A sha256 fingerprint of the compacted feature snapshot is stored beside
every generated text; nightly, forced and ingest-triggered regeneration
all skip the model call when the fingerprint matches and refresh the
timestamp instead. Warms cover only the user's resolved locale and the
blanket per-status eviction after a comprehensive generation is gone —
a lazily-read second locale regenerates on its own miss path. The
ingest debounce widens from thirty minutes to six hours and no longer
deletes cache rows, the visit-triggered warm re-checks freshness at job
start, backs off for an hour after a failure and is capped at two
forced runs per user per day, and its dedup window now outlives the
client poll horizon. An active day drops from hundreds of model calls
to a handful tied to actual data change.
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.
A dose past its slot time but still inside its catch-up window now stays
on the medication card as overdue and takeable instead of yielding to
the next occurrence — the next-due field can therefore carry a past open
slot, flagged with nextDueOverdue. Y-axis padding no longer dips below
zero for series that cannot be negative, so a steps chart stops
suggesting minus nine hundred steps.
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.
Invites move into their own admin section with a real ledger: status
badges, expiry, uses, a redemption history of who joined when (new
redemption table, revocation is now soft so history survives), and an
honest one-time link/QR moment. The assistant self-context grows
structured fields for conditions, allergies and focus — encrypted like
the free text — merges age and gender from the profile into one fenced
prompt block, and asks up to three targeted follow-up questions that
surface as tappable chips above the coach composer. A fourth nudge
trigger gently suggests a check-up when the self-context is stale and
the coach is actually in use.
Users can now tell the assistant about themselves in an encrypted
free-text profile that feeds the coach and briefing prompts as clearly
fenced context, with the coach allowed one targeted follow-up question
when the picture is incomplete. Operators on closed registrations can
mint expiring invite links with a QR code from the admin area; a valid
invite opens registration exactly as many times as it allows and records
who redeemed it. A nightly pass watches three deterministic signals —
low adherence, blood pressure above its target band, a falling recovery
trend — and sends at most one coach nudge per week through the existing
notification channels, gated behind the same opt-outs as every other
assistant surface.
The two-o'clock status crons generated for every account, ignoring both
the per-user coach opt-out and the operator kill switch; they now share
one gated discovery that also skips users the pregenerate pass will
rewarm anyway, and the mood card finally gets the nightly run the other
six always had. Deleted measurements no longer feed any prompt. Locales
without an assistant language fall back to English consistently instead
of German texts with English fallbacks. A rate-limited regenerate stops
claiming success, the dashboard briefing state distinguishes a missing
provider from a pending generation and serves a stale briefing with its
timestamp instead of hiding it, narrative warming actually processes
oldest first, and worker failures reach the error tracker through one
shared reporter while the insight queues gain real retries.
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 top insights navigation was driven purely by data availability: a
sub-page pill appeared whenever its metric had readings in the 90-day
window, with no connection to the per-tile visibility the customize
panel writes. Hiding a sub-page in Anpassen therefore never removed its
nav pill, and the two surfaces drifted apart.
Thread the resolved insights layout into the tab strip via the layout
shell. A pill now shows iff its metric has data AND its slug is visible
in the saved layout; data availability stays the floor, so a
layout-visible metric with no readings still gets no pill. Pills and
group children order by the saved layout order, falling back to the
natural slug order. While the layout query is in flight the strip keeps
the data-only gate, so first paint is unchanged and a slow or failed
layout fetch never suppresses a pill the user has data for.
Add a total slug to manager-group mapping in sub-page-metric so every
routed sub-page resolves to a category, a superset of the tab-strip nav
grouping that also covers the flat pills and the sleep / mood / events
categories the strip never collapses.
Close four findings from the health-score audit:
- Hypotension cliff: the below-floor branch reused the over-target table,
so 1 mmHg under the clinical floor dropped from 100 to ~81 — a 19-point
discontinuity. A dedicated under-floor curve now starts at 100 AT the
floor and descends smoothly (floor-10->70, -20->45, -30->20), so the
score is continuous on both sides of every boundary on both axes.
- Rollup vs live divergence: the graded BP score weighed a high-variance
day 1:1 on the rollup path (one per-day-mean pair) but N:1 on the live
path (N per-event pairs), drifting the pillar by up to ~20 points
depending on DAY-bucket warmth. gradeBpScoreFromSeries now takes an
optional per-pair count; the rollup path passes perDayPairCount so both
paths produce the same score for the same data.
- Resting proxy degenerate days: a day with fewer than three PULSE
samples no longer contributes a resting estimate, so a lone workout
reading can't masquerade as resting HR.
