Connect, status, places, settings, test, sync and disconnect replace their
stubs. A nightly job (03:20) and the connect backfill read the timeline,
visits and residency endpoints through safeFetch and store one row of daily
values per local day: distances, places visited, minutes away from the home
place and the sealed country with its travel-day verdict. A private instance
needs its exact origin in DAWARICH_PRIVATE_ORIGINS.
The connection joins the shared ledger and the connection health model,
watched for errors only. The day carries a movement block, the model
projection drops the travel country, the two movement channels join the
correlation matrix under the environment module, travel days become trip
suggestions, and the days travel in the environment backup section.
Two daily series that both follow the season (temperature and blood
pressure, daylight and sleep) correlated strongly with nothing between
them. In a seeded simulation of such a pair the engine surfaced a
finding in 58 % of 400-day runs and 30 % of 180-day runs, and a real
next-day effect under the season came back with the wrong sign.
Every daily pair now goes through seasonallyAdjustedPearson: a linear
trend and one annual harmonic are removed from both series (trend only
under 120 paired days), the residuals are correlated, and the p-value
uses the Pyper-Peterman effective sample size. Shrinkage and the
phrasing tier read the effective size too. BH-FDR and the effect floor
are unchanged. Pairs too short to fit the basis are not tested.
The weather channels are tested once over the mean of the day before
and the day itself against the same day's outcome (lagDays 0), which
pairs the overnight low with the night it shaped now that sleep is
keyed on the wake day. Discovered pairs carry an additive nEff, the
same-day templates are wired, and the matrix skips the weather read
when the environment module is off.
scripts/compare-correlation-findings.ts counts findings per account
before and after, read-only, for the release-candidate dry run.
runStatusCompletion and runBriefingCompletion take an optional
reasoningJob. Only a named job carries reasoning, resolved against the
operator's switch and cap and the payer; a call without one, which is
every status card, batch note, derived score and workout line, sends
exactly what it sent before. Thinking is reserved on the day's ledger
with the answer budget, and a reasoning status call falls back to a
90 s ceiling instead of 60 s.
The briefing reasons on its generation and phrasing re-roll, the weekly
and monthly narratives on their first pass; the JSON and grounding
repairs do not. An inventory test freezes which files may name a job.
Every active symptom definition enters pattern discovery as an outcome
channel SYMPTOM:<id>, labelled with its decrypted name (the data label
the interpretation already prefers over the key). The daily value is the
day's highest intensity in the person's zone; days without an occurrence
count as 0 only between the first and the last logged day. At most eight,
the active-definition cap. The SYMPTOM: prefix resolves to the illness
module in the surface map, so the family leaves the matrix with the
module, and the discovery guard lists the new fetcher.
The acute red-flag clause stated the glucose floors only in mg/dL and the
sustained-fever floor only in °C. The clause is matched against what the
person writes, so a reading of 2.9 mmol/L or 103 °F did not meet any of
its numbers. Each floor now carries both units, mg/dL and °C first, in
the English and German contracts.
Refs #1067
The narrative, the workout distance and the elevation chart converted
through the unrounded escape hatch, and the trend caption scaled its
noise floor off the raw factor. They now take the rounded helpers, so a
narrated pound or mmol/L figure reads at the grain every screen shows
it, and the caption's floors are declared canonically (the distance
floor in metres). The trends row joins the chart-feeding surfaces that
may hand a raw scale to a chart.
Refs #1067
The period narrative pinned kilograms and mg/dL on its change list, and
its personal-range lines carried no unit at all. Every delta and band
edge is now stated in the reader's units (computed canonically, converted
at the end, percent left unit-free), and each band transition carries
its unit into the prompt. The sleep channel, a per-night total in
minutes, was labelled hours and is now converted to them.
