Phase 3: two-axis scoring and routing

Scoring (news/score.py): every profile block is embedded and compared by
z-score WITHIN block, then weighted. Veto fires on absolute similarity OR a
margin over the interest signal; demotes apply a penalty instead of excluding,
because those categories sit adjacent to real interests.

Importance is deliberately NOT corroboration count -- the old system's error,
which measured the subscription list rather than the news. It combines block
similarity, corroboration, burst velocity, editorial prominence and aggregator
score, all weighted from config.

Routing (news/route.py): two lanes with separate budgets. Interest never
overrides quiet hours; importance may, within a hard nightly cap. Vetoes are
absolute on BOTH lanes -- the v0.2 bypass lane never consulted relevance, so a
blocklisted item could still fire at priority 5, and a test now asserts it
cannot. Budgets are spent strongest-first rather than first-come.

Measured on 1,318 real clusters: 2.5 notifications/day and a 14-item digest,
inside the 2-5/day target.

Three defects the real data exposed, none of which unit tests would have caught:

- velocity was computed as origins/hours with a 0.5h floor, giving every
  SINGLE-source cluster a spurious velocity of 2.0. Growth rate is undefined
  for a cluster that has not grown; it is now zero below two origins.
- deferred items (quiet hours, budget exhausted, immature) settled straight
  into the digest and bypassed its cap, producing 198 items/day. Everything
  that misses an alert lane now competes for one ranked, capped digest.
- feeds return large archives on first fetch -- 88 Strong Towns items going back
  five months, and a BBC entry titled "BBC News app" dated 2025. Those belong in
  the scoring population but must never notify, so routing now has a recency
  requirement.

Reading the output also found two profile gaps: recurring columns and link
round-ups ("Catching Our Eye News Roundup", "Astronomy Picture of the Day")
scored as top-ranked interest items. They are on-topic but publish on a
schedule, so they are demoted rather than vetoed and still reach the digest.

README.md

@@ -73,6 +73,19 @@ corpus with a specific embedding model. **Changing `[embedding].model` invalidat
 both**, because a different model puts cosine similarity on a different scale.
 Re-run the calibration in `profile/CALIBRATION.md` before trusting them.
 
+## Commands
+
+    news poll        one fetch -> embed -> cluster cycle
+    news sources     sources and item counts
+    news clusters    inspect clusters and their corroboration
+    news score       score clusters on both axes
+    news simulate    what would these thresholds actually have sent?
+
+`simulate` is the tuning surface. The old system's replay harness hardcoded its
+parameters and so could never sweep the thresholds it existed to tune.
+
 ## Status
 
-Early. `profile/` is written; the pipeline is not yet built.
+Ingest, embedding, clustering, two-axis scoring and routing are built and
+running against live feeds. Delivery (ntfy, the digest page) and the web UI are
+not yet written.

news/cli.py

@@ -68,6 +68,81 @@ def cmd_clusters(args) -> int:
     return 0
 
 
+def _score_all(con, cfg):
+    from .score import ProfileVectors, score_clusters
+    pv = ProfileVectors(con, cfg.profile(), Embedder.from_config(cfg))
+    return pv, score_clusters(con, pv, cfg.scoring, cfg.clustering)
+
+
+def cmd_score(args) -> int:
+    cfg = Config()
+    con = store.connect(cfg.db_path)
+    _, scores = _score_all(con, cfg)
+    scores.sort(key=lambda s: -max(s.interest_score, s.importance_score))
+    print(f"{'inter':>6} {'impor':>6} {'block':<24} {'flags':<14} story")
+    print("-" * 108)
+    for s in scores[: args.limit]:
+        flags = []
+        if s.veto:
+            flags.append("VETO")
+        if s.demote:
+            flags.append(f"-{s.demote_penalty:g}")
+        print(f"{s.interest_score:>6.2f} {s.importance_score:>6.2f} "
+              f"{s.interest.block[:23]:<24} {','.join(flags)[:13]:<14} {s.lead_title[:52]}")
+    return 0
+
+
+def cmd_simulate(args) -> int:
+    """What would these settings actually have sent?
+
+    The tuning surface the old system never had: its replay harness hardcoded
+    default parameters and so could never sweep the thresholds it existed to
+    tune.
+    """
+    from datetime import UTC, datetime
+
+    from .route import DIGEST, DROP, IMPORTANT, INTEREST, route
+
+    cfg = Config()
+    con = store.connect(cfg.db_path)
+    _, scores = _score_all(con, cfg)
+    routing = dict(cfg.routing)
+    if args.interest_threshold is not None:
+        routing["interest_threshold"] = args.interest_threshold
+    if args.important_threshold is not None:
+        routing["important_threshold"] = args.important_threshold
+
+    now = datetime.now(UTC)
+    decisions = route(con, scores, routing, cfg.delivery, now)
+    by_lane = {}
+    for d in decisions:
+        by_lane.setdefault(d.lane, []).append(d)
+
+    # Rate is over the notification-eligible window, not the whole archive:
+    # backfilled items inflate the span and would understate the true rate.
+    days = routing["max_age_hours"] / 24.0
+    eligible = sum(1 for s in scores
+                   if s.last_seen and (now - s.last_seen).total_seconds()
+                   <= routing["max_age_hours"] * 3600)
+    print(f"{len(scores)} clusters, {eligible} inside the "
+          f"{routing['max_age_hours']}h notification window ({days:.1f} days)")
+    print(f"thresholds: interest {routing['interest_threshold']}, "
+          f"important {routing['important_threshold']}\n")
+    for lane in (IMPORTANT, INTEREST, DIGEST, DROP):
+        n = len(by_lane.get(lane, []))
+        rate = f"{n / days:5.1f}/day" if lane != DROP else " " * 9
+        print(f"  {lane:<18} {n:>5}  {rate}")
+
+    for lane in (IMPORTANT, INTEREST):
+        items = sorted(by_lane.get(lane, []), key=lambda d: -d.score)
+        if items:
+            print(f"\n=== {lane} ===")
+            for d in items[: args.show]:
+                title = next(s.lead_title for s in scores if s.cluster_id == d.cluster_id)
+                print(f"  {d.score:>6.2f}  [{d.reason[:28]:<28}] {title[:56]}")
+    return 0
+
+
 def main(argv: list[str] | None = None) -> int:
     parser = argparse.ArgumentParser(prog="news")
     sub = parser.add_subparsers(dest="cmd", required=True)
@@ -81,6 +156,16 @@ def main(argv: list[str] | None = None) -> int:
     p.add_argument("-v", "--verbose", action="store_true")
     p.set_defaults(fn=cmd_clusters)
 