- Pulse-status proxy day boundary: thread the user's timezone into the
resting-proxy day-key so it buckets identically to the targets route.
Fairness anchors unchanged (134/87 -> 57, 165/105 -> 22).
The per-metric and wellness-score assessment prompts gain a premium-advisory
layer: name the earned win, build a little momentum, frame an unfavourable
finding as an opportunity, and close forward-looking. Every existing guard
stays in force — no platitudes, no bare number-echoing, autonomy-supporting,
never alarming, moralising or diagnostic, and the banned-opener and
forbidden-phrase lists are unchanged. The composite-score archetype warms to
a WHOOP/Oura-style recovery coach while staying descriptive, not clinical.
PROMPT_VERSION 5.0.0 -> 5.1.0 so the provenance can slice prose before/after
the tone edit. Cached accounts converge to the new voice within ~24h.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Every surface that applied a resting-pulse target judged the raw PULSE
series against a resting band. Apple Health maps all heart-rate samples
— including workout HR — onto PULSE, and the resting figure onto a
separate RESTING_HEART_RATE type. A single workout emits hundreds of
expected-high samples, so the resting-target evaluation read a large
share "outside target" and tanked the in-target % / consistency even
when the clean resting series averaged a healthy figure.
Judge the resting band against a resting series. A shared helper prefers
RESTING_HEART_RATE; when the user has none it derives a proxy from the
low percentile of each day's PULSE samples, so a dense workout burst
sitting in the upper tail cannot drag the resting estimate up. Applied
to the resting-pulse tile + its consistency strip, the pulse in-target %
in the assessment snapshot, and the dashboard / sub-page classification.
Raw heart rate, where it is merely charted, no longer carries the
resting-band overlay. The doctor report is unchanged — it reports raw
heart-rate stats factually, with no resting-target judgment to mislead.
Add the menstrual-cycle phase as a channel in the existing FDR-guarded
correlation machinery, the same way rated mood factors were folded in —
no new statistics, the same Welch + Benjamini-Hochberg pipeline, the same
day floors and q = 0.10 gate.
Two complementary mechanisms, both confined to a gender-gated surface:
- a categorical luteal-vs-follicular contrast per outcome metric (resting
heart rate, HRV, sleep, steps, weight, basal/wrist/skin temperature),
surfacing one headline finding (resting-heart-rate-by-phase, falling
back to HRV); and
- the continuous phase ordinal folded into the lagged-Pearson matrix.
Phase never reaches the general correlations route — the temperature
channels held out of the general matrix are un-blocked only here, behind
the cycle gate, so a reproductive inference can never leak onto a
non-gated surface. Every row shows n, effect size, p and q; nothing is
fabricated on thin data and nothing is framed as causal.
Surface it through a new gated GET /api/cycle/insights and a drop-in
card that mirrors the mood-factor crosstab.
Add a cycle dimension to the Coach snapshot: current phase + day-of-cycle,
the next predicted event (period range + confidence + method, fertile
window goal-gated), and the headline phase finding — present only for a
cycle-enabled account, so a non-cycle snapshot is unchanged. A new ground
rule keeps the Coach descriptive: never contraception-grade, never a
"safe day" claim.
OpenAPI regenerated; phase-correlation + snapshot-inclusion tests added;
copy localised across all six locales.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
- Medication cycle status: re-hydrate `nextDueAt` (it arrives as an ISO string
over the wire) before the Berlin day-bucketing, so "next dose in N days" no
longer drifts by a day near midnight or off Berlin. Covered by a new
string-input test.
- Wellness rings: drive the conic sheen off a fixed white so it always lightens
(a near-black light-mode foreground under overlay was darkening the tile into
a grey band); give the ring a transform transition so it scales smoothly with
the tile lift instead of snapping; cap the green-band glow at a few breaths
instead of an infinite drop-shadow repaint; deepen the light-mode stress and
recovery end-stops for non-text contrast; track the sm/md column count to the
active-score count so two or four scores never leave an empty cell.
- Mood factor crosstab: bound the snapshot's cross-metric read to the 365-day
window and exclude soft-deleted rows, so the factor deltas the model cites
match the visible board over the same canonical row set (no recency-biased
truncation, no soft-delete skew); thread the user's source priority so the
per-day canonical pick agrees with the screen; render the delta neutrally
rather than green/red, since a higher vital is good for steps but bad for
resting heart rate and the board is observational.
- Log-intake: surface an error when a pinned slot can't resolve to an instant
instead of silently logging the dose through the unscheduled path.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Rated mood factors (work / sleep-quality / stress, scored per entry) now
participate in the cross-metric correlation surface. Until now their score
series was captured but read by zero analytics.
