feat(telemetry): rule_usage_events — the table, the service, and a restore that maps rule ids through the rule map (#3315)
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Milestone 333 step 1. The write-path standing-rule arm is the only retrieval
surface in Scribe whose usefulness cannot be observed — and, not
coincidentally, the only one that has never declined to fire. 296 calls, zero
zero-result, 100% clearing its threshold, while every other surface declines
most of the time (#3311, and re-measured in note #3430). `retrieval_logs`
gives it scores; scores say what the ranker thought, never whether the hint
landed.

WHY A SIBLING TABLE AND NOT A COLUMN ON note_usage_events. The row carries no
note-specific field and the readout is the same shape, which is the strongest
case for sharing that note #3163 admits. What decides against it is identity at
RESTORE: the note importer maps note_id through note_id_map, so a rule id
parked in that column comes back attached to whatever note holds that number in
the target database. Not dropped — reattached. The restore reports success, the
counters are populated, and every one is about the wrong record, with no other
field to disagree with. rule_versions made the same call for the same reason;
this is the third rule-side sibling and it reads like the first two.

FK-free on rule_id and user_id, matching note_usage_events / retrieval_logs /
app_logs, and deliberately unlike rule_versions. A version belongs to a rule's
history and dies with it; telemetry outlives what it describes. Deleting a rule
must not erase the evidence that it was surfaced forty times and opened never,
because that evidence is the case for having deleted it.

The service uses `background.spawn` rather than a third copy of the
strong-reference dance — that module's own docstring says new callers should,
and a fourth copy is how one of them drifts. The AppLog canary #2663 demands is
kept, and since `rule_usage` needed exactly `note_usage`'s semantics, that
canary moved into `background.report_telemetry_failure` and note_usage now
calls it. `retrieval_telemetry` deliberately keeps its own: its canary is a
different shape (one process-wide flag, no AppLog row), so repointing it would
change behaviour rather than consolidate it.

No ambient bucket, and that is a decision. The note twin splits ranked from
ambient surfacings because enter_project and the skill sync deliver records
without choosing them (#2477). Rules have the same problem waiting —
list_always_on_rules loads them wholesale — but nothing emits here yet, so an
empty AMBIENT_SOURCES would be machinery pretending to a distinction the data
does not contain. `source` stays granular, so the split stays a readout-level
change needing no migration.

Backup carries it (v14). The round-trip test seeds a NOTE alongside the rule so
the target database has a note id to collide with — without that decoy, a
restore running rule ids through the wrong map would merely drop them and the
test would pass by absence, rather than failing on the populated-and-wrong
result that is the actual hazard.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01TcCs1CcQ1ormdnzSshKqvN
This commit is contained in:
2026-09-02 16:55:22 -04:00
co-authored by Claude Opus 5
parent e029a7db64
commit 8826be7a91
10 changed files with 904 additions and 34 deletions
+46 -3
View File
@@ -6,20 +6,63 @@ write that never errors and never lands (the #2663 GC footgun). This module is
the one place that gets the pattern right: strong references in ``_pending``,
discarded on completion, with failures logged at WARNING instead of vanishing.
``note_usage`` and ``retrieval_telemetry`` predate this module and carry their
own copies with bespoke canary semantics; new fire-and-forget callers use this
instead of writing a fourth copy.
``retrieval_telemetry`` predates this module and keeps its own copy, because
its canary is a genuinely different shape — one process-wide flag and no
AppLog row. ``note_usage`` and ``rule_usage`` share ``report_telemetry_failure``
below. New fire-and-forget callers use ``spawn`` rather than writing another
copy of the strong-reference dance.
"""
from __future__ import annotations
import asyncio
import logging
import traceback
from collections.abc import Coroutine
logger = logging.getLogger(__name__)
_pending: set[asyncio.Task] = set()
# Sites that have already dropped their once-per-process AppLog row, keyed
# "<subsystem>:<site>". A readout can run on every list render — without this,
# a broken table turns the error log into a firehose that buries the finding it
# exists to surface.
_reported: set[str] = set()
async def report_telemetry_failure(subsystem: str, site: str) -> None:
"""Make a swallowed telemetry failure visible. Call from an except block.
WARNING to the process log every time; one AppLog error row per process per
(subsystem, site) so the admin UI shows the outage without host access.
