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.
Maintainer-voice sweep across `src/`. ~190 references to the
maintainer by first name in code comments and JSDoc neutralised to
"the maintainer", "the live tenant", "users", or "the user" depending
on context. Three sed passes covering ~50 distinct patterns
(`Marc reported`, `Marc wants`, `Marc kept`, `Marc rolled back`, etc.).
Test fixtures (`displayName: "Marc B."`, `username: "marc"`,
`<HeroStrip userName="Marc">`) kept as opaque test data per the brief.
CHANGELOG normalisation. The v1.4.14 + v1.4.15 entries paired a
German bullet with its English translation by historical design — the
in-app copy is English-default and the user docs are English, so the
mixed-language style was a holdover from the early-marathon notes.
A one-off node script extracted the `_..._` English paragraph from
each bilingual bullet and rewrote the entry as that text. ~44 bullets
reduced; one Docs bullet that lost a leading word in the regex
fixed by hand.
CLAUDE.md → CONTRIBUTING-AI.md rename so the filename is no longer
AI-vendor-specific. `CONTRIBUTING.md` reference updated. `AGENTS.md`
stays in place for multi-agent compatibility (the conventions doc is
shared with Codex / Cursor / etc.).
Wave-4 state wrap. STATE.md now records C1–C5 + D + D2 as complete;
v1421-backlog.md grew a "Closed in v1.4.22" header listing the 20
items the marathon landed; `.planning/phase-W4-report.md` documents
the per-commit decisions, test deltas, and the 23 items deferred to
v1.4.23 with reasoning.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Each recommendation now carries an optional `confidence: 0..100`
integer in `aiRecommendationSchema`. New `src/lib/ai/confidence.ts`
exposes `computeConfidence({ n, recencyDays, deviationStdRatio })`,
the deterministic formula the wrapper will use to override whatever
number the model picks.
Score breakdown (sum, max 100):
- n contribution: log10-saturating curve, capped at 40. n<3 hard-
caps the whole score at 5*n (max 15) so a three-sample window
never produces a confident-looking meter.
- recency contribution: 30 at <2d, decays linearly to 0 at 30d.
- signal contribution: 30 at |z|>=1.5, scaled linearly to 0 at
z=0; null ratio (no baseline yet) returns a neutral 15.
Schema is `.optional()` so:
- The wrapper can fill it post-validation regardless of what the
LLM emitted — the model's calibrated probability is unreliable.
- Legacy cached payloads from before B5d landed still parse.
Integer-only and bounded so the meter component renders without
clamping; a renegade provider that emits 101 or 67.5 fails parse and
triggers the wrapper's corrective retry.
15 fixtures cover the input matrix: n hard-cap (n=0..2), n=3 floor,
mid-range (n=14, n=20), saturation (n=100 plateau, n=10000 cap),
recency clamp (45d -> 0), null-ratio neutral, negative-z magnitude,
plus monotonicity-in-n + integer-in-bounds invariants.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Marc-André Bombeck