Two paths, both on the existing FDR-controlled engine:
- A factor x vital crosstab on the mood insights page and the mood
snapshot: for each factor the user scores, split its days low vs high by
the factor's own median, then run the same Welch test + day floors +
Benjamini-Hochberg correction the tag crosstab uses. Surfaces lines like
"sleep runs ~38 min below baseline on the days you rated work low"
(n-gated, q <= 0.10, never fabricated on thin data).
- Factor channels (FACTOR:<key>) fold into the period-narrative discovery
matrix as both lag source and lag target, so the drivers the coach and
narrative reference can cite a factor relationship.
An inverse factor (higher rating = worse day) gets the documented sign-flip
once, at the series boundary, so "up" always reads as a better day and the
low/high split and phrasing stay honest. Strings land in all six locales;
the surface carries the standing "association, not cause" caption.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Add an additive, non-breaking assessment field to GET /api/insights/derived:
{ text, source, updatedAt } | null, keyed to the requested metric id for the
five per-score ids (READINESS, SLEEP_SCORE, RECOVERY_SCORE, STRAIN_SCORE,
STRESS_SCORE). The field is null when the metric is not one of those or when
its status is not "ok". A deterministic text always fills it — composed from
the score's own contributors, so provider-less accounts and the demo are never
empty — and warmer provider prose overrides it once cached, warmed out of band
so the GET never blocks on a model round-trip. de/en, following the v1.12.12
deterministic-narrative model. The batch grid read returns assessment: null;
the detail sheets use the single-metric route.
Introduce a shared buildMetricSignal() helper: a token-lean, signal-rich
descriptor (current, own baseline, signed delta, spread, normal-swing verdict,
normal-range placement, contributors) computed server-side so the model states
the comparison instead of re-deriving it from raw buckets. Thread it into the
generic per-metric assessment snapshot and lead the base prompt from it. Add a
PROMPT_VERSION constant to the base system prompt so prompt changes are
traceable.
Regenerate docs/api/openapi.yaml.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
When no AI provider is configured (or before the first AI summary is written),
the period-in-review card stayed empty. Compose a concise, factual, strictly
non-causal summary from the same structured digest the AI prompt is built from
— ranked metric changes vs the prior period, vitals that moved outside their
typical range, and an honest count of statistical associations — and persist it
with a `deterministic` provider marker so a later AI warm replaces it in place.
The read route now warms regardless of provider; the read-never-blocks posture
is unchanged. Fills the no-key demo's retrospective too.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
MOOD is mood-entry backed, not a MeasurementType; it was filtered out of
DISCOVERY_BEHAVIOURS but not DISCOVERY_OUTCOMES, so it leaked into the
measurement.findMany type filter and threw PrismaClientValidationError,
failing the period-narrative warm job.
Add three MeasurementType values for WHOOP fields a coverage audit found
uncaptured: AVERAGE_HEART_RATE and MAX_HEART_RATE (the cycle score's
whole-day aggregates, kept distinct from spot PULSE / RESTING_HEART_RATE /
WALKING_HEART_RATE_AVERAGE) and SLEEP_DISTURBANCE_COUNT (the per-night
disturbance tally). Units: bpm / bpm / count.
Wiring mirrors the existing per-type surfaces, traced from VO2_MAX and the
v1.11.0 WHOOP-native score classes:
- canonical enum + unit + plausibility range in
src/lib/validations/measurement.ts (every ingest / analytics / rollup
path derives from measurementTypeEnum.options, so the mean-based rollup
tier picks the new types up automatically).
- Prisma enum + migration 0125 (ALTER TYPE ADD VALUE IF NOT EXISTS,
non-transactional, idempotent — same pattern as 0111).
- category overlay (cardiovascular for the HR pair, sleep for the count).
- list-view label key / Lucide icon / chart-colour.
- i18n label key in all six locales.
- chart-token allowlist + orphan-enum stripper.
- PersonalRecord direction (HR pair null — no clean goal axis, like
WALKING_HEART_RATE_AVERAGE; disturbance count MIN, like
BREATHING_DISTURBANCES).
- enum-coverage drift guard (count 60 -> 63, doctor-PDF exclusions for the
device-derived signals) + apple-health HK-counterpart exclusion (these
are WHOOP-only; HealthKit ships no first-class daily-aggregate HR
quantity nor a disturbance tally).