THIS IS NOT DECORATION. #2663 is the record of a telemetry subsystem running
at zero for weeks — every counter reading empty, indistinguishable from
"nobody uses this" — because every failure went to ``logger.debug``. A
subsystem whose failures are all invisible cannot report its own death.
The AppLog write is itself guarded: when the database is down it fails too,
and that is fine. The WARNING already said so, and a canary must never take
down the surface it watches.
"""
logger.warning("%s telemetry %s failed", subsystem, site, exc_info=True)
key = f"{subsystem}:{site}"
if key in _reported:
return
_reported.add(key)
try:
from scribe.services.logging import log_error
await log_error(
endpoint=subsystem,
error_type=f"{subsystem}_{site}_failed",
error_message=f"{subsystem} telemetry {site} is failing; "
"usage counters will read zero until this is fixed",
traceback=traceback.format_exc(),
)
except Exception:
logger.debug("%s canary write failed", subsystem, exc_info=True)
def spawn(coro: Coroutine, *, site: str) -> None:
"""Schedule ``coro`` fire-and-forget; ``site`` names it in failure logs.
+58 -2
View File
@@ -12,6 +12,7 @@ from scribe.models.note_version import NoteVersion
from scribe.models.rule_version import RuleVersion
from scribe.models.design_system import DesignSystem, DesignToken
from scribe.models.note_usage import NoteUsageEvent
from scribe.models.rule_usage import RuleUsageEvent
from scribe.models.canonical_system import CanonicalSystem
from scribe.models.rulebook import RuleRelation, rule_systems as rule_systems_t
from scribe.models.code_shape import CodeShape, CodeShapeEvent, CodeShapeUse
@@ -62,8 +63,12 @@ logger = logging.getLogger(__name__)
# _COLUMN_EXCLUSIONS and its guard landed with it, so the next such column
# fails the build instead.
# v13 (2026-08) added rule_versions — a rule's edit history (milestone 323).
# v14 (2026-09) added rule_usage_events — the rule twin of note_usage_events
# (milestone 333). Carrying it is the WHOLE REASON the table is separate: the
# note importer maps note_id through note_id_map, so a rule id parked there
# would restore attached to whatever note took that number.
# Bump when the serialized schema changes.
BACKUP_VERSION = 13
BACKUP_VERSION = 14
# Every table this backup carries, by its REAL name. Paired with _NOT_INCLUDED
# below, these two lists must together account for the entire schema — which is
@@ -92,6 +97,11 @@ _BACKED_UP = [
# v13 (2026-08): a rule's edit history (milestone 323). note_versions has
# always travelled; its sibling has no excuse not to.
"rule_versions",
# v14 (2026-09): rule usage telemetry (milestone 333). Same argument
# note_usage_events makes for itself — pull-through is only ever
# accumulated, so a restore that dropped it would silently reset the
# measurement to zero while everything still looked fine.
"rule_usage_events",
]
