fix(insights): correct signals-of-day extraction and determinism

Drop steps from the signals-of-day set: Apple Health steps ingest as
many intraday stats-prefixed samples, so the newest raw row is a
partial-day fragment, not a daily total — same exclusion already applied
to per-night sleep. Add a glucose signal off the canonical stored value
(the model reads the snapshot, not display units) so the block matches
the priority comment that already claimed it; drop the dead sleep entry
from SIGNAL_PRIORITY. Track the raw extreme magnitude when keeping the
most extreme recent anomaly so a larger anomaly is no longer dropped by
comparing against an already-rounded value. Thread the injected clock
through trendSlope so the emerging-trend cutoff is deterministic under a
test clock. Rename the anomaly day-count to anomalyDaysAgo so the
snapshot hash staleness-tiers it instead of letting the raw count drive
the fingerprint. Cap the returned set at three to match the schema.

src/lib/analytics/trends.ts

@@ -29,11 +29,12 @@ export interface TrendSlope {
 export function trendSlope(
   data: DataPoint[],
   windowDays: number,
+  now: number = Date.now(),
 ): TrendSlope | null {
   if (data.length < 2) return null;
 
   const sorted = [...data].sort((a, b) => a.date.getTime() - b.date.getTime());
-  const cutoff = Date.now() - windowDays * 24 * 60 * 60 * 1000;
+  const cutoff = now - windowDays * 24 * 60 * 60 * 1000;
   const window = sorted.filter((p) => p.date.getTime() >= cutoff);
 
   if (window.length < 2) return null;