a COMPUTED STRESS_SCORE row — server-owned, a
client can never POST it. It gates and writes nothing below the minimum
intra-day sample floor or without a usable baseline.
Standard: Kim et al. 2018 (HRV and stress meta-analysis); Thayer et al. 2012
(neurovisceral integration). Idempotent per user per day via the nightly job.
Daytime heart-rate-variability (SDNN) and heart-rate samples need to keep
their intra-day shape long enough for the stress engine to read them, but
the raw per-sample volume must stay bounded. Add a retention tier that
keeps the last 14 days of raw HRV/HR samples and folds everything older to
one daily-mean row via the proven mean-consolidation drain (same idempotent
stats:<HK>:<day> fold, soft-delete, and rollup recompute).
The two dense-tier types are deliberately EXEMPT from the destructive
daily-mean drain allowlist (HIGH_FREQUENCY_MEAN_TYPES) — that drain would
collapse the intra-day shape and soft-delete the raw rows. A regression test
pins both exclusions so a future edit that adds either type to the drain
allowlist fails loudly.
Migration 0108 adds only the partial index that keeps the retention drain's
discovery and per-user scan cheap; the retention bound lives in code so
tuning it never needs a migration.
Replace the generic page description with the self-hosted positioning —
Withings + Apple Health sync, transparent derived wellness metrics, and
AI Insights you own — so the search-result snippet matches the README
and landing copy. OpenGraph and Twitter card descriptions are unchanged.
Add a recovery-score engine that turns a user's already-stored nightly
signals into a stored 0-100 score. It reuses the readiness blend — the
resting-heart-rate, HRV (SDNN), sleep and respiratory-rate deviation
from the personal baseline, with the null-redistribution the health
score already uses — so the stored series and the live readiness surface
can never drift. The lineage is the recovery-marker literature (Plews
2013, Buchheit 2014): a higher score reads as more recovered. It is a
descriptive wellness proxy, not a clinical or training-recovery
assessment, and it is only stored when enough components are present —
below that floor no row is written rather than a headline from one
signal.
A nightly job computes each eligible user's score and upserts it as a
COMPUTED RECOVERY_SCORE row, idempotent per user per day on the
externalId day key, so a re-fired tick overwrites in place instead of
duplicating. The score is never computed on a page visit. The queue is
registered in the worker's queue inventory, scheduled, and wired to a
handler; a grep guard pins all four points so it cannot silently never
run.
Add a server-owned COMPUTED measurement source for rows a server engine
derives rather than a device or a person reports, plus three first-class
0-100 score types — RECOVERY_SCORE, STRESS_SCORE, STRAIN_SCORE (unit
"score", plausibility range 0..100).
COMPUTED is read-only from a client's perspective: it joins the read /
decode enum so the native client can decode the rows it queries and
charts, but every client-facing write surface rejects it exactly like
WITHINGS and IMPORT — the batch ingest allowlist stays {APPLE_HEALTH,
MANUAL} and the single-entry POST 422s a COMPUTED source.
All three score types thread through every type-exhaustiveness site: the
unit + plausibility-range maps, the PR-direction resolver (scores carry
no record direction, like the device events), the category overlay (a
new "scores" cluster), the list-view label / icon / colour maps with
locale strings across all six bundles, and the insight chart-token
allowlist + orphan-enum stripper. They are not clinical vitals, so they
stay out of the doctor-report PDF.
Only the recovery score is computed today; the stress and strain types
are defined now so the engines that compute them later need no schema
change. Migration 0106 is purely additive (ADD VALUE IF NOT EXISTS).
Raise the per-export administration ceiling from 1000 to 5000 (~3.5 years
at four doses a day) and resolve it from FHIR_MAX_MEDICATION_ADMINISTRATIONS,
bounded 1..50000 with a fallback to 5000 on an unset or out-of-range value.
The windowed-then-capped newest-first behaviour and the honest-truncation
narrative are unchanged; this only raises the ceiling so it bites far less
often. Add the var to the compose environment whitelist and the production
env example so it reaches the container and check-env stays green.
The builder already accepts a germanAtc option that appends the BfArM ATC
URI after the WHO entry. Thread it from the health-record export route: an
explicit germanAtc flag on the selection payload wins, otherwise it derives
from a German-region locale. The WHO coding stays coding[0], byte-identical
and locale-independent, so a WHO-only consumer is unaffected.
Add the optional germanAtc field to the strict export selection schema and
regenerate the OpenAPI contract.
Emit a SNOMED CT coding alongside the existing .text anchor on the
administration dosage. Route maps ORAL to 26643006 (Oral route) and
INJECTION to 34206005 (Subcutaneous route, the form HealthLog injections
take). Site keys on the eight InjectionSite enum values, collapsing to the
three gross body-region concepts (abdomen 818983003, thigh 68367000, upper
arm 40983000); laterality and the abdominal quadrant stay verbatim in the
.text anchor rather than inventing lateralised concepts.
