feat(telemetry): record WHAT the bar turned away, not only how close it came (#3807)

#3670 added `best_available_score` so a threshold could be judged from its
rejections. It records how CLOSE the bar came to firing and not WHAT it
refused, and that is the half a decision actually needs.

Live, pre_tool_rule sits at a ~0.72 bar with a near-miss p90 of 0.7071 —
about 117 declines a day within 0.013 of firing. Dropping to 0.707 would
take that arm from 22 hits a day to roughly 139: six-fold, on a surface
that runs before every Bash call. The percentile says the mass is there.
Nothing said whether it was worth showing.

NEITHER OBVIOUS INSTRUMENT ANSWERS IT. Pull-through cannot: the injected
rule line already carries title and trigger, so a session can comply
without ever calling get_rule, and rule pull-through understates
usefulness by construction. Reading the rejected records can — and
`result_ids` holds only what was RETURNED, so on a zero-result call the
near-missed record had no name at all.

So the id, from the SAME ranked candidate as the score. Both searches
unpack `best` once and read both fields off it, because splitting that
into two expressions is exactly how a later edit pairs a score with its
neighbour's id — and a score attached to the wrong record is worse than no
id, since it invites judging the wrong one and concluding the bar is fine.

write_path withholds the id on the same condition it withholds the score
(#3739): a surviving id beside a null score names a record without saying
what it scored, the pair disagreeing in the other direction.

THE READ PATH IS A LISTING, NOT A STATISTIC — an id cannot be percentiled,
and a reader tuning a bar needs to go and read the records. Opt-in via
`near_miss_samples` (0-20, default 0) so the ordinary readout keeps its
size, and deliberately NOT a window function: this module's one production
outage was a grouped query Postgres rejected, swallowed by the broad
except, every counter reading zero while the mocked tests passed (#2663).
One flat ordered query, overfetched, bucketed in Python — the shape that
lesson prescribes.

Migration 0097, nullable and unbackfilled. Not a foreign key: the table
spans record types and `source` says which, exactly as result_ids works.

The integration guard pins the listing as PER SOURCE. A global LIMIT would
let a noisy source eat the whole quota and leave the surface being tuned
showing nothing — which reads as "nothing was close", the misreading this
milestone has spent itself correcting.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_011cPyzNnegXHr5iRMzzy5KJ

src/scribe/models/retrieval_log.py

@@ -62,6 +62,15 @@ class RetrievalLog(Base):
     # close": a 0.0 there would read as a corpus with no relevant records at
     # all, which is an artifact standing in for a measurement.
     best_available_score: Mapped[float | None] = mapped_column(Float, nullable=True)
+    # WHICH record scored that, so a reader can judge what the bar refused
+    # rather than only how close it came (#3807). Written from the same ranked
+    # candidate as the score above — the two describing different records would
+    # be worse than no id at all, because it invites judging the wrong one.
+    #
+    # Not a foreign key on purpose: this table spans record types (the rule arms
+    # store rule ids, the note arms store note ids) and `source` is what says
+    # which, exactly as `result_ids` has always worked.
+    best_available_id: Mapped[int | None] = mapped_column(Integer, nullable=True)
     # [{"id": int, "score": float, "rank": int}, ...], highest-first.
     result_ids: Mapped[list] = mapped_column(JSONB, nullable=False, default=list)
     duration_ms: Mapped[float | None] = mapped_column(Float, nullable=True)