# Tables intentionally NOT in the backup, surfaced in the payload so the gap is
@@ -178,6 +188,8 @@ _COLUMN_EXCLUSIONS: dict[str, set[str]] = {
"note_supersessions": {"id", "created_at"},
"rule_relations": {"id", "created_at"},
"note_usage_events": {"id"},
# Same as the note twin: the surrogate key is re-issued on insert.
"rule_usage_events": {"id"},
"design_systems": {"deleted_at", "deleted_batch_id", "created_at", "updated_at"},
"design_tokens": {"deleted_at", "deleted_batch_id", "created_at", "updated_at"},
"repo_bindings": {"id", "created_at", "updated_at"},
@@ -321,6 +333,17 @@ def _usage_event_rows(rows) -> list[dict]:
]
def _rule_usage_event_rows(rows) -> list[dict]:
return [
{
"user_id": r.user_id, "rule_id": r.rule_id, "event": r.event,
"source": r.source,
"created_at": r.created_at.isoformat() if r.created_at else None,
}
for r in rows
]
def _code_shape_rows(rows) -> list[dict]:
return [r.to_dict() for r in rows]
@@ -606,6 +629,9 @@ async def export_full_backup() -> dict:
)).scalars().all()
design_tokens = (await session.execute(select(DesignToken))).scalars().all()
usage_events = (await session.execute(select(NoteUsageEvent))).scalars().all()
rule_usage_events = (
await session.execute(select(RuleUsageEvent))
).scalars().all()
repo_bindings = (await session.execute(select(RepoBinding))).scalars().all()
code_shapes = (await session.execute(select(CodeShape))).scalars().all()
code_shape_events = (await session.execute(
@@ -665,6 +691,7 @@ async def export_full_backup() -> dict:
"design_systems": _design_system_rows(design_systems),
"design_tokens": _design_token_rows(design_tokens),
"note_usage_events": _usage_event_rows(usage_events),
"rule_usage_events": _rule_usage_event_rows(rule_usage_events),
"repo_bindings": _repo_binding_rows(repo_bindings),
"note_supersessions": _note_supersession_rows(supersessions),
"code_shapes": _code_shape_rows(code_shapes),
@@ -740,6 +767,14 @@ async def export_user_backup(user_id: int) -> dict:
usage_events = (await session.execute(
select(NoteUsageEvent).where(NoteUsageEvent.note_id.in_(note_ids))
)).scalars().all() if note_ids else []
# Scoped through the RULE, not the event's user_id — the same call
# rule_versions makes one block up. user_id here is whoever the arm
# fired for, so filtering on it would carry this user's surfacings of
# someone ELSE's rule and drop the ones fired for someone else on
# theirs: the opposite of a per-user export.
rule_usage_events = (await session.execute(
select(RuleUsageEvent).where(RuleUsageEvent.rule_id.in_(_rule_ids))
)).scalars().all() if _rule_ids else []
repo_bindings = (await session.execute(
select(RepoBinding).where(RepoBinding.user_id == user_id)
)).scalars().all()
@@ -858,6 +893,7 @@ async def export_user_backup(user_id: int) -> dict:
"design_systems": _design_system_rows(design_systems),
"design_tokens": _design_token_rows(design_tokens),
"note_usage_events": _usage_event_rows(usage_events),
"rule_usage_events": _rule_usage_event_rows(rule_usage_events),
"repo_bindings": _repo_binding_rows(repo_bindings),
"note_supersessions": _note_supersession_rows(supersessions),
"code_shapes": _code_shape_rows(code_shapes),
@@ -994,7 +1030,8 @@ async def _restore_v2(data: dict) -> dict:
"rulebook_subscriptions": 0, "rule_suppressions": 0,
"topic_suppressions": 0, "rulebook_exclusions": 0,
"systems": 0, "record_systems": 0, "design_systems": 0,
"design_tokens": 0, "note_usage_events": 0, "repo_bindings": 0,
"design_tokens": 0, "note_usage_events": 0, "rule_usage_events": 0,
"repo_bindings": 0,
"note_supersessions": 0, "code_shapes": 0, "code_shape_events": 0,
"code_shape_uses": 0, "canonical_systems": 0,
"rule_systems": 0, "rule_relations": 0, "rule_versions": 0,
@@ -1496,6 +1533,25 @@ async def _restore_v2(data: dict) -> dict:
))
stats["note_usage_events"] += 1
# The rule twin — and the reason it is a separate table at all.
# Resolved through rule_id_map, NOT note_id_map. A rule id run through
# the note map would either drop (best case) or land on whatever note
# took that number, producing telemetry that is wrong rather than
# missing and that nothing downstream could detect (milestone 333).
# Must come after the rules themselves; rule_id_map is populated there.
for ev in data.get("rule_usage_events", []):
mapped_rid = rule_id_map.get(ev.get("rule_id", 0))
if mapped_rid is None:
continue
session.add(RuleUsageEvent(
user_id=user_id_map.get(ev.get("user_id") or 0),
rule_id=mapped_rid,
event=ev.get("event", ""),
source=ev.get("source", ""),
created_at=_dt(ev.get("created_at")),
))
stats["rule_usage_events"] += 1
# 20. Repo bindings — small, but losing them means every bound repo
# quietly stops loading its project at session start.
for rb_data in data.get("repo_bindings", []):
+10 -28
View File
@@ -30,13 +30,13 @@ from __future__ import annotations
import asyncio
import logging
import traceback
from sqlalchemy import case, func, select
from scribe.models import async_session
from scribe.models.note_usage import PULLED, SURFACED, NoteUsageEvent
from scribe.models.base import iso
from scribe.services.background import report_telemetry_failure
logger = logging.getLogger(__name__)
@@ -46,37 +46,19 @@ logger = logging.getLogger(__name__)