+    p = sub.add_parser("score", help="score clusters on both axes")
+    p.add_argument("--limit", type=int, default=25)
+    p.set_defaults(fn=cmd_score)
+
+    p = sub.add_parser("simulate", help="what would these thresholds have sent?")
+    p.add_argument("--interest-threshold", type=float, default=None)
+    p.add_argument("--important-threshold", type=float, default=None)
+    p.add_argument("--show", type=int, default=8)
+    p.set_defaults(fn=cmd_simulate)
+
     args = parser.parse_args(argv)
     return args.fn(args)
 

news/config.py

@@ -97,6 +97,24 @@ class Config:
             "veto_margin_over_interest": s.get("veto_margin_over_interest", 0.3),
             "corroboration_pickup_weight": s.get("corroboration_pickup_weight", 0.3),
             "corroboration_depth_weight": s.get("corroboration_depth_weight", 0.2),
+            "demote_absolute": s.get("demote_absolute", 0.55),
+            "importance_weights": s.get("importance_weights", {}),
+        }
+
+    @property
+    def routing(self) -> dict[str, Any]:
+        r = self.section("routing")
+        return {
+            "interest_per_day": r.get("interest_per_day", 3),
+            "important_per_day": r.get("important_per_day", 2),
+            "important_per_night": r.get("important_per_night", 1),
+            "interest_threshold": r.get("interest_threshold", 2.0),
+            "important_threshold": r.get("important_threshold", 2.0),
+            "digest_floor": r.get("digest_floor", 0.5),
+            "hn_min_score": r.get("hn_min_score", 150),
+            "max_age_hours": r.get("max_age_hours", 48),
+            "digest_max_items": r.get("digest_max_items", 25),
+            "serendipity_max_interest": r.get("serendipity_max_interest", 0.5),
         }
 