Refs #1067
The status assessments folded their recent days, weeks, months and years on
Berlin days whatever the user's zone, the mood and cycle crosstabs keyed
their metric days in Berlin, the resting-pulse proxy defaulted to Berlin
days, the briefing's opener rotated at Berlin midnight, and every
assessment prompt labelled today's date as Berlin's. They now use the
user's zone. Rollup months and years are labelled by their UTC start,
which is how they are cut; read in a zone west of UTC the label named the
month before.
"Europe/Berlin" was written out in some eighty places. DEFAULT_TIMEZONE in
lib/tz/format is now the one definition: the second copy in mood/date-key,
DISPLAY_TIMEZONE, the Berlin-only day key helpers and the per-route copies
are gone. An in-repo lint rule rejects the literal outside lib/tz and
tests; four areas another change owns are listed as pending.
The Coach correlations tool, the per-metric card and the period
narrative scanned every channel, so a switched-off module still fed
their statistics and the text a model was grounded on. The matrix's
modules option is now required, each caller resolves the record's map,
and the Coach skips the lab pass with labs off. A registry guard holds
every caller to resolving the map itself.
The mask's doc comment now states what it does to the false discovery
correction: fewer channels is a smaller family, so q-values of the
remaining pairs move and a borderline pair can cross the threshold.
Serving stored text and starting model work are separate questions. A
delegate may not start model work on somebody else's record, but reads
the owner's stored briefing, period narrative, status notes, workout
notes and Coach unread signal exactly when the owner would: those
readers now resolve the record's own capability state, not the
viewer's. Generation, warms and enqueues still ask as the viewer, so a
delegate's read of a stale narrative queues nothing. A hidden
model-written narrative is no longer overwritten by a deterministic
warm while AI is unavailable.
The sharing front door reads the digest's briefing lead again, and an
integration case pins both halves.
Refs #975
Every status note reader and writer moves to InsightStatusCache: the
generators, the unchanged-data gates, the stale-while-revalidate read,
the ingest debounce, the previous-note prompt block and the
medication-compliance card with its per-medication lines. A stall now
opens a negative-cache window next to the note instead of a stub row
that shadowed it.
Stored model text is never served while its capability is unavailable,
whatever the reason: the status readers and gates check statusText, the
period narrative hides a model-written row while periodNarrative is
unavailable (the deterministic narrative is data and always shown), and
the daily digest drops reaction lines while reactionLines is
unavailable. A read-only miss now reports why (`unavailable` with the
capability's reason) and keeps hasProvider meaning provider presence, so
a withdrawn consent no longer reads as "no provider".
runStatusCompletion takes the capability as a required argument and
re-checks it before the provider chain is resolved, so a job queued
before a switch flipped still stops at the wire. The comprehensive
briefing re-checks briefing the same way. hasUsableStatusProvider is the
one presence probe.
Refs #975
Four surfaces assembled the correlation-discovery matrix and three carried a
different channel set. The Coach `get_correlations` tool had neither the
environmental-exposure channels nor the custom-metric ones, so asking it
whether air pressure relates to your sleep met a matrix the pair had never
been in. Its own file header said the opposite - "the SAME full-matrix scan
the route runs" - and had said it since the weather channels arrived in
v1.25. The period narrative was missing those two families and the
compliance / symptom pair on top.
`src/lib/insights/discovery-matrix.ts` is now the one place a matrix is
built. v1.30.3 hoisted the fetch discipline into a shared module for exactly
this reason and left the assembly duplicated behind; this finishes it. The
route, the per-metric card, the Coach tool and the period narrative all call
`assembleDiscoveryMatrix` and get the same families. What still differs is
declared as an option with its reason at the declaration: the measurement
read mode (a read-cost choice, left per surface), the extra metric types the
narrative's delta beat needs, and the RATED mood factors.
Mood factors stay on the narrative alone. That capture kind is frozen, the
two surfaces that persist a discovered pair write its channel key into a
plaintext column, and a custom factor's key is an opaque id - so admitting
them elsewhere is a decision about what to ask, not a parity fix.
Restore the per-metric filter on the assessment card's relations. It was
written in place of the pattern-dismissal filter rather than chained with it,
so a weight card's prompt had been receiving every surviving pair in the
record while the function name, the docstring and the early-return guard all
still said one metric.
