Implement Summary Cache Repository
epic-periodic-summaries-core-logic-task-002 — Create the caching layer for generated summaries, supporting storage and retrieval of pre-computed summary data with cache invalidation strategies, TTL management, and organisation-scoped cache keys.
Acceptance Criteria
Technical Requirements
Implementation Notes
Implement cache storage in a Supabase table: id (uuid pk), cache_key (text), organisation_id (uuid fk), period_id (uuid fk nullable), payload (jsonb), expires_at (timestamptz), created_at. Use a composite unique index on (cache_key, organisation_id) and perform upsert with onConflict on this pair so re-generating a summary updates the cache atomically. For TTL, calculate expires_at = DateTime.now().toUtc().add(ttl) in Dart and pass as an ISO-8601 string to Supabase. Run a Supabase pg_cron job (or application-level scheduled task) to periodically purge expired rows — do not rely solely on query-time filtering to keep the table size bounded.
Register as a Riverpod Provider with SupabaseClient as a dependency. The caching layer is critical for the gamification 'Wrapped' summaries — these may be expensive to compute and must be served instantly from cache when a peer mentor opens their summary screen.
Testing Requirements
Integration tests against Supabase local instance covering: cache set and immediate retrieval (hit), retrieval after TTL expiry (miss), invalidate single entry, invalidateOrganisationCache removing all entries for an org, cross-organisation isolation (org A cannot read org B cache), and setCachedSummary overwrite behaviour (upsert on conflict). Unit tests for key format generation and TTL calculation logic using fake DateTime values.
Supabase pg_cron or Edge Function retries could trigger multiple concurrent generation runs for the same period and organisation, producing duplicate summaries and sending multiple push notifications to users — a serious UX regression.
Mitigation & Contingency
Mitigation: Implement a database-level run-lock using an INSERT … ON CONFLICT DO NOTHING pattern keyed on (organisation_id, period_type, period_start). Only the first successful insert proceeds; subsequent attempts read the existing lock and exit early. Test with concurrent invocations in a Deno test suite.
Contingency: If duplicate summaries are detected post-deployment, add a deduplication cleanup job that removes all but the most recent summary per (user_id, period_type, period_start) and sends a corrective push notification.
FCM and APNs have different payload structures and size limits. An oversized or malformed payload could cause silent notification drops on iOS or delivery failures on Android, meaning mentors never learn their summary is ready.
Mitigation & Contingency
Mitigation: Build the PushNotificationDispatcher with separate FCM and APNs payload constructors, enforce a 256-byte body limit on the preview text, and run integration tests against the Firebase Emulator and a test APNs sandbox.
Contingency: Fall back to a generic 'Your periodic summary is ready' message if personalised preview text construction fails, ensuring delivery even when the personalisation pipeline encounters an error.
Outlier thresholds that are too tight will flag most mentors as outliers (alert fatigue for coordinators), while thresholds that are too loose will miss genuinely underactive mentors — directly undermining HLF's follow-up goal.
Mitigation & Contingency
Mitigation: Implement thresholds as configurable per-organisation database settings rather than hardcoded constants. Provide sensible defaults (underactive < 2 sessions/period, overloaded > 20 sessions/period) and document the tuning process for coordinators in the admin portal.
Contingency: If coordinators report threshold miscalibration after launch, expose a threshold configuration UI in the coordinator admin screen and allow real-time threshold adjustment without requiring a code deployment.
The app may not have 12 months of historical activity data for all organisations at launch, making year-over-year comparison impossible for most users and rendering the comparison widget empty, which could disappoint users expecting Wrapped-style insights.
Mitigation & Contingency
Mitigation: Design the generation service to gracefully handle missing prior-year data by setting the yoy_delta field to null rather than zero. The UI must treat null as 'no comparison available' with appropriate placeholder copy rather than showing a misleading 0% delta.
Contingency: If historical data import from legacy Excel/Word sources becomes feasible, add a one-time backfill Edge Function that populates prior-year activity records from imported spreadsheets. Until then, explicitly communicate the data-availability limitation in the first summary each user receives.