     # -- reader ------------------------------------------------------------

news/route.py

@@ -0,0 +1,220 @@
+"""Routing: turn scores into decisions.
+
+Two independent lanes, because "something I might like" and "something I need to
+know" are different questions:
+
+    alert:interest    high interest. Respects quiet hours, always.
+    alert:important   high importance regardless of interest. May wake the
+                      reader, with its own smaller budget and a hard nightly cap.
+    digest            everything else worth reading, collected for the morning.
+    drop              vetoed, or below the floor.
+
+Vetoes are absolute on BOTH lanes. In the old system the bypass lane never
+consulted relevance (gate.rs:302), so a blocklisted item could still fire at
+priority 5. That must not recur, and a test asserts it.
+"""
+
+from __future__ import annotations
+
+import sqlite3
+from dataclasses import dataclass
+from datetime import datetime, time, timedelta
+
+from .score import ClusterScore
+
+INTEREST = "alert:interest"
+IMPORTANT = "alert:important"
+DIGEST = "digest"
+DROP = "drop"
+
+
+@dataclass(frozen=True)
+class Decision:
+    cluster_id: str
+    lane: str
+    reason: str
+    score: float
+
+
+def _parse_hhmm(value: str) -> time:
+    hh, mm = value.split(":")
+    return time(int(hh), int(mm))
+
+
+def in_quiet_hours(now: datetime, quiet: dict) -> bool:
+    start = _parse_hhmm(quiet.get("start", "22:00"))
+    end = _parse_hhmm(quiet.get("end", "07:00"))
+    minute = now.hour * 60 + now.minute
+    s, e = start.hour * 60 + start.minute, end.hour * 60 + end.minute
+    # Quiet hours normally wrap midnight.
+    return minute >= s or minute < e if s > e else s <= minute < e
+
+
+def _sent_since(con: sqlite3.Connection, lane: str, since: datetime) -> int:
+    row = con.execute(
+        "SELECT COUNT(*) AS n FROM notification_log WHERE lane=? AND created_at>=?",
+        (lane, since.isoformat()),
+    ).fetchone()
+    return int(row["n"] or 0)
+
+
+def route(
+    con: sqlite3.Connection,
+    scores: list[ClusterScore],
+    routing: dict,
+    delivery: dict,
+    now: datetime,
+) -> list[Decision]:
+    """Decide a lane for every scored cluster.
+
+    Clusters are considered strongest-first within each lane, so a limited daily
+    budget is spent on the best candidates rather than on whatever arrived
+    first -- the ordering bug that let the old system's budget go to noise.
+    """
+    quiet = delivery.get("quiet_hours", {})
+    quiet_now = in_quiet_hours(now, quiet)
+    may_wake = bool(delivery.get("importance_may_wake", True))
+    day_ago = now - timedelta(days=1)
+
+    interest_budget = routing.get("interest_per_day", 3) - _sent_since(con, INTEREST, day_ago)
+    important_budget = routing.get("important_per_day", 2) - _sent_since(con, IMPORTANT, day_ago)
+    night_budget = routing.get("important_per_night", 1) - _sent_since(
+        con, IMPORTANT, now - timedelta(hours=10))
+
+    already = {
+        r["cluster_id"]
+        for r in con.execute(
+            "SELECT DISTINCT cluster_id FROM notification_log WHERE created_at>=?",
+            ((now - timedelta(days=3)).isoformat(),),
+        )
+    }
+
+    decisions: dict[str, Decision] = {}
+    # Deferred items are digest CANDIDATES, not digest members. Everything that
+    # misses an alert lane competes for the same capped digest, so a quiet-hours
+    # deferral cannot smuggle 190 items past the cap the way an earlier version
+    # did.
+    deferred: dict[str, str] = {}
+
+    def settle(s: ClusterScore, lane: str, reason: str, value: float) -> None:
+        decisions[s.cluster_id] = Decision(s.cluster_id, lane, reason, value)
+
+    def defer(s: ClusterScore, reason: str) -> None:
+        deferred[s.cluster_id] = reason
+
+    max_age = timedelta(hours=routing.get("max_age_hours", 48))
+    live: list[ClusterScore] = []
+    for s in scores:
+        # Staleness first. Feeds hand back large archives on first fetch -- one
+        # run pulled 88 items going back five months, plus a BBC entry literally
+        # titled "BBC News app" dated 2025. Those belong in the scoring corpus,
+        # because the z-score population should reflect what news looks like,
+        # but nothing that old may reach the reader.
+        if s.last_seen is not None and now - s.last_seen > max_age:
+            settle(s, DROP, "stale", s.interest_score)
+        elif s.veto:
+            settle(s, DROP, f"veto:{s.veto}", s.interest_score)
+        elif s.cluster_id in already:
+            settle(s, DROP, "already-notified", s.interest_score)
+        elif _immature(s, routing):
+            # Not rejected, just not ripe: the crowd has not voted yet. It is
+            # re-scored on the next cycle as its score climbs.
+            settle(s, DROP, "aggregator-immature", s.interest_score)
+        else:
+            live.append(s)
+
+    # --- importance lane first: smaller budget, higher stakes ---
+    for s in sorted(live, key=lambda x: -x.importance_score):
+        if s.cluster_id in decisions or s.cluster_id in deferred:
+            continue
+        if s.importance_score < routing.get("important_threshold", 2.0):
+            continue
+        if important_budget <= 0:
+            defer(s, "important-budget-exhausted")
+            continue
+        if quiet_now:
+            if not may_wake or night_budget <= 0:
+                defer(s, "quiet-hours")
+                continue
+            night_budget -= 1
+        important_budget -= 1
+        settle(s, IMPORTANT, f"importance:{s.importance.block}", s.importance_score)
+
+    # --- interest lane: never overrides quiet hours ---
+    for s in sorted(live, key=lambda x: -x.interest_score):
+        if s.cluster_id in decisions or s.cluster_id in deferred:
+            continue
+        if s.interest_score < routing.get("interest_threshold", 2.0):
+            continue
+        if _conflict_needs_importance(s, routing, delivery):
+            defer(s, "conflict-general-needs-importance")
+            continue
+        if quiet_now:
+            defer(s, "quiet-hours")
+            continue
+        if interest_budget <= 0:
+            defer(s, "interest-budget-exhausted")
+            continue
+        interest_budget -= 1
+        settle(s, INTEREST, f"interest:{s.interest.block}", s.interest_score)
+
+    # --- one capped, ranked digest ---
+    floor = routing.get("digest_floor", 0.0)
+    cap = routing.get("digest_max_items", 25)
+    pool = sorted(
+        (s for s in live if s.cluster_id not in decisions),
+        key=lambda x: -max(x.interest_score, x.importance_score),
+    )
+    taken = 0
+    for s in pool:
+        value = max(s.interest_score, s.importance_score)
+        reason = deferred.get(s.cluster_id, "digest")
+        if value < floor and s.cluster_id not in deferred:
+            settle(s, DROP, "below-floor", value)
+        elif taken < cap:
+            settle(s, DIGEST, reason, value)
+            taken += 1
+        else:
+            settle(s, DROP, "digest-full", value)
+
+    # Serendipity: reserve slots for items that scored well on importance but
+    # POORLY on the interest profile, so the digest does not become a mirror of
+    # the profile. A preference learner tightens its own bubble as it succeeds.
+    slots = int(delivery.get("serendipity_slots", 0))
+    if slots:
+        ceiling = routing.get("serendipity_max_interest", 0.5)
+        outside = sorted(
+            (s for s in pool
+             if decisions[s.cluster_id].lane == DROP and s.interest_score < ceiling),
+            key=lambda x: -x.importance_score,
+        )
+        for s in outside[:slots]:
+            settle(s, DIGEST, "serendipity", s.importance_score)
+
+    return [decisions[s.cluster_id] for s in scores]
+
+
+def _immature(s: ClusterScore, routing: dict) -> bool:
+    """Aggregator items wait for the crowd.
+
+    An HN post at 3 points is noise and the same post at 300 is news, so an item
+    whose only signal is an aggregator score below the bar is held for the
+    digest rather than routed on arrival.
+    """
+    threshold = routing.get("hn_min_score", 150)
+    return s.ext_score is not None and s.ext_score < threshold and s.corroboration.origins <= 1
+
+
+def _conflict_needs_importance(s: ClusterScore, routing: dict, delivery: dict) -> bool:
+    """Category-E conflict notifies only on a major development.
+
+    Connor: "my actual war interest is low, but unfortunately all wars are
+    important." Routine front-line reporting goes to the digest; a new
+    offensive, a ceasefire or mass casualties clears the importance bar and
+    reaches him through the other lane.
+    """
+    if not delivery.get("conflict_general_requires_importance", True):
+        return False
+    if s.interest.block != "conflict-general":
+        return False
+    return s.importance_score < routing.get("important_threshold", 2.0)

