Weight and BMI move on a weekly cadence, but the per-metric generators
rebuilt the full snapshot (bounded findMany + per-series rollup reads +
correlation math) every day and relied on the post-build content-hash gate
to skip only the model call. Add an input gate that runs first: a single
grouped probe over the salient inputs (per-type count + newest reading, plus
mood for weight and the profile height for BMI) fingerprints what the
snapshot would read. On a non-forced run whose fingerprint matches the cached
row, the cached assessment is re-stamped under today's key and the whole
build is skipped. A miss falls through to the normal build and the existing
post-build gate.
Consent is checked before any re-date so a revoked-consent user never has
stale text presented as current. Forced runs never gate but still record a
fresh fingerprint for the next day.
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.
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.
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>
Read the MONTH / YEAR rollup tier for the monthly / yearly slices of the
focused single-metric status snapshots (weight, pulse, bmi,
blood-pressure) via `buildGradedSeriesWithRollups`, so the coarse tiers
finally earn their write amplification. BMI has no tier of its own, so it
scales the WEIGHT tier by 1 / heightCm² (`scaleGradedSeries`) — an exact
linear transform. The multi-metric general overview and the tier-less
mood / adherence series keep their bounded in-memory fold.
Fix the coverage-miss path that returned an always-empty monthly / yearly
slice: the bounded ~90-day recent read can never supply those slices, so
on a cold-tier miss the builder now folds the full history in memory
rather than shipping empty coarse arrays when years of raw history exist.
Excludes tombstoned rows from both reads.
Lift the byte-identical `round`, `normalizeSummaryText`,
`normalizeLocale`, `summarizeSeries`, the `{summary}`-envelope parse, and
the cache-row persist block out of the seven generators into
`status-shared.ts`. Drop the per-medication expectation in the compliance
generator: the prompt returns only `{summary}`, so the per-med cards are
server-side placeholders rather than a dead model-authored branch. Remove
the unused `summarizeGradedSeries` export.
Behaviour is unchanged on the in-memory path; the rollup path is exact
where the tier composes (count / min / max / mean) and the payload stays
under the snapshot char cap.