`discovery-matrix-guard.test.ts` freezes who may fetch a channel, who may
construct one, and who may scan. Each matcher asserts a non-zero match count,
so a matcher that has stopped matching fails rather than agreeing with the
allowlist.
The statistics are untouched - same Pearson, same exact p-value, same
Benjamini-Hochberg, same floors. The Coach's family is larger now, which is
the point: it is corrected over the same family the insights page is.
On a German metric page the strip printed its own summary in German and
the pattern line under it in English. The pattern line is a finished
sentence the server writes, and the route never told the server who was
reading, so it wrote English.
The route now resolves the reader's language the same way the
correlations and analytics routes do and passes it down. The language is
a required argument the whole way through — it used to be optional with
an English fallback, which is why a caller could stay silent and still
get a sentence back. The cycle page's lagged rows had the same gap and
are fixed with it.
The strip's browser cache is keyed by language too, so switching
language no longer re-uses the sentence written for the previous one.
Three defects on one card of the step sub-page, all of them a surface
answering a question that belongs to the metric.
"Your usual range is -5,595.6-13,387.6 steps", under a chart whose own
y-axis refuses to draw a negative step. Same app, same question, two
answers: the axis clamped and the sentence beneath it did not. Both now
read the same fact. `VALUE_RANGES` already declares every metric's
plausibility floor for ingest; `value-domain.ts` reads it and answers
"can this metric be negative" for the padded y-domain and for the median
+/- k.MAD band alike. The band's lower edge floors at zero for a
non-negative metric; `spread` stays the unclamped dispersion so a
deviation-in-sigma calculation is unaffected. `buildBaselineBand` now
takes the metric it is describing as a required argument, so a new caller
cannot quietly reintroduce a negative edge. Two types carried no
plausibility range at all, which let any number through ingest and read
as "unknown" on the negativity question: walking steadiness gets the same
0-100 percent band as its two gait siblings, the loud-listening event a
floor of 1 with a generous ceiling.
"13,387.6 steps" also said steps to a reader of German. Five sub-page
units are English words, not symbols - steps, flights, falls, years, and
a "count" that was a poor label in any language. They now travel as i18n
keys through a new `unitKey` on the metric-page scaffold and resolve in
all six locales. The thirteen real symbols (bpm, mmHg, %, m/s, kg/m2,
...) stay literals; translating a symbol would be the opposite mistake.
And the Min read "104.0 steps". Precision was a per-page prop defaulting
to one decimal, so every page had to remember that its metric is a count
- and the step page did not. It follows the metric now: a discrete metric
(tallies, category events, closed integer instrument scores, ordinal
levels) resolves zero decimals wherever it is rendered, and a page only
passes the prop to override that.
The causal bank lived in the narrative validator as an English and German list,
so the no-causation rule was enforced in code on one surface and for two of the
six locales it ships in. It now comes from the shared screen, which carries all
six, and the narrative also gets the dose and risk-score contracts it never
checked -- persisted prose with a dose imperative in it is as unsafe as a chat
reply with one.
Red-team cases carry their language. The German outbound case was probed as
English, which would have reported a pass the guard never earned.
Three layers. The German and English narrative prompts are frozen by content
hash, normalised for the prompt-version string that a prompt change is
required to move — any other drift fails. The four riding locales must name
their language, carry the verbatim reply-language directive from their own
safety-contract file as the last instruction, and contain no German-body
sentinel. A generator-level test drives a French run end to end and asserts
the row is keyed fr, the cache action is locale-scoped, and the system prompt
reaches the provider in English with the French directive.
Alongside it a source-level ban on the exact shape the bug took
(`=== "en" ? "en" : "de"`, `?? "de"`) across the coach and narrative
surfaces, with a self-check so a typo in the pattern cannot turn the guard
into a silent pass, and coach-memory recall cases for all four locales.