news/score.py

@@ -0,0 +1,247 @@
+"""Two-axis scoring: is this something I'd like, and is this something I need to know.
+
+The two questions are independent and get independent answers. Conflating them
+is what made the old system's notifications wrong: its "importance" was
+corroboration count, its relevance was three BM25 keywords, and its notification
+lane consulted neither.
+
+Blocks are compared by z-score WITHIN block, never by raw cosine. Cosine
+magnitude is not comparable across blocks -- "geopolitics" averages 0.501
+similarity against world-news text while "kentucky-louisville" averages 0.441 --
+so a plain max hands one block 78% of all items. See profile/CALIBRATION.md.
+"""
+
+from __future__ import annotations
+
+import math
+import sqlite3
+from datetime import datetime
+from dataclasses import dataclass, field
+
+import numpy as np
+
+from . import cluster as cluster_mod
+from . import store
+from .cluster import Corroboration
+from .embed import Embedder, embed_text
+from .util import content_hash
+
+
+@dataclass(frozen=True)
+class BlockHit:
+    """The best-matching block of a kind, and how far above normal it scored."""
+
+    block: str
+    z: float
+    raw: float
+
+
+@dataclass
+class ClusterScore:
+    cluster_id: str
+    lead_title: str
+    last_seen: datetime | None
+    interest: BlockHit
+    importance: BlockHit
+    corroboration: Corroboration
+    velocity: float          # distinct origins per hour since first seen
+    prominence: int          # 1 if any member came from a front-page feed
+    ext_score: int | None    # best aggregator score (HN points) in the cluster
+    veto: str | None
+    demote: str | None
+    demote_penalty: float
+    interest_score: float
+    importance_score: float
+    reasons: list[str] = field(default_factory=list)
+
+
+class ProfileVectors:
+    """Embedded probes for every block in the profile.
+
+    Probe vectors are cached in the same `embeddings` table as items, keyed by
+    content hash, so editing one probe re-embeds one probe rather than all of
+    them.
+    """
+
+    def __init__(self, con: sqlite3.Connection, profile: dict, embedder: Embedder):
+        self.blocks: dict[str, list[tuple[str, np.ndarray, dict]]] = {}
+        for kind in ("interest", "veto", "demote", "importance"):
+            entries = []
+            for block in profile.get(kind, []):
+                pairs = [(content_hash(p), p) for p in block["probes"]]
+                vecs = embedder.encode_cached(con, pairs)
+                mat = np.stack([vecs[h] for h, _ in pairs])
+                entries.append((block["id"], mat, block))
+            self.blocks[kind] = entries
+
+    def best(self, kind: str, vec: np.ndarray, weighted: bool = True) -> tuple[str, float]:
+        """Highest raw cosine across blocks of `kind`, as (block_id, cosine)."""
+        best_id, best = "", -1.0
+        for block_id, mat, block in self.blocks[kind]:
+            raw = float((mat @ vec).max())
+            if weighted:
+                raw *= block.get("weight", 1.0)
+            if raw > best:
+                best_id, best = block_id, raw
+        return best_id, best
+
+    def raw_matrix(self, kind: str, vecs: np.ndarray) -> dict[str, np.ndarray]:
+        """Per-block raw cosine for every row of `vecs`, unweighted."""
+        return {bid: (vecs @ mat.T).max(axis=1) for bid, mat, _ in self.blocks[kind]}
+
+    def weight(self, kind: str, block_id: str) -> float:
+        for bid, _, block in self.blocks[kind]:
+            if bid == block_id:
+                return float(block.get("weight", 1.0))
+        return 1.0
+
+    def block(self, kind: str, block_id: str) -> dict:
+        for bid, _, b in self.blocks[kind]:
+            if bid == block_id:
+                return b
+        return {}
+
+
+def _z(values: np.ndarray) -> np.ndarray:
+    """Z-score, safe when a block is flat across the population."""
+    std = float(values.std())
+    if std < 1e-9:
+        return np.zeros_like(values)
+    return (values - float(values.mean())) / std
+
+
+def score_clusters(
+    con: sqlite3.Connection,
+    profile_vectors: ProfileVectors,
+    scoring_cfg: dict,
+    clustering_cfg: dict,
+    since: str | None = None,
+) -> list[ClusterScore]:
+    """Score every cluster in the window.
+
+    The z-score population is the window itself, so scores are relative to
+    "what news looked like recently" rather than to an absolute cosine value
+    that means nothing on its own.
+    """
+    rows = con.execute(
+        """SELECT c.id, c.centroid, c.size, c.first_seen_at, c.last_seen_at,
+                  (SELECT title FROM items WHERE id = c.lead_item_id) AS lead
+           FROM clusters c
+           WHERE (? IS NULL OR c.last_seen_at >= ?)
+           ORDER BY c.last_seen_at DESC""",
+        (since, since),
+    ).fetchall()
+    if not rows:
+        return []
+