Referencing concept ids in a FHIR instance is not redistributing the
licensed SNOMED distribution, so this is safe to ship. The .text anchor is
unchanged, so a consumer without a SNOMED binding is unaffected.
Reconcile the dose fixture to the real uppercase enum value the live
builder emits (the previous lowercased value never matched production).
Add mapping tests for the five event classes (verdict resolution,
severity grading, the value-pinned-to-1 contract, unknown-codepoint
fallback, and that a continuous measurement never gets a classification),
the awareness-card gating + device-verdict framing + disclaimer presence,
and the events route narrowing + empty-state contract. Extend the enum,
chart-token and Coach-gate drift guards for the new event types.
Add a timeline of the health notifications the user's device produced on
its own, reachable from the Insights overview. The surface reflects the
device's own decision: each row reads "Your device flagged …" and a
permanent disclaimer states this is not a medical assessment by
HealthLog and that HealthLog does not diagnose any condition.
The surface is data-availability-gated — it un-mounts entirely when the
user has no such events, so an account that never triggered one never
sees an empty or alarming card. Copy renders as plain React text
children; no markdown library is involved.
Accept the optional HKCategoryValue codepoint on each batch entry and
persist the resolved rhythm_classification on the stored row. The wire
field is additive and ignored for non-event identifiers, so every
existing caller is byte-for-byte unchanged. Regenerate the OpenAPI
contract.
Add a discrete EVENT row class to the Measurement model for the
device-flagged health notifications a wearable produces on its own —
irregular-rhythm, high/low heart rate, walking-steadiness and
breathing-disturbance alerts.
Following the sleep-stage / glucose-context nullable-context precedent,
this is an additive nullable column on the existing table, not a new
storage paradigm. Five new MeasurementType values carry the event class
and a new rhythm_classification enum column carries the device's own
verdict / severity (migration 0105, with a CHECK that pins the column to
the event types). An event row stores value 1 and the device verdict;
it never participates in trend, rollup, chart or personal-record
analytics.
For the irregular-rhythm class, HealthLog ingests only the
classification RESULT the device's own certified on-device algorithm
already produced. It never ingests a raw ECG waveform, never
re-classifies, and never derives a verdict of its own.
The Apple Health batch ingest maps the five category identifiers, with
the device's HKCategoryValue codepoint resolved to the stored
classification; an unknown codepoint degrades to a fallback verdict
rather than dropping the event.
Wire seven previously-deferred HealthKit quantity identifiers through
the full pipeline — enum, mapping, plausibility range, category, list-UI
metadata, FHIR coding, and the generic metric-status assessment:
CARDIO_RECOVERY heartRateRecoveryOneMinute bpm
WRIST_TEMPERATURE appleSleepingWristTemperature celsius
FALL_COUNT numberOfTimesFallen count
SIX_MINUTE_WALK_DISTANCE sixMinuteWalkTestDistance m
STAIR_ASCENT_SPEED stairAscentSpeed m/s
STAIR_DESCENT_SPEED stairDescentSpeed m/s
BREATHING_DISTURBANCES appleSleepingBreathingDisturbances count
Each value rides raw on the wire (identity conversion). Fall count is
cumulative (daily SUM); the stair speeds drain to a daily mean; the rest
store as latest per-workout / per-night spot readings. Wrist temperature
and breathing disturbances are flagged privacy-sensitive. The category
sleep-apnea and walking-steadiness EVENT identifiers stay deferred — they
are events, not quantities.
Each new metric gains an Insights sub-page on the shared scaffold with the
generic assessment card, localised across all six locales. Cardio fitness
(VO2 max) — ingested since v1.4.23 but assessment-less — gains its own
/insights/cardio-fitness page so it picks up the assessment instead of
riding as a bare chart-row on the pulse page.
Normal-range anchors are cited where defensible (six-minute walk 400-700 m,
ATS guideline + population reference); the rest defer to the user's own
baseline rather than fabricate a band.
Migration 0104 appends the enum values additively (IF NOT EXISTS, forward-only).
Extend POST /api/workouts/batch with an optional per-workout `samples`
array — a route-independent heart-rate series so indoor workouts still
yield a strain-relevant signal. Each entry is `{ t, hr?, speedMs?,
power?, cadence? }`; the array is capped at 30 000 points
(MAX_WORKOUT_HR_SAMPLES), covering a long endurance session sampled at
1 Hz while bounding the largest new workout-side write stream the same
way the 20 000-point route cap bounds the geometry.
Persistence rides the existing route-attachment path: the freshly
written workout id is resolved once (by composite key, or the manual
tuple), then both the route geometry and the HR series attach by FK
with skipDuplicates so a re-submitted batch stays idempotent. A workout
may carry both a GPS route and a canonical HR series, or just one.
GET /api/workouts/{id} returns the series alongside the route. OpenAPI
regenerated.
`samples` keeps first-write-wins/overwrite parity with the workout row
it hangs off: the 1:1 FK plus skipDuplicates means a re-ingest of an
existing workout never duplicates or mutates its series.
