Implement Summary Period Repository
epic-periodic-summaries-core-logic-task-001 — Build the data access layer for summary periods, including CRUD operations for period metadata, period boundary calculations storage, and idempotency key management to prevent duplicate summary generation runs.
Acceptance Criteria
Technical Requirements
Implementation Notes
Use Supabase's upsert with onConflict: 'idempotency_key' and ignoreDuplicates: false so the existing row is returned on conflict — this avoids a read-before-write race condition. Model SummaryPeriodStatus as a Dart enum with a fromString factory to guard against unexpected database values. Define the SummaryPeriod data class as immutable (final fields, copyWith) and derive equality with == and hashCode for use in Riverpod state. Register the repository with a riverpod Provider
The Supabase table should include columns: id (uuid pk), organisation_id (uuid fk), period_type (text), start_date (timestamptz), end_date (timestamptz), status (text), idempotency_key (text unique), created_at, updated_at. This repository underpins the gamification 'Spotify Wrapped' style summaries discussed in the workshop.
Testing Requirements
Integration tests against a Supabase local instance (supabase start) covering: successful create, idempotent create returning existing record, getPeriod for existing and missing ID, listPeriods with organisation filter, updatePeriod status transition, and RLS rejection when accessing another organisation's periods. Unit tests for the repository class using a mock Supabase client (implement the SupabaseClient interface or use a hand-written fake) covering error mapping to typed exceptions.
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.