+    mat = np.stack([store.from_blob(r["centroid"]) for r in rows])
+    mat /= np.maximum(np.linalg.norm(mat, axis=1, keepdims=True), 1e-12)
+
+    interest_raw = profile_vectors.raw_matrix("interest", mat)
+    importance_raw = profile_vectors.raw_matrix("importance", mat)
+    veto_raw = profile_vectors.raw_matrix("veto", mat)
+    demote_raw = profile_vectors.raw_matrix("demote", mat)
+
+    interest_z = {b: _z(v) * profile_vectors.weight("interest", b) for b, v in interest_raw.items()}
+    importance_z = {
+        b: _z(v) * profile_vectors.weight("importance", b) for b, v in importance_raw.items()
+    }
+    veto_z = {b: _z(v) for b, v in veto_raw.items()}
+
+    def argbest(per_block: dict[str, np.ndarray], i: int) -> tuple[str, float]:
+        return max(((b, float(v[i])) for b, v in per_block.items()), key=lambda kv: kv[1])
+
+    out: list[ClusterScore] = []
+    for i, row in enumerate(rows):
+        i_block, i_z = argbest(interest_z, i)
+        m_block, m_z = argbest(importance_z, i)
+
+        # --- veto: absolute similarity OR a margin over the interest signal ---
+        veto_hit = None
+        best_veto_z = -9.0
+        for b, v in veto_z.items():
+            if veto_raw[b][i] >= scoring_cfg["veto_absolute"]:
+                veto_hit = b
+            if float(v[i]) > best_veto_z:
+                best_veto_z, best_veto_block = float(v[i]), b
+        if veto_hit is None and best_veto_z > i_z + scoring_cfg["veto_margin_over_interest"]:
+            veto_hit = best_veto_block
+
+        # --- demote: a penalty, not an exclusion ---
+        demote_hit, penalty = None, 0.0
+        for b, v in demote_raw.items():
+            block = profile_vectors.block("demote", b)
+            if float(v[i]) >= scoring_cfg.get("demote_absolute", 0.55):
+                p = float(block.get("penalty", 1.0))
+                if p > penalty:
+                    demote_hit, penalty = b, p
+
+        corr = cluster_mod.corroboration(
+            con, row["id"], clustering_cfg["syndication_threshold"],
+            scoring_cfg["corroboration_pickup_weight"],
+            scoring_cfg["corroboration_depth_weight"])
+
+        meta = con.execute(
+            """SELECT MAX(s.prominence) AS prom, MAX(i.ext_score) AS ext
+               FROM cluster_members cm
+               JOIN items i ON i.id = cm.item_id
+               JOIN sources s ON s.id = i.source_id
+               WHERE cm.cluster_id = ?""",
+            (row["id"],),
+        ).fetchone()
+
+        # Velocity is a GROWTH rate, so it is only defined once a story has been
+        # picked up more than once. A singleton has no growth: computing
+        # 1 origin / 0.5h floor gave every single-source cluster a spurious
+        # velocity of 2.0, which is most of the corpus.
+        if corr.origins < 2:
+            velocity = 0.0
+        else:
+            hours = max(
+                0.5,
+                (cluster_mod._parse(row["last_seen_at"])
+                 - cluster_mod._parse(row["first_seen_at"])).total_seconds() / 3600.0,
+            )
+            velocity = corr.origins / hours
+
+        out.append(
+            ClusterScore(
+                cluster_id=row["id"],
+                lead_title=row["lead"] or "",
+                last_seen=cluster_mod._parse(row["last_seen_at"]),
+                interest=BlockHit(i_block, i_z, float(interest_raw[i_block][i])),
+                importance=BlockHit(m_block, m_z, float(importance_raw[m_block][i])),
+                corroboration=corr,
+                velocity=velocity,
+                prominence=int(meta["prom"] or 0),
+                ext_score=meta["ext"],
+                veto=veto_hit,
+                demote=demote_hit,
+                demote_penalty=penalty,
+                interest_score=i_z - penalty,
+                importance_score=_importance(m_z, corr, velocity, meta, scoring_cfg),
+            )
+        )
+    return out
+
+
+def _importance(
+    block_z: float, corr: Corroboration, velocity: float, meta, cfg: dict
+) -> float:
+    """Importance is NOT corroboration count.
+
+    That was the old system's mistake: with a dozen general-news feeds all
+    reprinting the same wire, "how many sources carried it" measured the
+    subscription list rather than the news. Corroboration is one term among
+    several here, and burst velocity -- how fast independent newsrooms picked
+    it up -- carries as much weight, because 0 to 6 origins in ninety minutes is
+    what breaking news actually looks like.
+    """
+    w = cfg.get("importance_weights", {})
+    score = w.get("block", 1.0) * block_z
+    score += w.get("corroboration", 0.4) * math.log1p(max(0.0, corr.score))
+    score += w.get("velocity", 0.5) * math.log1p(max(0.0, velocity))
+    score += w.get("prominence", 0.3) * int(meta["prom"] or 0)
+    if meta["ext"]:
+        score += w.get("aggregator", 0.3) * math.log1p(float(meta["ext"]) / 100.0)
+    return score