The types render on the measurement list + Insights chart surfaces; like the
v1.11.0 WHOOP-native scores they get no dedicated Insights sub-page (the
sub-page map stays curated) and no LOINC / FHIR mapping (not clinical-grade).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The v1.12.1 diversity block (variety lead, data-strength line, steady-run
repetition signal, FDR-screened cross-metric relations) reached only the
generic archetype cards. The seven hand-tuned headline cards — the ones users
see most — ran at temperature 0.3 with only the previous-context block, so they
stayed prone to repetitive openers and forced filler steps. Thread the same
assessmentContextBlock through the specialized get*UserPrompt builders and
raise their temperature to 0.45 to match the archetypes.
Soften the unconditional "close with one step" across the specialized sections
and the activity / body-composition / sleep archetypes to the base prompt's
conditional form — close with a step only when the finding implies one,
otherwise affirm and name one thing to watch — so a steady metric no longer
manufactures a filler step. EN/DE parity preserved; guard computeSteadyRun
against an absent graded slice.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
general-status and blood-pressure-status read the full medication-intake
history with no time floor, scanning every row for accounts with years of
data. Both only consume the trailing ~365 days (the adherence fold and the
continuity series / 7-30 day compliance gate), so add a scheduledFor floor at
now - 365d.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The reference-grounding builder (buildSystemPromptWithReferences) and its
SOURCES list shipped to no one: both live paths called the plain system prompt,
so the model was asked to cite referenceId values it was never shown — and the
parser rejects invented ids, so the citation machinery the schema and UI
footnote already support stayed dark. Wire the builder into both consumers,
passing the metric sections the snapshot actually carries (a weight-only run
never lists BP guidance). Apply the fenced-JSON parse fallback here too.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Anthropic and the local provider do not send a JSON mode, so a compliant model
still wraps its { "summary": … } reply in a code fence or prefixes a sentence,
which broke JSON.parse and surfaced the raw fenced string as the assessment.
Add a shared stripJsonFences helper (drop the fence, narrow to the first { …
last }) and apply it as a parse fallback in parseSummaryFromContent. No-op on
already-clean JSON.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The generic metric-status generator read SLEEP_DURATION row-per-stage and
fed the snapshot a single sleep STAGE (~16 min) as the current value, so the
sleep prose reported a fraction of an hour for a full night. Route the
SLEEP_DURATION status/snapshot through reconstructSleepNights — the same
per-night, source-deduped, midnight-aware time-asleep total the dashboard,
series, and targets surfaces use — so the snapshot's series, summary, and
latest value are all the night total in minutes (the registry unit and normal
range are already minutes). Gated to SLEEP_DURATION; no other metric's status
path changes.
The readiness wellness index could surface a contributor value of 0 for an
account that recorded resting heart rate / HRV / respiratory rate but had no
scorable baseline: a non-finite baseline center or today value fell through
clamp100 to a misleading 0 that reads as a real worst-case sub-score. Return
null instead so the client drops the contributor, and document the null-vs-0
contract: null means no usable signal (no baseline, no recent reading,
non-finite input); a finite value — including a genuine 0 — means the baseline
is established and the latest reading really deviates that far.
(cherry picked from commit 0422ac012765f30069a41f662c2b025197ed9a88)
Make every metric subpage identical by construction in the shared
scaffold rather than per-page bespoke.
- Target tile matches the other cards: dark `bg-card` background and the
`rounded-xl border p-4` spacing the assessment and stat-strip cards
use, instead of the old translucent `bg-card/20` panel.
- Drop the 7T/30T/90T/1J range row and its "+X% vs previous" delta from
every subpage. The chart owns its own window via its in-card range
tabs, so the chart query is unaffected. Retire the now-dead
`MetricRangeControls`, `MetricRangeDelta`, `TimeRangePills`,
`useAnalyticsRange`, the `useInsightsRangePref` persisted-range hook,
and `sentimentFromMetricDirection` along with their tests.
- Fix the spine order to intro -> chart -> target card -> assessment ->
Min/Max/Median/Mittelwert stat strip. The stat strip moves to the foot
of the spine, below the assessment. Remove the "Letzte Messung" card
and the headline primary tile from subpages; retire
`MetricLastMeasurementCard` and `MetricPrimaryTile`.
- Blood pressure gains the stat strip it was missing: two stacked
systolic / diastolic strips, since a single-series strip would drop the
diastolic half. `MetricStatStrip` takes an optional series caption.
Update the spine guard to assert the target card precedes the
assessment and that the retired range row and last-measurement card
appear on no subpage.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
(cherry picked from commit 80b2a810314b4c0951c0d68c04bffc89003005d6)
The per-metric assessment cards are tightly grounded but their form had
converged: every card opened the same way, forced a "one doable step"
even when nothing was actionable, and a metric that stayed steady for
weeks produced near-identical paragraphs. Squeeze more value from data
already computed server-side, without touching the grounding floor or any
safety contract.
