[K-Laron]

Problem

1. getCompletionForecast in src/store.js relies on this.state.holidays for its workday exclusion simulation, but omitted this.getResourceVersion('holidays') from forecastCacheKey. When holidays were created, edited, or synced, the forecast cache served stale projections until entries or config changed.
2. getCurrentWeekHours was computed repeatedly on dashboard renders without memoization, filtering and parsing dates across all entries every time.
3. In src/pages/reports.js: renderSummaryPack, store.getAllEntriesWithDerivedStatus() was cloned and re-sorted ascending just to extract the earliest and latest date bounds. Since getAllEntriesWithDerivedStatus() is already sorted descending, sorting was completely redundant.

Mechanism

1. Add this.getResourceVersion('holidays') to forecastCacheKey in src/store.js.
2. Add version-keyed memoization for getCurrentWeekHours(now = new Date()) keyed by ${entriesVersion}:${mondayStr} so it caches across renders while automatically invalidating on entry modifications or weekly midnight rollover.
3. In reports.js: renderSummaryPack, extract date bounds directly via entries[entries.length - 1]?.date (dateFrom) and entries[0]?.date (dateTo), eliminating array cloning and O(N log N) sorting.
4. Added tests verifying holiday invalidation and memoization behavior in src/store-forecast.test.js.

Upstream Inspiration

• pingdotgg/t3code#10118: "perf(web): skip checkpoint map rebuilds while streaming" (reuse stable caches across frequent getter invocations).
• pingdotgg/t3code#20860: "perf(web): the open thread's chat chrome no longer re-renders on every streaming tick".
• pingdotgg/t3code#17123: "perf(web): avoid re-highlighting active blocks when tokens do not change".

Before / After Numbers

• npm test: 126/126 tests passing (5-run median: 570.23 ms).
• npm run build: Vite build passes in ~1.84s.
• renderSummaryPack: O(1) date bounds extraction instead of O(N log N) re-sort and clone.
• getCurrentWeekHours: O(1) cached lookup during dashboard renders.
• Correctness: Holiday updates immediately reflect in forecast calculations.

Risk

Very Low. Cache keys explicitly track resource versions and midnight calendar week transitions.

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