news/store.py

@@ -80,6 +80,20 @@ CREATE TABLE IF NOT EXISTS cluster_members (
 );
 CREATE INDEX IF NOT EXISTS cluster_members_item ON cluster_members(item_id);
 
+-- The suppression and budget ledger. Every send is recorded, including dry
+-- runs, so `simulate` and the live router share one notion of "already sent".
+CREATE TABLE IF NOT EXISTS notification_log (
+  id                INTEGER PRIMARY KEY AUTOINCREMENT,
+  cluster_id        TEXT NOT NULL,
+  lane              TEXT NOT NULL,
+  score             REAL,
+  origins_at_notify INTEGER,
+  dry_run           INTEGER NOT NULL DEFAULT 0,
+  created_at        TEXT NOT NULL
+);
+CREATE INDEX IF NOT EXISTS notification_log_created ON notification_log(created_at);
+CREATE INDEX IF NOT EXISTS notification_log_cluster ON notification_log(cluster_id);
+
 -- Append-only: every click is a training event, never an update in place.
 CREATE TABLE IF NOT EXISTS feedback (
   id         INTEGER PRIMARY KEY AUTOINCREMENT,

profile/config.toml

@@ -67,3 +67,43 @@ veto_margin_over_interest = 0.3
 # their own copy. Raise pickup_weight if you add local papers running wire.
 corroboration_pickup_weight = 0.3
 corroboration_depth_weight = 0.2
+
+[routing]
+# Daily budgets. Deliberately small: the point of the system is a handful of
+# well-chosen interruptions, not a feed.
+interest_per_day = 3
+important_per_day = 2
+# Hard cap on waking the reader during quiet hours, inside important_per_day.
+important_per_night = 1
+
+# Thresholds are in z-score units -- "how many standard deviations above normal
+# for this block", not raw cosine. Calibrate with `news simulate`, which reports
+# the notifications-per-day these values would actually have produced.
+interest_threshold = 2.0
+important_threshold = 2.0
+digest_floor = 0.5
+# A floor alone yielded 198 items a day. The digest is capped by count and fed
+# strongest-first, so the cap is always spent on the best candidates.
+digest_max_items = 25
+# Serendipity slots are filled from items BELOW this interest score, so they are
+# genuinely outside the profile rather than near-misses.
+serendipity_max_interest = 0.5
+
+# Aggregator maturation: an HN post at 3 points is noise, at 300 it is news.
+hn_min_score = 150
+
+# Nothing older than this may generate a notification. Feeds return large
+# archives on first fetch -- one run pulled 88 items going back five months --
+# and those belong in the scoring corpus but not in your pocket.
+max_age_hours = 48
+
+[scoring.importance_weights]
+# Importance is NOT corroboration count -- that was the old system's error.
+# Velocity is weighted as heavily as corroboration: 0 to 6 independent origins
+# in ninety minutes is what breaking news looks like, and a story sitting at 6
+# origins for three days is not.
+block = 1.0
+corroboration = 0.4
+velocity = 0.5
+prominence = 0.3
+aggregator = 0.3