- Surface FDR-surviving cross-metric correlations on the per-metric card.
The discovery engine already screens behaviour×outcome pairs with a real
Pearson + exact p-value + Benjamini-Hochberg FDR control; that
intelligence only reached the period narrative. A new read-only consumer
runs the same full-matrix discovery and filters to the pairs that
involve the current metric, then feeds the engine's own conservative,
descriptive, never-causal interpretation strings into the prompt as
grounded relations. Best-effort: a correlation hiccup can never block the
generation it only decorates.
- Streak-aware repetition. Derive a steady-run length from the graded
series (consecutive recent weeks within a band of the user's own
baseline) and tell the model when it has already reported "no material
change" N times running, so it acknowledges the continuity in one clause
and pivots to a different facet instead of restating the same level.
- Stop forcing a step; add controlled variety. The closing step is now
conditional — when nothing is genuinely actionable the model affirms and
names one thing to watch rather than manufacturing the filler that lets
platitudes back in. A deterministic per-render variety token (seeded from
user + metric + day, never Math.random / Date.now) rotates the opening
angle so consecutive cards and days don't read identically, and the
phrasing temperature lifts 0.3 → 0.45 while the facts stay pinned by the
snapshot and the forbidden-phrase guards.
- Surface the computed data strength (n + recency) into the prose prompt so
it hedges on thin data instead of guessing what "few" means, matching the
UI confidence badge.
- Add locale-matched few-shot examples (a grounded assessment + a labelled
banned-filler counter-example) to the assessment system prompt, which
most helps weaker local-provider models follow the contract.
The own-baseline grounding, computed-not-hallucinated stats, schema-
enforced output, filler-phrase ban, and correlation-as-association
discipline are all preserved and re-pinned by new guard tests.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
(cherry picked from commit c9d04cab1523e0e57a3f50c87c9f88684b01b26f)
The tag × metric crosstab summed cumulative metrics (steps, active
energy, sleep duration) per day across every source with no canonical
pick, so once two sources reported the same day — Fitbit + Apple steps,
Fitbit + WHOOP sleep — the per-day total double-counted and inflated the
with/without averages and the Welch delta the surface ranks on. Run the
metric rows through the same per-day source-priority + device-type picker
the analytics steps/sleep path uses before bucketing, keyed by the
metric's priority ladder and the user's Berlin calendar day. Same-source
per-stage rows still sum into the night total; only cross-source twins
collapse. Thread the user's source-priority blob through the read so the
pick honours the configured ladder.
The cross-metric read was a flat `take: 5000` over the 365-day window
ordered `measuredAt desc`, unioned across per-stage sleep + per-sample
pulse/HRV; a multi-source, high-frequency user blew past it and silently
dropped the oldest months, biasing the crosstab and the long-window
correlations toward recent data. Lift the cap to cover the realistic
worst case for the window and annotate a wide event when the cap is hit
so a truncated read is observable rather than silently wrong. The read
stays raw rather than moving to the DAY rollup tier because that tier
buckets on UTC midnight while these aggregates key on the user's Berlin
day, which would skew the day pairing at the boundary.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
(cherry picked from commit aa72ffba6e3bcac9f97be4adc26d689d4f352e98)
Close the launch-blocking gap where the ConsentReceipt infrastructure was
built but never enforced as a precondition: a direct API caller with a valid
token could forward a health snapshot to a server-managed external LLM with no
receipt on file. Consent was enforced client-side only.
Add a consent guard (src/lib/ai/consent-guard.ts) and call it before the first
external-provider call on the server-managed path. The gate fires only when the
resolved chain could egress via the operator's global key (admin-openai); a
user's own BYOK key (openai/anthropic), their own ChatGPT OAuth account, and
the self-hosted local provider stay ungated — that egress is the user's own act
and the settings flow is its consent. The check fails closed: a BYOK-primary
chain with an admin-openai fallback still requires a receipt, since the runner
may cascade to the operator key. The surface maps to the consent kind (coach ->
ai_coach, insights -> ai_insights_only; master ai_full satisfies either).
- Interactive routes (insights/chat, insights/generate POST) throw
ConsentRequiredError; api-handler renders a 403 with
meta.errorCode = "consent.ai.required", mirroring assistant.disabled.* so
the client can render an inline grant-consent notice.
- Off-request pipelines fail closed quietly: comprehensive generation returns a
typed skipped:no-consent outcome, and the per-metric status family
(runStatusCompletion, gating every status card + the period-narrative warm +
the off-budget Coach memory workers) surfaces the no-key fallback instead of
egressing.
