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Update backlog statuses; strengthen over-clustering issue with new evidence 
Mark each item open/mitigated/done, fold completed work into Shipped, and
upgrade the clustering bug with the on-device Jackson/airport over-merge proof
and a concrete TF-IDF/embeddings fix.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-19 17:07:39 +03:00

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Backlog & status

Source-of-truth tracker. The Gitea issue tracker is currently empty (0 issues) — run scripts/create-issues.sh with a token to populate it. [client] = iOS, [backend] = the platform service on the Docker host, [ci] = build/test.

Status: 🔴 open · 🟡 mitigated client-side (real fix still pending) · 🟢 done.

Backend — data quality (highest priority)

  1. 🟡 [backend] F1 mis-classified into tech/finance/politics. No sport category, so F1 (100% F1 sources) scatters across topics: "Monaco Grand Prix…" → tech, "F1 reports 35% CO2…" → finance, "McLaren launch appeal…" → politics. Add a sport/f1 topic and route motorsport sources there. Client mitigation shipped: F1 pill matches clear F1 headlines + a majority of F1 sources, and F1 is excluded from All/Tech/Finance. Backend still mis-tags.
  2. 🔴 [backend] Catastrophic over-clustering — unrelated articles merged on a single shared word. Newly confirmed on-device: a story merged a Russian-film-director article + "Who's afraid of Michael Jackson?" + "Chelsea Jackson Roberts" (wellness) — grouped on the surname Jackson. Another merged "Gunfire at Niger airport" + "L.A. County Whiteman Airport crash" + "Niger fintech". Result: wrong headline, summary, topic, and inflated signal. Raise the TF-IDF threshold hard (~0.22 → 0.45–0.55) and require multiple shared distinctive terms / named-entity overlap, with a tight time window. If still over-merging, move to sentence embeddings (all-MiniLM-L6-v2, cosine ≥ ~0.6). Make canonical headline + summary come from the same representative article. No client fix is possible — the story object itself is wrong.
  3. 🔴 [backend] Add accurate per-story tags (topic + region). So the client can read tags (sport, uganda, south-africa, …) instead of keyword-guessing. Unblocks #6.
  4. 🔴 [backend] Topic-classifier coverage for the 47 feeds. science/world/tech mapping.

Backend — features

  1. 🔴 [backend] Server-side push for breaking alerts (APNs or ntfy). For breaking-story notifications while the app is closed. Client does local notifications + background refresh only.

Client

  1. 🔴 [client] Move interest filters server-side once tags (#3) exist. Today's pills are client-side keyword/headline matches on loaded stories. Refined since: regions match headline-only (no polluted summaries/outlets), regions exclusive, F1 by source majority, East Africa removed.
  2. 🔴 [client] SSID-based trusted networks. Needs Access WiFi Information entitlement (device + paid account). Approximated by LAN reachability today.
  3. 🔴 [client] Optional in-app WireGuard tunnel. NetworkExtension; entitlement + device. Deferred.
  4. 🔴 [client] App icon + launch assets. AppIcon is an empty placeholder.
  5. 🔴 [client] Flesh out Latest / Search tabs. Saved is now bookmarks; Latest/Search still minimal.
  6. 🔴 [client] Verify hero image loading. AsyncImage vs real feed imageUrls.
  7. 🔴 [client] Offline-first polish. Pre-cache top stories.

CI

  1. 🔴 [ci] Add unit/UI tests + a test matrix leg. Build matrix compiles, runs no tests.
  2. 🔴 [ci] Backend CI build matrix. Python 3.11–3.13 + lint + Docker build/health probe.

🟢 Shipped

Signal feed + detail + reader + feed manager · LAN⇄Tailscale connectivity · notifications (morning/evening briefings + breaking alerts) with Open-Meteo weather · device code signing · feed resilience (no blank-on-refresh, ignore cancelled, coalesced WS refresh) · clearer empty states (polling / unreachable+host / offline / caught-up) · deterministic feed order · 6-line summary preview · pinned filters (F1 split out, regions exclusive & headline-matched, Finance/Tech by topic) · swipe actions (short→Save / long→Mark read, right→Share) · read/seen handling (seen-tracking with per-load snapshot, read stories collapse into a "Read" shelf with compact rows, "all caught up" state).