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#2477, option (a) as decided, with the readout changed in the same commit. ## The two silent surfaces enter_project returns open tasks + recent notes on every project entry — probably the largest surfacing by volume — and emitted nothing, so the pulls it caused floated unattributed and the surfaced:pulled ratio ran against a denominator missing its biggest contributor. Now source "enter_project". build_process_manifest installs every reachable Process as an auto-surfacing skill on the operator's machine — its own docstring calls it the most consequential passive surface Scribe has — and emitted nothing, so a Process matched on every relevant turn and never opened was indistinguishable from one never installed. Now source "process_skill_sync": the honest event is "installed", which is a surfacing in effect since the description sits in front of the model each session. ## The readout, same commit — the condition option (a) carried Both surfaces are AMBIENT: top-N-by-recency and install-everything are not ranked choices. Pooling them into surfaced_count would make a note's number dominated by "recently updated in a project you opened", and dead-weight detection would read that as popularity — the wrong number read confidently, which is the corrupts-data tier the survey ranked above everything else. So usage_for_notes splits: surfaced_count stays RANKED-ONLY (every existing consumer's reading — "surfaced often, never pulled → dead weight" — keeps meaning what it meant), and ambient_count is new. Classified in SQL via a CASE on AMBIENT_SOURCES so the group count stays three rows per note, not one per distinct source. Pulls stay pooled: "did anyone ever open this?" does not depend on how it was found. #1038 and #2085 read agent pulls and ranked surfacings; both are unaffected by ambient volume, which is the point. Refs #2477
193 lines
7.4 KiB
Python
193 lines
7.4 KiB
Python
"""Note usage telemetry — was a surfaced note ever actually pulled?
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Two event streams, deliberately independent:
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- SURFACED: we put this note's title in front of the agent (auto-inject, or
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either arm of the write-path prior-art trigger).
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- PULLED: someone then opened it in full (get_snippet / get_note / the REST
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detail route).
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The ratio between them is the signal. A snippet surfaced forty times and never
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pulled is not neutral — it occupies the injection budget on every future turn
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and dilutes the menu — so this is what makes dead weight visible and prunable.
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Design notes (mirrors retrieval_telemetry, for the same reasons):
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- Writes are fire-and-forget. `record_surfaced` / `record_pulled` extract
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plain ints synchronously and schedule the insert as a background task, so
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telemetry never adds latency to — or can break — the surface it observes.
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- Every failure path is swallowed. Losing a usage row costs a data point;
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raising would cost the operator their retrieval.
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- Reads (`usage_for_notes`) are NOT fire-and-forget — a readout the caller
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awaits, aggregated in one round-trip for a whole page of snippets rather
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than per row.
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"""
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from __future__ import annotations
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import asyncio
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import logging
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from sqlalchemy import case, func, select
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from scribe.models import async_session
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from scribe.models.note_usage import PULLED, SURFACED, NoteUsageEvent
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logger = logging.getLogger(__name__)
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async def _insert_events(rows: list[dict]) -> None:
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"""Persist usage rows. Best-effort: all errors are swallowed."""
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try:
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async with async_session() as session:
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session.add_all([NoteUsageEvent(**row) for row in rows])
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await session.commit()
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except Exception:
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logger.debug("note usage telemetry write skipped", exc_info=True)
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def _schedule(rows: list[dict]) -> None:
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if not rows:
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return
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try:
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asyncio.get_running_loop().create_task(_insert_events(rows))
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except RuntimeError:
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# No running loop (sync context outside the app) — skip rather than
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# block. Every app path runs on the loop.
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logger.debug("note usage telemetry skipped — no running event loop")
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def record_surfaced(
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*, user_id: int | None, note_ids: list[int] | set[int], source: str
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) -> None:
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"""Fire-and-forget: record that these notes were shown to the agent.
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Takes the whole menu at once — one insert per surfacing event, not per note
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— because a menu is a single decision and its rows should land together.