Also rate-limit POST /api/fitbit/sync (the one Fitbit route without a limiter):
a 5/60s baseline plus a tighter 1/hour bucket on the expensive fullSync walk,
keyed by user id, matching the sibling Fitbit routes.
Harden the Fitbit OAuth redirect_uri: assert it is an absolute https origin (or
http on localhost), lands on /api/fitbit/callback, and stays same-origin with
NEXT_PUBLIC_APP_URL — defence-in-depth behind Google's registered-URI check so
a Host-coerced or misconfigured app URL cannot redirect the authorization code
off-origin.
(cherry picked from commit 46b5fc2cea1b6e80bee0445bfdacf5790442c67d)
Use FITBIT_ACTIVITY_PAGE_SIZE for the sleep and exercise reads instead of a
magic 25, remove the unused FitbitDataTypeKey type, and declare the crosstab
day floors independently so they aren't a duplicate re-export of the influence
floors.
Extend the mood-relations surface from mood to a health metric. For each
structured mood tag present on enough days, compare a metric's value on
tag-present vs tag-absent days: active energy on workout days (same day),
sleep length on nights tagged sleep (same day), and next-day recovery
after a tag like alcohol or food (D to D+1 lag). The comparison reuses the
existing statistics engine wholesale — the Welch two-sample t-test, the
per-group day floors, the confidence band, and the Benjamini-Hochberg FDR
control already used by the influence and discovery boards — so no new
statistics code lands. Only pairs that clear p < 0.05 and the FDR control
surface, ranked by adjusted q then absolute delta and capped at eight rows.
The result rides on GET /api/mood/insights as a new additive
`tagMetricCrosstab` field and renders as a confidence-gated, observational
card on the mood insights page, framed as an association in your own data
rather than a cause. The endpoint is server-rendered and not in the OpenAPI
contract, so no contract change is required.
Deprecate the standalone moodLog integration. Mood is now tracked fully
inside HealthLog through entries, structured tags, and rated factors, so
the external webhook and reverse-sync bridge no longer add anything. The
webhook route, the push and pull helpers, and the validation schemas carry
an @deprecated note pointing at the native path; the surface stays
functional this release and is slated for removal in a future major. The
settings card shows a deprecation hint, localised across all six locales.
- Mood discovery footer no longer pairs a mood-only numerator with the
full behaviour-by-outcome denominator. Reword it to surface the mood
relationships out of all day-to-day pairs the engine tested across
every metric, so the count it reports is honest about its scope.
Update all six locales.
- Rank the better-days board on a comparable scale: standardize the tag
mood-point delta into a Cohen's-d effect (delta over the pooled
with/without mood SD, clamped to [0,1]) so it sits alongside a metric
|r| instead of the old |delta|/2 heuristic. Fall back to |delta|/2 only
when the pooled SD is undefined. The pooled SD is ranking-only and is
stripped before the row enters the snapshot payload; the raw delta and
r the cards show are unchanged.
- Normalize the Withings and Whoop resume buttons to the min-h-11 scale
token, dropping the arbitrary min-h-[44px] spelling.
- Give the API token copy button a 44px tap target on small viewports,
scaling back to the tighter icon size from sm up.
- Drop the dead cached prop from InsightStatusCard and every caller; the
card has carried no cached affordance since the badge was removed.
Two changes that turn the descriptive relations surfaces into a
statistically-gated discovery view on the mood page.
Mood as an outcome: the FDR-controlled all-pairs correlation discovery
engine treated mood only as a behaviour (a lag source). Promote it to an
outcome channel too, so the scan also surfaces "behaviour today → next-day
mood" relations (e.g. more daylight today → better mood tomorrow) alongside
the existing "mood today → next-day outcome" direction. The self-pair is
skipped and Benjamini-Hochberg already controls the larger pair family this
opens up. The discovery route now feeds the shared mood daily-mean series
into both roles.
Surface the discovery slice: the engine was computed but never rendered.
The mood Insights page now shows the mood-involving pairs that survive the
false-discovery correction, each phrased observationally with its paired-day
count, r, and BH q-value, plus the honest "X of N tested" footer. The
surface self-fetches the correlation route and degrades to nothing when the
operator has disabled it. Observational only, with the standing disclaimer.
Two new observational surfaces on the mood Insights page, both computed in
the single mood-aggregates engine so the charts and the coach snapshot stay
in sync.
