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bvandeusen 0915c48bb0 Merge pull request 'feat(telemetry): tell a ranker decline from a repeat before the observation window opens (#3497)' (#139) from dev into main
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2026-09-03 21:23:01 -04:00
bvandeusen aea7b63b62 Merge pull request 'fix(telemetry): both rule arms logged only their hits, so the clear-rate could only read 100% (#3497)' (#138) from dev into main
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2026-09-03 07:19:08 -04:00
bvandeusen 5b02908dfd dev → main: rules become measurable at the preload, and retrievable at the tool call (#137)
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2026-09-02 23:41:09 -04:00
bvandeusen 34cd389371 dev → main: rule usage telemetry, the plugin's derived version (#136)
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2026-09-02 18:52:20 -04:00
bvandeusen b267037911 Two milestones: a note can carry its own check (317), and a rule keeps what it used to say (323) (#135)
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2026-08-31 00:01:15 -04:00
bvandeusen 93d660b710 Tool disambiguators, kind badges, and a badge layer that clears AA (#3123, #3124, #3132)
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2026-08-27 21:28:48 -04:00
bvandeusen 056c7c75da A task's kind is correctable — the Kind select stops lying (#3129)
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2026-08-27 18:05:16 -04:00
13 changed files with 30 additions and 617 deletions
+1 -1
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@@ -1,7 +1,7 @@
{
"name": "scribe",
"description": "Scribe system-of-record for Claude Code: MCP tools over your notes/tasks/projects/rules, a session-start push channel that surfaces your always-on rules + active-project context, process-skills (writing-plans, systematic-debugging, verification, brainstorming, reusing-code), and your saved Scribe Processes auto-surfaced as skills (/scribe:sync). Replaces superpowers + file-memory with one app-backed plugin.",
"version": "2026.09.04.0140",
"version": "2026.09.03.0329",
"author": {
"name": "Bryan Van Deusen"
},
-10
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@@ -21,16 +21,6 @@ for the operator's work, and as your own working memory across sessions.
compaction — call `list_always_on_rules()` (and `enter_project()` when a
project is in scope) BEFORE acting. When a loaded rule and a default habit
disagree, the rule wins; if no rule speaks to it, ask rather than assume.
- **What you loaded is not all of the rules.** Only the always-on tier arrives
that way; conditional rules are RETRIEVED, and one you were never handed
binds exactly as hard. So before a consequential act, `search` for a rule
about it (`content_type="rule"`) rather than concluding from an empty
loaded set that nothing applies. "I was not told" is not the same as "there
is no rule," and only one of those is checkable.
This bites hardest on which TOOL to reach for — curling an API that has an
MCP client, standing up a local stack, running a suite CI owns. Those feel
like mechanics rather than decisions, so they raise no doubt and generate no
query; the moment you are most confident is the moment to look.
- **Recall before acting** — before you answer anything about the operator's
work or start a task, `search` Scribe first; assume a related note, task, or
decision already exists. Concretely, reach for recall whenever a request
+4 -25
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@@ -56,31 +56,10 @@ Two constraints on *how* that's achieved:
re-deriving it or opening a duplicate. When a project is in scope, pass its
`project_id` so results stay scoped.
2. **Standing rules are binding — and the ones you were handed are not all of
them.** Load the resident set via `list_always_on_rules()` at session start
(see "Do this first"); treat every one as binding. Pull a rule's full
statement with `get_rule(id)` when it's about to bite. When a project is in
scope, `enter_project(id)` also returns its applicable rules.
Rules come in two tiers. **Always-on** rules are delivered — they arrive
whether or not you ask. **Conditional** rules are RETRIEVED, and one binds
just as hard for never having been handed to you. So before a consequential
act, `search(content_type="rule")` on what you are about to do. An empty
loaded set is not evidence that no rule applies; it is only evidence that
none was pushed, and those are different claims.
The tier split exists because delivery does not scale: every resident rule
costs tokens in every session forever, so a rulebook that grows past a few
dozen either stops growing or stops fitting. Retrieval is what lets the
rulebook keep growing — but retrieval only fires if something asks.