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"""
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try:
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rows = [
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{
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"user_id": user_id,
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"note_id": int(nid),
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"event": SURFACED,
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"source": source,
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}
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for nid in note_ids
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]
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except Exception:
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logger.debug("note usage payload build failed", exc_info=True)
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return
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_schedule(rows)
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def record_pulled(*, user_id: int | None, note_id: int, source: str) -> None:
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"""Fire-and-forget: record that a note was opened in full."""
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try:
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rows = [
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{
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"user_id": user_id,
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"note_id": int(note_id),
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"event": PULLED,
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"source": source,
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}
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]
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except Exception:
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logger.debug("note usage payload build failed", exc_info=True)
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return
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_schedule(rows)
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# Surfacings that are NOT a ranked choice. enter_project returns whatever the
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# top-N-by-recency happen to be; the skill sync installs every Process the
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# operator can reach. Counting those alongside auto-inject would make a note's
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# surfaced_count dominated by "it was recently updated in a project you
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# opened", and dead-weight detection would read that as popularity (#2477).
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# They still matter — a pull that follows one must not float unattributed — so
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# they land in their own bucket rather than not landing at all.
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AMBIENT_SOURCES = ("enter_project", "process_skill_sync")
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def empty_usage() -> dict:
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"""The zero readout — what a note with no recorded events looks like.
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Callers render this shape unconditionally, so a note predating the table
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reads as "never surfaced, never pulled" rather than as a missing key.
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`surfaced_count` is RANKED surfacings only — a scored surface chose this
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record. `ambient_count` is the rest (see AMBIENT_SOURCES). The split is the
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readout half of #2477: the "high surfaced, zero pulls → dead weight"
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reading is only valid over surfacings that were choices.
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"""
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return {
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"surfaced_count": 0,
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"ambient_count": 0,
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"pull_count": 0,
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"last_surfaced_at": None,
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"last_pulled_at": None,
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}
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async def usage_for_notes(note_ids: list[int]) -> dict[int, dict]:
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"""Aggregate usage for a set of notes: {note_id: {counts + timestamps}}.
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One GROUP BY for the whole page rather than a query per row — this feeds a
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list view, so the per-row shape would be N+1 by construction. Notes with no
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events are returned with `empty_usage()` so the caller never has to
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distinguish "no events" from "not in the result".
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"""
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ids = [int(n) for n in note_ids]
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out: dict[int, dict] = {nid: empty_usage() for nid in ids}
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if not ids:
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return out
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try:
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async with async_session() as session:
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rows = (
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await session.execute(
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select(
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NoteUsageEvent.note_id,
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NoteUsageEvent.event,
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func.count().label("n"),
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func.max(NoteUsageEvent.created_at).label("last_at"),
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# Classified in SQL so the group count stays small: per
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# note we get at most (surfaced-ranked, surfaced-ambient,
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# pulled) rather than one row per distinct source.
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case(
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(NoteUsageEvent.source.in_(AMBIENT_SOURCES), True),
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else_=False,
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).label("ambient"),
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)
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.where(NoteUsageEvent.note_id.in_(ids))
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.group_by(
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NoteUsageEvent.note_id,
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NoteUsageEvent.event,
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case(
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(NoteUsageEvent.source.in_(AMBIENT_SOURCES), True),
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else_=False,
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),
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)
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)
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).all()
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except Exception:
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# A telemetry readout must not be able to break the list it decorates.
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logger.debug("note usage readout failed", exc_info=True)
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return out
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for note_id, event, n, last_at, ambient in rows:
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slot = out.get(int(note_id))
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if slot is None:
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continue
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if event == SURFACED and ambient:
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slot["ambient_count"] = int(n)
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elif event == SURFACED:
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slot["surfaced_count"] = int(n)
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slot["last_surfaced_at"] = last_at.isoformat() if last_at else None
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elif event == PULLED:
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# Pulls are pulls regardless of what surfaced the record — the
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# question a pull answers ("did anyone ever open this?") doesn't
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# depend on how it was found.
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slot["pull_count"] = slot["pull_count"] + int(n)
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latest = last_at.isoformat() if last_at else None
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if latest and (slot["last_pulled_at"] or "") < latest:
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slot["last_pulled_at"] = latest
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return out
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