The narrative read route narrowed every non-English locale to German, so a
French, Spanish, Italian or Polish account read the German narrative row and
warmed it from the German prompt body. Carry the resolved locale through
instead: the row is keyed (user, period, locale) across the full UI locale
union, and the four locales now compose the English instruction body with
their language named and the locale's own reply-language directive appended
last. The German and English prompts are unchanged apart from the version
string.
The nightly warm keeps the user's stored locale for the same reason — it has
to write the key the read route reads — and the coach and dashboard narrative
recalls read that same key. Coach memory stays de/en: it is model-facing
context, not user-facing prose, so the four locales compose and key English
rather than German.
NARRATIVE_PROMPT_VERSION 1.13.0 -> 1.14.0.
The asc+take(20000) window-cap bug (fixed on the correlations route
alone) and the mixed-grain toDailyMeans bug (fixed on three of four
readers) both survived on the Coach get_correlations tool, the
per-metric assessment card, and the period narrative. Dense accounts
saw the cap drop the newest rows on the coach/card readers and drop
the CURRENT period on the narrative — backwards for a recent-window
and a current-vs-prior surface respectively; the narrative's own local
toDailyMeans twin also averaged sleep stage-segments and blended
per-sample step chunks with drained daily totals instead of summing.
Hoists the fetch + grain resolution into
fetchMeasurementWindowSeries/fetchMoodWindowSeries
(correlation-channel-series.ts) — desc+cap+resort, full column select
for buildMeasurementDailySeries's per-type grain — and routes the
route, the coach tool, the per-metric card, and the period narrative
through it, deleting every local copy.
The per-metric insight assessments opened on the current value and read as
a data readout, while the overview texts lead with the day's verdict and
land the warm, motivating tone. Diagnosis (campaign insights-copy audit +
verification): identical warm persona/contract fragments, but the
per-metric USER prompt instructed number-first while the overview
instructed verdict-first, and the opener-hint rotation was wired into
briefing/scores/Coach but never the per-metric path (so the base prompt's
'do not open with the number' clause stayed dormant there).
Rewrote the seven per-metric assessment user prompts (generic archetype +
six bespoke: BP/weight/pulse/BMI/mood/compliance + overall) verdict-first
in EN+DE — meaning first, the number right after as support; grounding,
non-diagnostic framing, no-vendor and no-markdown all preserved (only
clause order changed). Wired openerArchetypeHint into metric-status and
the bespoke generators. Factored a shared openingShape contract into
shared-contracts so overview/per-metric/scores can't drift again, with a
coverage test. Lifted the three deterministic first-paint fallbacks to
verdict-led. Prompt-contract regression tests added. No new model calls,
token budget flat.
Replace the fixed three-beat assessment skeleton with a menu of moves the
model orders freely, and reframe the daily briefing from per-signal
enumeration to a verdict-first read that weaves the few salient signals into
one associative story. Score cards now name both the helped and the hurt
contributors, translate the band into a forward read for the day, and close
on one grounded nudge; the deterministic fallback gains the same band-meaning
sentence so provider-less and demo accounts read as well.
Add a hash-seeded opener-archetype rotation (deterministic, testable) so
consecutive cards and days no longer open the same way, a day-rotated sampling
seed for the period narrative in place of the fixed reference seed, and a
shared paragraph formatting contract. Add a score-number grounding gate and
extend the briefing grounding allow-set to the glucose, labs, preventive-care
and workout aggregate blocks so real figures can be cited without opening the
gate. Gate the daily score warm on an input fingerprint so a quiet day skips
the model call.
Render daily medication-compliance rate and illness symptom-severity as
first-class series in the FDR discovery engine, so the adherence-dip →
symptom-flare link (and compliance → vital drift) can finally surface.
Compliance pools every active medication's dose-history ledger into a per-day
taken/(taken+missed) rate, re-keyed to the user's display timezone. Symptom
severity reads the illness day-log functional impact, zero-filling healthy days
only across real episode spans so a user with no episodes yields an empty
series rather than a constant. Both flow through the existing n >= 20, BH-FDR,
effect-size, and shrinkage gates unchanged; a sparse series degrades to absent.