profile/profile.toml

@@ -338,6 +338,21 @@ probes = [
   "A missing person case takes a turn as investigators search a rural property.",
 ]
 
+# Recurring columns, link round-ups and daily photo features. These are often
+# genuinely on-topic -- Astronomy Picture of the Day matches space-aerospace
+# correctly -- but a feature that publishes on a schedule is not news breaking,
+# and should never be an interruption. Demoted rather than vetoed so they still
+# reach the digest.
+[[demote]]
+id = "recurring-feature"
+penalty = 1.5
+probes = [
+  "Catching Our Eye: a round-up of links and short items we noticed this week.",
+  "Astronomy Picture of the Day: today's image, with a short explanatory caption.",
+  "Your morning briefing: everything you need to know today, in five bullet points.",
+  "This week in review: the stories we covered, collected.",
+]
+
 # ============================================= the importance lane ===========
 # Independent of interest. Vetoes still apply here -- v0.2's bypass lane ignored
 # relevance entirely (gate.rs:302), which let blocklisted items fire at priority 5.

tests/test_route.py

@@ -0,0 +1,156 @@
+"""Routing decisions.
+
+The most important assertion here is that a veto blocks BOTH lanes. In the old
+system the bypass lane never consulted relevance (gate.rs:302), so a blocklisted
+item could still fire at priority 5 -- which is how a baseball recap could
+interrupt someone who had blocklisted sports.
+"""
+
+from __future__ import annotations
+
+from datetime import UTC, datetime, timedelta
+
+import pytest
+
+from news import store
+from news.cluster import Corroboration
+from news.route import DIGEST, DROP, IMPORTANT, INTEREST, in_quiet_hours, route
+from news.score import BlockHit, ClusterScore
+
+NOW = datetime(2026, 9, 8, 14, 0, tzinfo=UTC)      # daytime
+NIGHT = datetime(2026, 9, 8, 23, 30, tzinfo=UTC)   # inside 22:00-07:00
+
+ROUTING = {
+    "interest_per_day": 2, "important_per_day": 1, "important_per_night": 1,
+    "interest_threshold": 2.0, "important_threshold": 2.0, "digest_floor": 0.5,
+    "hn_min_score": 150, "max_age_hours": 48, "digest_max_items": 25,
+    "serendipity_max_interest": 0.5,
+}
+DELIVERY = {
+    "quiet_hours": {"start": "22:00", "end": "07:00"},
+    "importance_may_wake": True,
+    "conflict_general_requires_importance": True,
+    "serendipity_slots": 0,
+}
+
+
+def mk(cid, *, interest=0.0, importance=0.0, veto=None, block="urbanism",
+       imp_block="war-escalation", ext=None, origins=2, last_seen=NOW):
+    return ClusterScore(
+        cluster_id=cid, lead_title=cid, last_seen=last_seen,
+        interest=BlockHit(block, interest, 0.5),
+        importance=BlockHit(imp_block, importance, 0.5),
+        corroboration=Corroboration(origins, 0, 0, float(origins)),
+        velocity=0.0, prominence=0, ext_score=ext, veto=veto, demote=None,
+        demote_penalty=0.0, interest_score=interest, importance_score=importance)
+
+
+@pytest.fixture
+def con(tmp_path):
+    return store.connect(tmp_path / "r.db")
+
+
+def lanes(decisions):
+    return {d.cluster_id: d.lane for d in decisions}
+
+
+def test_veto_blocks_the_importance_lane_too(con):
+    """The v0.2 bug: bypass ignored relevance, so vetoed items still fired."""
+    out = route(con, [mk("v", interest=5.0, importance=9.0, veto="us-big-three-sports")],
+                ROUTING, DELIVERY, NOW)
+    assert lanes(out)["v"] == DROP
+    assert out[0].reason.startswith("veto:")
+
+
+def test_high_interest_alerts_during_the_day(con):
+    out = route(con, [mk("a", interest=3.0)], ROUTING, DELIVERY, NOW)
+    assert lanes(out)["a"] == INTEREST
+
+
+def test_interest_never_overrides_quiet_hours(con):
+    out = route(con, [mk("a", interest=9.0)], ROUTING, DELIVERY, NIGHT)
+    assert lanes(out)["a"] == DIGEST
+    assert out[0].reason == "quiet-hours"
+
+
+def test_importance_may_wake_but_only_within_the_nightly_cap(con):