**Ask hardest where you feel most certain.** Rules about which TOOL to reach
for — use the forge's MCP client rather than curling its API, don't stand up
a local stack, don't run the suite CI owns — govern moves that feel like
mechanics rather than decisions. A reflex raises no doubt, so it generates
no query, so the rule that would have stopped it is never retrieved. That is
the failure this instruction exists to prevent, and confidence is its only
warning sign.
2. **Standing rules are binding.** Load them via `list_always_on_rules()` at
session start (see "Do this first"); treat every one as binding. Pull a
rule's full statement with `get_rule(id)` when it's about to bite. When a
project is in scope, `enter_project(id)` also returns its applicable rules.
3. **Update over duplicate.** When recording, prefer updating an existing
note/rule/task over creating a new one. Search first; revise what's there.
+3 -28
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@@ -45,31 +45,6 @@ from quart import Quart
# The accepted cost: an agent that never opens create_note's docstring never
# learns the field exists. Guidance lives in the create_note / update_note
# docstrings and the using-scribe skill instead.
#
# Milestone 333 step 3 (2026-09-04) bought the HOW bullet's second clause —
# search(content_type="rule") before a consequential act — by TRADING OUT
# "Processes are saved procedures (follow verbatim)" and "Deletes are
# trash-recoverable". Recorded so the trade is not silently reversed:
# - Both were already in test_instruction_surfaces_agree's DISPLACED_TOPICS
# and already stated on a delivered surface, so nothing fell off: the
# process reflex is in every scribe-proc-* skill listing (each says the
# process governs and is followed verbatim), and trash recovery is in the
# delete_*/list_trash/restore docstrings, which is where per-tool guidance
# belongs by this block's own doctrine.
# - What it bought is not per-tool guidance and has nowhere else to live at
# session-start altitude. Rules were retrievable only by RESIDENCY: the
# always-on preload put them in front of the agent, and nothing told a
# session to go looking for one it had not been handed. The tier split is
# therefore load-bearing on ANY install (rule 115): a delivered rule costs
# tokens in every session forever, so a rulebook that only delivers cannot
# grow past what one session can hold, and every rule worth keeping has to
# become resident to bind at all. Retrieval is what lets it keep growing —
# and retrieval fires only if something asks, which nothing told a session
# to do. A tool-choice reflex asks least of all (#3476, #161).
# - This states the PULL for conditional rules, exactly as the surrounding
# line states it for always-on ones. Rule 119 makes these surfaces the
# specification, so the same sentence lands on all three session-start
# surfaces, and test_instruction_surfaces_agree pins it.
_INSTRUCTIONS = """
Scribe is the operator's self-hosted second brain and system of record — and
yours: recall from it before acting, record as you go. Keep no parallel copy
@@ -88,13 +63,13 @@ Hierarchy: Project -> Milestone -> Task/Note. The map, by purpose:
active project_id to stay in scope.
- WHERE work happens: Systems. Tag records with system_ids as you write;
create_system when the area is unmodelled.
- HOW: rules bind. list_always_on_rules() at start; before a consequential
act, search(content_type="rule") — the resident set is not all of them.
- HOW: rules are binding — list_always_on_rules() at session start.
- UI: the project's design system is binding — resolve_design_system /
get_design_system_stylesheet before hand-writing a value.
- REUSE: search snippets before writing a helper; record what you build with
create_snippet; classify shapes against canon (classify_shapes) — a
consumer map is rows, never prose.
consumer map is rows, never prose. Processes are saved procedures (follow
verbatim). Deletes are trash-recoverable.
A task is a note with status (*_note vs *_task tools).
Creates are duplicate-gated: a near-match BLOCKS and returns the existing
-65
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@@ -315,61 +315,6 @@ async def create_rule(
) -> dict:
"""Create a new rule in a rulebook (a SHARED rule — keep it general).
PROPOSE RULES READILY, AND WRITE ONE WHEN THE OPERATOR SAYS YES. Noticing
that something has hardened into a standing instruction is valuable work,
and a session that notices it and says nothing has thrown the observation
away. So raise it whenever you see one. The single step that belongs
between noticing and writing is the operator's yes: a rule binds every
future session, and they are the person it binds.
Their yes is also the only moment the rule is reliably IN FRONT of them.