Each channel forms its own metric family (no self-lag tautology) and keeps the
association-not-causation framing. Add discoveryMeasurementTypes() so every
caller drops the non-measurement channels before a Prisma type filter.
The retrospective narrative was the one model surface that omitted the
shared tone contract, so it read colder than the daily briefing beside it.
Compose the tone fragment into both prompts and warm the hand-written tone
line to name a genuine win when the period earns it, while keeping the
descriptive-never-causal and no-alarm guards intact. The cross-surface
coverage test now asserts the contract reaches this surface too.
The shared contracts cover chronic deferral (dose, diagnosis, drug-level
to a clinician) but had no acute branch. Add a closed-list crisis clause —
chest pain, syncope, sudden severe symptoms, hypertensive-crisis readings,
suicidal ideation — that points to prompt or emergency care without
diagnosing, and keep every other turn calm and non-alarmist. It rides the
single shared-contract source so it lands on the Coach, the per-metric
status cards, the comprehensive briefing, and the period narrative; the
coverage test asserts it on all four surfaces.
The period narrative was written straight to storage with no
post-generation check and no corrective retry, unlike Comprehensive
Insights. A populated context could still yield causal phrasing or a
number absent from the context block.
Add a validator that flags causal language (EN/DE) and any number not in
the structured context; on a trip, retry once with a corrective suffix,
then write nothing (the last good row stays) rather than persist an
ungrounded or causal story.
One-shot prettier pass so the new format:check gate starts from a clean
baseline. Formatting only — no behaviour change. Generator-owned and
vendored artifacts stay untouched via .prettierignore.
The grounding, tone/banned-opener, GLP-1 dose-safety, metric-identifier
ban and forbidden-filler rules were independently encoded across the
comprehensive, status, Coach and narrative prompts and had drifted. Move
the canonical wording into `prompts/shared-contracts.ts` (locale-keyed
fragments) and compose each surface from it.
Where the surfaces had drifted, adopt the stricter wording: most notably
the GLP-1 dose-prescription contract — previously present only in the
comprehensive and Coach prompts — now reaches the status cards and the
period narrative too. A cross-surface coverage test asserts every
enforced fragment appears verbatim in every surface, in de and en.
Add an opt-in `responseFormat: "json"` to CompletionParams that the
structured surfaces (comprehensive briefing + per-metric status cards)
set. On local (Ollama / OpenAI-compatible) it adds `format: "json"`; on
Anthropic it prefills the assistant turn with `{` and re-prepends the
brace to the reply, so the first emitted token is already inside a JSON
object. Both cut the first-pass JSON-failure rate that fence-stripping
otherwise has to absorb.
OpenAI already pins `response_format: json_object` and is unchanged. The
period narrative (plain text) and the Coach (streaming prose) leave the
flag unset, so their non-JSON paths are untouched.
Add an optional `seed` to CompletionParams and thread it onto the
OpenAI and local (Ollama / OpenAI-compatible) request bodies. The field
is dropped when unset, so existing callers are byte-identical.
Pin a stable seed for the status/reference cards (defaulted in the
status provider) and the period narrative, so a prompt change is
diff-able against a fixed baseline rather than masked by low-temperature
non-determinism. Anthropic's Messages API has no seed knob, so its
client ignores the field (documented inline). The seed is annotated on
the narrative wide-event.
Replace the scattered `?? 0.3` / `?? 1000` temperature and maxTokens
magic numbers across the status provider, Coach route, comprehensive
generator and period-narrative generator with a single typed
`ai-budgets.ts` map. Each entry documents the output contract that
fixes its token ceiling.
Right-size the per-metric status output from 1000 to 250 tokens: the
card renders one `{ "summary": "..." }` of 2-4 sentences (30-60 words),
so 1000 was an order of magnitude over the real ceiling.
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.
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>
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.
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)
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.
Marc-André Bombeck