+    scores = [mk("i1", importance=9.0), mk("i2", importance=8.0)]
+    out = lanes(route(con, scores, ROUTING, DELIVERY, NIGHT))
+    assert out["i1"] == IMPORTANT, "the top importance item may wake"
+    assert out["i2"] == DIGEST, "the nightly cap is 1"
+
+
+def test_importance_cannot_wake_when_disabled(con):
+    delivery = {**DELIVERY, "importance_may_wake": False}
+    out = route(con, [mk("i", importance=9.0)], ROUTING, delivery, NIGHT)
+    assert lanes(out)["i"] == DIGEST
+
+
+def test_daily_budget_is_spent_on_the_strongest_candidates(con):
+    """Budget must go to the best items, not to whichever arrived first."""
+    scores = [mk("weak", interest=2.1), mk("strong", interest=8.0), mk("mid", interest=4.0)]
+    out = lanes(route(con, scores, {**ROUTING, "interest_per_day": 1}, DELIVERY, NOW))
+    assert out["strong"] == INTEREST
+    assert out["weak"] == DIGEST and out["mid"] == DIGEST
+
+
+def test_stale_clusters_never_notify(con):
+    old = NOW - timedelta(days=5)
+    out = route(con, [mk("s", interest=9.0, last_seen=old)], ROUTING, DELIVERY, NOW)
+    assert lanes(out)["s"] == DROP
+    assert out[0].reason == "stale"
+
+
+def test_immature_aggregator_items_are_held(con):
+    """An HN post at 3 points is noise; it is re-scored as its score climbs."""
+    out = route(con, [mk("hn", interest=9.0, ext=5, origins=1)], ROUTING, DELIVERY, NOW)
+    assert lanes(out)["hn"] == DROP
+    assert out[0].reason == "aggregator-immature"
+    ripe = route(con, [mk("hn", interest=9.0, ext=400, origins=1)], ROUTING, DELIVERY, NOW)
+    assert lanes(ripe)["hn"] == INTEREST
+
+
+def test_general_conflict_needs_importance_to_interrupt(con):
+    """Connor: war interest is low, but all wars are important."""
+    routine = mk("c", interest=9.0, importance=0.1, block="conflict-general")
+    assert lanes(route(con, [routine], ROUTING, DELIVERY, NOW))["c"] == DIGEST
+    major = mk("c", interest=9.0, importance=5.0, block="conflict-general")
+    assert lanes(route(con, [major], ROUTING, DELIVERY, NOW))["c"] == IMPORTANT
+
+
+def test_digest_is_capped_by_count(con):
+    scores = [mk(f"d{i}", interest=1.0) for i in range(40)]
+    out = lanes(route(con, scores, {**ROUTING, "digest_max_items": 5}, DELIVERY, NOW))
+    assert sum(1 for v in out.values() if v == DIGEST) == 5
+
+
+def test_serendipity_fills_from_outside_the_profile(con):
+    delivery = {**DELIVERY, "serendipity_slots": 2}
+    # On-profile items must outrank the off-profile ones and fill the cap,
+    # otherwise the off-profile items make the digest on merit and the reserved
+    # slots have nothing to do. (An earlier version of this test got that
+    # backwards and failed against correct code.)
+    scores = [mk(f"on{i}", interest=1.9, importance=1.9) for i in range(30)]
+    scores += [mk("off1", interest=-1.0, importance=1.0),
+               mk("off2", interest=-2.0, importance=0.9)]
+    out = route(con, scores, {**ROUTING, "digest_max_items": 5}, delivery, NOW)
+    picked = {d.cluster_id for d in out if d.reason == "serendipity"}
+    assert picked == {"off1", "off2"}
+
+
+def test_already_notified_clusters_are_not_repeated(con):
+    con.execute(
+        "INSERT INTO notification_log (cluster_id,lane,score,created_at) VALUES (?,?,?,?)",
+        ("a", INTEREST, 5.0, NOW.isoformat()))
+    out = route(con, [mk("a", interest=9.0)], ROUTING, DELIVERY, NOW)
+    assert lanes(out)["a"] == DROP
+    assert out[0].reason == "already-notified"
+
+
+@pytest.mark.parametrize("hhmm,expected", [
+    ("23:30", True), ("02:00", True), ("06:59", True),
+    ("07:00", False), ("14:00", False), ("21:59", False), ("22:00", True)])
+def test_quiet_hours_wrap_midnight(hhmm, expected):
+    h, m = map(int, hhmm.split(":"))
+    now = datetime(2026, 9, 8, h, m, tzinfo=UTC)
+    assert in_quiet_hours(now, {"start": "22:00", "end": "07:00"}) is expected