Resolve the overlap where the vitals tier and the composite tier both extend
the derived-metric registry, dispatch, query-key factory, i18n bundles and the
OpenAPI contract: every derived metric (vitals baseline, fitness/vascular age,
HRV balance, BMI, sleep score, readiness, coincident-deviation) is now wired and
implemented, the dispatch test asserts the full set, and the locale bundles carry
both the vitals and the score-anatomy/composite strings.
The v1.9.0 equal-height change set the card content to a flex column and
pinned the action buttons to the bottom with mt-auto. On a shorter card next
to a taller one in the grid, that opened an empty gap between the content and
the buttons. The cards already stretch to a shared height via the grid, so the
buttons can sit directly after the content: drop the flex column and the
mt-auto wrapper on both card variants. The reserved dose-row slot stays, so the
dose lines still align across the grid; only the gap is gone.
Build the composite tier of the derived-metrics layer on the shared seam:
- Sleep score — a transparent 0–100 composite from sufficiency, efficiency,
consistency, timing and composition sub-scores over the per-stage sleep
rows, reweighting around any sub-score the data cannot support (a legacy
asleep-only night drops composition gracefully rather than fabricating it).
- Wellness/readiness index — extends the health-score null-redistribution
blend with resting-HR, HRV (SDNN), sleep, respiratory-rate and mood
deviation-from-baseline components; returns insufficient below two present
components so it never headlines from one signal.
- Coincident-deviation flag — counts vitals outside their personal band on
the latest day and fires when two or more coincide, listing the
contributing vitals as possible factors, never a cause or a diagnosis.
Each composite cites its standard, carries coverage + confidence +
provenance, and reweights around missing inputs.
Add an FDR-controlled correlation discovery engine behind
GET /api/insights/correlations: it scans a curated behaviour x outcome
matrix, lag-joins each behaviour day to the next day's outcome, runs Pearson
with the exact Student-t p-value, and applies Benjamini-Hochberg control
across every tested pair so only statistically-defensible patterns surface —
each tagged with n, r, p and the adjusted q, framed descriptive not causal.
Add the score-anatomy detail view at /insights/scores/<metric>: a full
score ring, ranked contributor rows each showing its push/pull and weight
share, and the cited-standard provenance explainer — reused by every
composite, mobile-first and accessible.
Regenerate the OpenAPI contract for the new metric values + the correlation
discovery response, and add the i18n keys across all six locales.
Build the Apple-Health-Highlights grid of personal-vital tiles on the
Insights overview, backed by four new pure derived-metric compute
functions over the established seam:
- cardio-fitness band ("Fitness Age" frame) — VO2max placed against the
FRIEND-registry age/sex norm (Kaminsky 2015), surfaced + trended, never
re-derived.
- vascular-age delta — Withings vascular-age vs chronological age, a
relative wellness indicator (Vlachopoulos 2010 PWV framing), no medical
claim.
- HRV (SDNN) balance — reuses the typical-range engine for the band and
places the recent average as balanced / above / below; SDNN never
relabelled RMSSD; cadence-gated.
- BMI from weight + height — exact WHO classification, the fallback when
no device BMI exists.
Each metric carries coverage + confidence + provenance and cites its
standard through the provenance explainer. The dashboard renders one
SparklineDeltaTile per available vital: an absent vital does not render,
a still-building one shows the honest coverage meter rather than a
headline from too little history. Tiles read the generic
/api/insights/derived route through a TanStack Query hook keyed off the
centralised factory.
Regenerates the OpenAPI contract for the two new metric ids and adds the
vitals copy across all six locales.
Build the four reusable presentational components the v1.10 vitals and
score-anatomy surfaces share: a radial score ring, a coverage meter, a
sparkline delta tile, and a provenance explainer. Each extends the
existing dracula band + trend-sentiment vocabulary rather than a new
colour system, and ships its populated, provisional/empty, and stale
states up front so a sparse-data surface never goes blank.
- score-ring: centred tabular-nums number on a Recharts RadialBarChart,
band-coloured, size prop (sm tile / md / lg anatomy), count-up + sweep
on mount via a 0 KB requestAnimationFrame hook; role=img aria-label
restates the number so the ring is never colour-only.
- coverage-meter: CSS-only filled/hollow dots driven by the Derived<T>
coverage + confidence facets, with an accessible breakdown tooltip
(present vs required inputs, history days, missing list).
- sparkline-delta-tile: extends the trend-card grammar with an inline
Recharts area sparkline, a signed period delta, and an age/normal-range
framing slot.
- provenance-explainer: collapsible Popover (desktop) / bottom-sheet
(mobile) rendering inputs, plain-language method, and an optional cited
standard as React text children — no markdown library.
All four read their data off the Derived<T> union as a type-only import
so the client bundle stays free of the server graph. Recharts only, no
new runtime dependency. New i18n keys propagated across all six locales.
Marc-André Bombeck