Influence on mood (per tag): for each frequent flat and structured tag,
compare the average daily mood on days the tag is present against the
counterfactual baseline of days it is absent, with the delta and a
confidence band. The band comes from a Welch two-sample t-test reusing the
exact Student-t p-value already behind the correlation cards, not a naive
approximation. Both groups must clear a five-day floor; rows rank by
absolute delta and cap per axis. Sparse tags, single-day tags,
all-same-value days, and zero-delta tags are dropped cleanly — never NaN.
Better days board: one ranked list folding the tag deltas and the
mood x health-metric correlations (sleep, steps, pulse, weight, blood
pressure) into a single effect-size-ranked, confidence-gated surface — the
headline answer to "what goes with my good days?". Near-zero and
under-sampled correlations are excluded; the list is capped and observational
only, with the standing "association, not cause" caption.
Both surfaces ride the mood-status snapshot too so the assessment prose
never contradicts the on-screen relations. New copy in all six locales.
The target reference card carried an inline "Adjust target range" link,
which read as a control buried in a read surface. Lift the action to a
gear button in the category-page header, to the left of the Coach launch
icon, so the two sit as a consistent icon cluster beside the heading.
A small page-scoped provider bridges the two: the reference card
registers its editable target (one per page, except blood glucose which
fans out to several contexts and registers each) and the header gear
opens the per-metric editor sheet the provider owns. Single-target pages
open that target directly; glucose opens the primary context, since
target editing lives only on these pages — there is no separate targets
management surface. The card itself is now a pure read surface.
The gear carries the action's existing label as its accessible name,
clears the 44 px touch-target floor on mobile, and exposes a stable
`data-slot` for end-to-end coverage.
Each Trends-row card carries a one-line caption below its mini-chart.
The first choice is the AI advisor's per-metric sentence, but on a cold
briefing — a web-only account, a pre-briefing cached payload, or the
advisor still generating — that sentence is null and every card fell
back to a static "Awaiting more data" hint, even with a full 30-day
series painted right above it.
Add a deterministic, rule-based descriptor derived from the same series
the mini-chart plots, and apply a three-tier caption precedence:
1. advisor annotation present → the AI sentence (unchanged).
2. else, a computable series → the deterministic descriptor:
direction (rising / falling / stable) plus the first-vs-last
magnitude over the window, e.g. "Rising over 30 days (+8 mmHg)",
"Falling over 30 days (−1.4 kg)", "Stable over the last 30 days".
Mood reads on a categorical 1–5 scale, so it is phrased in plain
terms ("Mood trended slightly higher over 30 days") with no raw
point delta.
3. else (genuinely < 2 points) → the real "Awaiting more data" hint.
The descriptor is observational and neutral by construction: direction
and magnitude only, with no causal, diagnostic, or medical claim and no
value judgement — a rising weight and a rising step count read the same
way here. A per-metric stability floor (the larger of an absolute and a
relative bound) keeps day-to-day noise from reading as a trend.
The descriptor logic lives in a pure, unit-tested helper. The caption
reads the same series the chart shows: mood reuses the existing
mood-analytics cache slot, and numeric metrics take a small dedicated
30-day daily-aggregate read keyed under a new query-key factory entry
that joins the measurement-write invalidation set. New descriptor copy
ships in all six locales. The pending shimmer while the advisor is in
flight is unchanged.
Load the source-priority blob once and pass it into both
readBestGranularityRollups calls. Completes the B3 fast-path threading.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Complete the source-aware rollup read path: the slim summaries slice
(rollup + live), the comprehensive aggregator (both paths, including the
dailyByType correlation feed), and the /api/measurements route (rollup
read + the live date_trunc fallback) now resolve overlapping sources to
the source-priority ladder's canonical reading per (type, day) before
aggregating. A dual-source vital (e.g. WHOOP + Apple Watch resting heart
rate) surfaces one canonical series instead of a blend or a doubled
count; cumulative metrics keep summing per canonical source.
The collapse runs in SQL where the aggregate must stay a single
round-trip (buildSourceRankCase emits a per-user ladder-rank CASE;
canonicalMeasurementsFrom restricts a live read to canonical-source rows)
and in application code (collapseRollupRowsBySource) for the row readers,
both driven by the same resolved ladders so live and rollup agree.
Also widens the enum-literal SQL whitelist to accept digits so VO2_MAX
no longer throws on the typed write-hook recompute or the rank CASE.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Add a short-horizon OLS projection over the DAY-native per-day mean
series, extending the existing trendSlope. The fit, residual standard
error and prediction interval are computed at DAY granularity only — the
rollup invariant forbids composing a slope/sd from WEEK/MONTH buckets.