# never lands. The done-callback discard keeps the set from growing.
_pending: set[asyncio.Task] = set()
# Sites that already dropped their once-per-process AppLog row. The readout
# runs on every snippet list render — without this, a broken table would turn
# the error log into a firehose that buries the finding it exists to surface.
_reported: set[str] = set()
async def _report_failure(site: str) -> None:
"""Make a swallowed telemetry failure visible. Called from an except block.
"""This subsystem's canary, now the shared one.
WARNING to the process log every time; one AppLog error row per process per
site so the admin UI shows the outage without host access. The AppLog write
is itself guarded — when the whole database is down it fails too, and that
is fine: the WARNING already said so, and a canary must never take down the
surface it watches.
The per-site dedup, the WARNING and the single AppLog row all moved to
`background.report_telemetry_failure` unchanged when `rule_usage` needed
the identical behaviour — two hand-kept copies of a thing whose whole job
is to be reliable is the wrong number. `retrieval_telemetry` deliberately
still has its own: its canary is a different shape (one process-wide flag,
no AppLog row), so repointing it would change behaviour rather than
consolidate it.
"""
logger.warning("note usage telemetry %s failed", site, exc_info=True)
if site in _reported:
return
_reported.add(site)
try:
from scribe.services.logging import log_error
await log_error(
endpoint="note_usage",
error_type=f"note_usage_{site}_failed",
error_message=f"note usage telemetry {site} is failing; "
"usage counters will read zero until this is fixed",
traceback=traceback.format_exc(),
)
except Exception:
logger.debug("note usage canary write failed", exc_info=True)
await report_telemetry_failure("note_usage", site)
async def _insert_events(rows: list[dict]) -> None:
+193
View File
@@ -0,0 +1,193 @@
"""Rule usage telemetry — did a surfaced rule ever get read?
The sibling of `note_usage`, for the one retrieval surface in Scribe that
could not be measured at all.
Two event streams, deliberately independent:
- SURFACED: the write-path standing-rule arm put this rule in front of the
agent, unbidden, during a write.
- PULLED: someone then opened it in full (`get_rule`, or the REST detail
route).
WHY THIS ARM AND NOT ANOTHER. Every other surface declines most of the time —
`write_path` returns nothing on 78% of calls, `reuse_slot` on 79%, auto-inject
on 39%. The rule arm has never once returned nothing (#3311). That is either a
perfectly tuned surface or a bar it cannot fail to clear, and `retrieval_logs`
cannot tell the two apart: it records what the ranker scored, never whether the
hint was any use. The ratio these two streams produce is the missing half, and
without it any threshold change is a number picked off a histogram.
Design notes, mirroring `note_usage`:
- Writes are fire-and-forget through `background.spawn`, so telemetry never
adds latency to — or can break — the surface it observes. This module does
NOT carry its own copy of the strong-reference dance; `background` is the
one place that gets it right, and a fourth copy is how one of them drifts.
- Failures degrade, but never SILENTLY. `report_telemetry_failure` logs at
WARNING and drops one AppLog row per process per site. #2663 is the record
of this exact subsystem class running at zero for weeks — indistinguishable
from "nobody uses this" — because every failure went to `logger.debug`.
- Reads (`usage_for_rules`) are awaited and aggregated in one round-trip for
a whole page, never per row.
NO AMBIENT BUCKET, YET — and that is a decision, not an omission. The note twin
splits ranked surfacings from ambient ones because `enter_project` and the
skill sync put records in front of the agent without choosing them, and
counting those as surfacings makes recency read as popularity (#2477). Rules
have the same shape of problem waiting: `list_always_on_rules` and
`enter_project` load rules wholesale on every session. They do not emit here
today, so there is nothing to bucket, and an empty `AMBIENT_SOURCES` would be
machinery pretending to a distinction the data does not yet contain. When a
bulk surface starts emitting, the split is a readout-level change — a tuple and
a `case()`, exactly as in the twin — and needs no migration. Keep it that way:
`source` stays granular so the choice remains available.
