04 — Memory Wins Digest (Weekly)

Author: CC (Block B design pass) Date: 2026-05-01 Status: AWAITING_RATIFICATION Estimate: ~250 LOC + ~4-5h wall-clock Touches: apps/web (1 component + 1 tab in Memory app), packages/server (1 cron job + 1 route), packages/core (1 generator)

User story

Once a week (Monday morning by default), I want a summary card showing how Waggle's memory paid off the prior week — N facts saved, N agent recalls that used them, estimated minutes saved on context-explaining — so I can quantify the value and feel the compounding effect.

Acceptance criteria

Weekly digest fires once per week (configurable day/hour, default Monday 09:00 local).
Delivered as a Memory app tab card + an in-app banner on first desktop mount of the week.
Card content (3 metrics + 1 narrative line):
- Frames saved this week: N
- Recalls that hit a saved frame: M
- Estimated time saved (M × 9min context-restore baseline): ~T minutes
- Narrative: "Your top theme this week: . Top decision: "
Card persists in Memory app's "Wins" tab indefinitely — historical record of weekly progress, not just one-time.
First-week edge case: if user has < 7 days of history, banner suppressed but Wins tab shows "Come back next week for your first digest" placeholder.

UI sketch

Memory App > Wins tab:
  ┌─ Week of April 24-30 ──────────────────────────────────────┐
  │ ▲ 12 frames saved   ▲ 5 agent recalls   ⏱ ~45 min saved    │
  │                                                            │
  │ Top theme: API rate limiting + auth-rewrite                │
  │ Top decision: Ship migrations Wednesday                    │
  │                                                            │
  │ [Open Memory] [Open Last Decision Source]                  │
  └────────────────────────────────────────────────────────────┘

  ┌─ Week of April 17-23 ──────────────────────────────────────┐
  │ ▲ 8 frames · ▲ 3 recalls · ⏱ ~27 min saved                 │
  │ Top theme: Onboarding wizard polish                        │
  └────────────────────────────────────────────────────────────┘

  (older weeks collapsed by default, click to expand)

Banner on Monday morning:
  [Trophy icon] This week saved you ~45 min — see the breakdown
                                              [Open Wins] [✕]

Data model

New table weekly_wins:

id INTEGER PRIMARY KEY,
week_start TEXT NOT NULL UNIQUE,    -- 'YYYY-MM-DD' (Monday)
frame_count INTEGER NOT NULL,
recall_count INTEGER NOT NULL,
estimated_minutes_saved INTEGER NOT NULL,
top_theme TEXT,
top_decision TEXT,
top_decision_source_session_id TEXT,
generated_at TEXT NOT NULL,
delivered_at TEXT                   -- nullable until banner shown

For recall_count, need to instrument frame retrieval:

Existing HybridSearch.search() already returns frame IDs
Add RecallEvent log: every search/retrieval that hits a frame logs { frame_id, ts, source: 'agent' | 'manual' } to a recall_events table
Aggregate weekly count per (week, agent-source-only)

Server-side generator

Cron runs Monday 00:30 local (off-peak):

Query frames where created_at >= weekStart AND created_at < weekStart+7d
Query recall_events where source='agent' AND ts in [weekStart, weekStart+7d]
Compute estimated_minutes_saved = recall_count × 9 (calibrated baseline; configurable)
Theme extraction: LLM call ("From these N frames, what's the dominant theme in 5-10 words?")
Top decision: highest-importance critical/important frame matching decision pattern from the week
Insert row, set delivered_at=null, await client poll

Estimated minutes baseline (the "9 min context-restore"): documented derivation needed; placeholder until UX research lands.

Implementation notes

Recall instrumentation is the hardest part — needs hook in HybridSearch.search() callsite to log frame IDs returned and identifier of the consumer (agent loop vs manual UI search).
Weekly cron: trivial extension of cron infrastructure; runs generateWeeklyWins(weekStart) on schedule.
Wins tab in Memory app: paginate if N > 12 weeks.
Edge: time zones again — week boundary is server-local Monday 00:00. Document.

Estimate

Recall events table + instrumentation: ~70 LOC (touches HybridSearch + agent-loop)
Generator + cron: ~80 LOC
Server route /api/weekly-wins: ~30 LOC
WinsCard + WinsTab components: ~80 LOC
Banner + ack route: ~30 LOC
Tests: ~50 LOC
Total ~340 LOC, ~4-5h with verification.

Risks + open questions

Recall instrumentation is the cost driver — need to wire HybridSearch to log every retrieval. Hot path; throttle/buffer logs to avoid SQLite write storms.
Estimated-minutes-saved calibration — 9 min baseline is a guess. Run a small UX study or pilot a percentile estimate. v1: hardcode + flag for revision.
First week — user installs Monday afternoon, what do they see Tuesday? Nothing — wait for next Monday. Banner suppressed for ~7 days.
Theme/decision LLM cost — 1 call/week × ~700 tokens ≈ $0.01/user/week. Negligible.
Privacy — frames may contain sensitive content; theme summary on personal mind only, not Team/shared workspaces. Hard rule: no cross-workspace digests.
What counts as a "recall" — open question. Agent retrieval via recall_memory MCP tool? Hybrid search hits during chat? UI-driven Memory app search? Default: instrument all three; aggregate by source.

Out of scope (v1)

Comparison to prior week ("up 30% from last week") — wait until 4+ weeks of data.
Per-workspace digests — global personal-mind digest only v1.
Email digest delivery — in-app only.
"Share to team" affordance.
Streak integration ("you've maintained a 4-week digest streak"). (Streak feature is separate; wait until both exist.)

PM decisions needed

GO / MODIFY / SKIP
Default delivery day/hour (Monday 09:00 reasonable? Friday end-of-week instead?)
Recall sources to count (agent only / agent+UI / all)
Estimated-minutes baseline (9 min default, or skip the metric until calibrated?)
Banner vs. tab-only delivery (can banner be opt-out?)
Theme extraction model (Sonnet / Haiku)

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