The projection is gated on fit quality (R squared), in-window history and
staleness: below any floor the engine returns insufficient rather than a
weak line, so noise is never extrapolated. The prediction-interval band
widens with the horizon distance from the data centre, so the fan
visibly communicates uncertainty.
Register TRAJECTORY in the derived registry and dispatch (additive,
iOS-forward-compatible; the capabilities endpoint and drift-guard pick it
up automatically). Surface it on the weight detail page as a forecast
band beneath the chart, labelled a projection with the cited method and
a conditional, range-only headline — never a prediction or a dated
event. i18n across all six locales.
Add a calm "your week / month in review" summary to the Insights
overview, generated from the period-narrative context (deltas, personal
bands, FDR-controlled associations, coincident days).
- New insight_narratives table (migration 0113): one durable row per
(user, period, locale); generated prose AES-256-GCM at rest following
the coach-message precedent; labels-only provenance stays plaintext.
- generatePeriodNarrative feeds the context into the provider chain with
a tight, descriptive-never-causal prompt; an insufficient context
yields no narrative, a missing provider no-ops, neither fabricates.
- Nightly warm cron on week (Mon) / month (1st) boundaries, budget-gated
per user; the read-only GET enqueues a single-user warm on a cold read.
- Read route is stale-while-revalidate and never blocks on the provider;
the card renders plain text (no markdown), a single provenance
disclosure, and a fixed footprint (no CLS). i18n in all six locales.
Assemble the structured, provenance-carrying data the period narrative
narrates, without any LLM call. buildPeriodNarrativeContext reads one
bounded window covering the current and prior period of equal length and
delegates to a pure core that produces metric deltas, derived-band
transitions, FDR-surviving correlation drivers, and coincident-deviation
flags as label+number+source beats.
Reuse the rollup-backed daily series, the median ± k·MAD personal band,
and the existing Benjamini-Hochberg correlation engine, so the
descriptive-never-causal contract carries through verbatim — a driver
never enters without clearing the FDR target, and each keeps its
conservative interpretation string unchanged. Gate on data availability:
too little history returns an insufficient shape, never a fabricated
story. Pure core is unit-tested over seeded fixtures.
Add the WHOOP integration data layer (migration 0111): seven new
MeasurementType values (HRV_RMSSD, DAY_STRAIN, WORKOUT_STRAIN,
SLEEP_PERFORMANCE, SLEEP_EFFICIENCY, SLEEP_CONSISTENCY, SLEEP_NEED,
ENERGY_EXPENDITURE_KJ), a WHOOP MeasurementSource, the WhoopConnection
and WhoopOAuthState models, and the per-user encrypted BYO-key columns
on User. Day-strain takes DAY_STRAIN (not the COMPUTED STRAIN_SCORE) and
RMSSD takes HRV_RMSSD (not the SDNN HEART_RATE_VARIABILITY) so a native
value never shares a bucket with a derived proxy.
Carry the new types through the completeness walls (units, value ranges,
chart tokens, PR direction, categories, list-meta colours/icons/labels,
HealthKit-mapping exclusions) and feed the cross-source picker: recovery
ladder (WHOOP native above the COMPUTED proxy), WHOOP inserted into the
overlapping vital ladders and the workout ladder, plus skinTemperature
and respiratoryRate metric keys.
The Enright & Sherrill 1998 predicted-distance equation was established on a
40-80 reference cohort; the metric accepts adult ages 18-120, so the
prediction extrapolates outside that range. State it in the user-facing
caveat (all locales) and the norms doc so a younger or older user reads
their percent-of-predicted with that honesty.
Carry the per-day STRAIN anchor (personal vs population) from the
strain_trimp_cache row through to the STRAIN WellnessScoreValue read, and
pick the framing line by it on the score-anatomy surface: relative to your
own typical effort once anchored personally, a general reference during
cold start. The method copy was describing both regimes generically and
could not tell the user which one produced this score. Additive read field
— iOS non-breaking.
The personal-relative-anchor explanation (own recent training-day load vs a
general reference while building history) was EN-only; de/es/fr/it/pl carried
the stale v1.10.0 method+description. Port both strings to all five so the
two-mode honesty distinction is visible regardless of locale. Also correct the
stale strain-score header comment: STRAIN is not excluded from the doctor PDF —
it rides a segregated, disclaimed Wellness-summary section.
The sleep midpoint was minutes-of-day in UTC, so a non-UTC sleeper's
consistency and timing sub-scores drifted with the offset (a 03:00-local
midpoint read as a different clock time than a UTC user's). Resolve the user's
stored zone in computeSleepScore and express the midpoint against it via the
existing tz helpers; reconstructNights takes an explicit tz (UTC default) so
the pure path stays test-pinnable.