"""
from __future__ import annotations
import logging
from sqlalchemy import func, select
from scribe.models import async_session
from scribe.models.base import iso
from scribe.models.rule_usage import PULLED, SURFACED, RuleUsageEvent
from scribe.services.background import report_telemetry_failure, spawn
logger = logging.getLogger(__name__)
async def _report_failure(site: str) -> None:
await report_telemetry_failure("rule_usage", site)
async def _insert_events(rows: list[dict]) -> None:
"""Persist usage rows. Best-effort: failures degrade, visibly."""
try:
async with async_session() as session:
session.add_all([RuleUsageEvent(**row) for row in rows])
await session.commit()
except Exception:
await _report_failure("write")
def _schedule(rows: list[dict]) -> None:
if not rows:
return
spawn(_insert_events(rows), site="rule_usage_write")
def record_rule_surfaced(
*, user_id: int | None, rule_ids: list[int] | set[int], source: str
) -> None:
"""Fire-and-forget: record that these rules were shown to the agent.
Takes the whole hint at once — one insert per surfacing event, not per rule
— because a hint is a single decision and its rows should land together.
Record the RANKED hits only. The arm filters candidates before it speaks
(`exclude_rule_ids` drops what the session already holds), and a rule that
was considered and not shown was not surfaced. Counting those would inflate
the denominator with claims the agent never saw, which reads as a precision
problem the arm does not have.
"""
try:
rows = [
{
"user_id": user_id,
"rule_id": int(rid),
"event": SURFACED,
"source": source,
}
for rid in rule_ids
]
except Exception:
logger.debug("rule usage payload build failed", exc_info=True)
return
_schedule(rows)
def record_rule_pulled(*, user_id: int | None, rule_id: int, source: str) -> None:
"""Fire-and-forget: record that a rule was opened in full.
A PULL is somebody choosing to open one record. `list_always_on_rules` and
`enter_project` are NOT pulls — they are bulk resident loads that hand over
every applicable rule at once, and counting them would swamp the signal
with the very ambient delivery the ratio exists to distinguish from.
"""
try:
rows = [
{
"user_id": user_id,
"rule_id": int(rule_id),
"event": PULLED,
"source": source,
}
]
except Exception:
logger.debug("rule usage payload build failed", exc_info=True)
return
_schedule(rows)
def empty_rule_usage() -> dict:
"""The zero readout — what a rule with no recorded events looks like.
Callers render this shape unconditionally, so a rule predating the table
reads as "never surfaced, never pulled" rather than as a missing key. That
distinction matters more here than for notes: every rule in an install
predates this table, so for a while "no events" is the normal state and it
must not look like a broken readout.
"""
return {
"surfaced_count": 0,
"pull_count": 0,
"last_surfaced_at": None,
"last_pulled_at": None,
}
async def usage_for_rules(rule_ids: list[int]) -> dict[int, dict]:
"""Aggregate usage for a set of rules: {rule_id: {counts + timestamps}}.
One GROUP BY for the whole page rather than a query per row — this feeds a
list view, so the per-row shape would be N+1 by construction. Rules with no
events come back with `empty_rule_usage()`, so the caller never has to tell
"no events" from "not in the result".
"""
ids = [int(r) for r in rule_ids]
out: dict[int, dict] = {rid: empty_rule_usage() for rid in ids}
if not ids:
return out
try:
async with async_session() as session:
rows = (
await session.execute(
select(
RuleUsageEvent.rule_id,
RuleUsageEvent.event,
func.count().label("n"),
func.max(RuleUsageEvent.created_at).label("last_at"),
)
.where(RuleUsageEvent.rule_id.in_(ids))
.group_by(RuleUsageEvent.rule_id, RuleUsageEvent.event)
)
).all()
except Exception:
# A telemetry readout must not be able to break the list it decorates —
# but it must say it failed, or a broken readout is indistinguishable
# from a corpus nobody uses (#2663).
await _report_failure("readout")
return out
for rule_id, event, n, last_at in rows:
slot = out.get(int(rule_id))
if slot is None:
continue
if event == SURFACED:
slot["surfaced_count"] = int(n)
slot["last_surfaced_at"] = iso(last_at)
elif event == PULLED:
slot["pull_count"] = int(n)
slot["last_pulled_at"] = iso(last_at)
return out