After the write it may not be again for months — a conditional rule is not
read aloud at session start, and a project-scoped one does not appear in
an unfiltered list_rules() at all. So the proposal is the review.
When the operator asks for a rule in so many words, that IS the yes —
write it and move on. The loop below is for the rule you thought of.
A PROPOSAL CARRIES FOUR THINGS, and the fourth is the one that decides it:
1. WHAT it would require — the statement, in the words it would carry,
not a gloss of them. The operator is agreeing to text.
2. INTENT — what it changes about how work gets done, and what goes
wrong today without it. "Be careful about X" is not an intent; the
behaviour that would differ tomorrow is.
3. WHY NOW — the incident, observation or decision behind it. Pass that
record as arose_from_id, and say it in the conversation too: the
field is for the reader six months out, the sentence is for the
person deciding.
4. HOW IT WOULD BE ENFORCED — a test, a CI check, a hook, a schema
constraint, a duplicate gate, a review step... or nothing, in which
case say so plainly: "nothing — this is prose a session has to
remember." Answer this one honestly and it will sometimes dissolve
the rule, which is the point rather than a side effect. What a test
can assert should BE that test; a rule is what remains when nothing
mechanical can hold the thing. A rulebook grows by default and
shrinks only on purpose, so a question that prevents a rule is worth
more than any question that improves one's wording.
THEN CLOSE WITH A QUESTION THEY CAN ANSWER IN ONE WORD. Offer three
answers, and make the middle one the easy one:
* "Approve it AS WRITTEN" — you create it with the statement exactly as
shown. This is what makes element 1 load-bearing: they approved TEXT,
so that text is what gets stored, verbatim.
* "LET'S TALK ABOUT IT" — the wording, the scope, the tier, whether it
wants to be a rule at all. Most good rules arrive this way, so treat
this answer as the expected one rather than a setback.
* "NO" — let it go. If the observation is still worth keeping, it is a
note (create_note): recorded, findable, and binding on nobody.
Where the interface offers structured choices, ask it that way — a
question with named options is answered in a click, while the same
question inside a paragraph is answered by scrolling past. Where it does
not, write the three options out as three options. Either way ask once
and let the answer stand; re-raising a declined proposal argues a rule
into existence, which is the thing this whole loop exists to prevent.
A rulebook rule is shared by every project that gets the rulebook: an
always_on rulebook binds ALL your projects; a subscribed rulebook binds the
projects that opt in. So a rulebook rule must read as a general standard —
@@ -488,16 +433,6 @@ async def create_project_rule(
the rule is returned in get_project's applicable_rules (under
project_rules) and in list_rules(project_id=...).
PROPOSE, THEN WRITE ON A YES — create_rule's opening carries the whole
loop: the four things a proposal states (what it would require, its
intent, why now, and how it would be enforced) and the one-word question
that closes it (approve as written / talk about it / no). All of it
applies here unchanged. Reach for that loop MORE readily on this surface,
not less: a project rule stays out of an unfiltered list_rules(), and a
conditional one stays out of session start too, so the operator's yes is
the one moment this rule is certain to have been seen by the person it
binds.
Check first whether a rule is the right shape at all — create_rule's
opening asks that question and it applies identically here. A visual
standard is a design system; a procedure is a process (create_process);
+4 -24
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@@ -237,30 +237,10 @@ It is an UPPER BOUND per surface: a pull records the door it came
those same rules over time: a resident set surfaced thousands of times and
opened never is the dead-weight signal, one tier up.
Read it against `sources["write_path_rule"]`. That arm was once believed
never to decline — the reading that scoped #3311 — but it was the arm's
`retrieval_logs` row being written only on calls that FOUND something, so
the zeros were missing rather than absent (#3497). Measured since, it
declines the large majority of its calls like any other surface.
EVERY COUNTER BLOCK CARRIES ITS OWN COVERAGE — `complete_from` and
`covers_window`. `complete_from` is when the number became trustworthy:
for one source, its first recorded row; for a section that sums several,
the LATEST of theirs, because a total is complete only once every
contributor was being written. `covers_window: false` means the window
reaches back further than the recording does, so the count is a fraction
of the period it appears to describe.
READ IT BEFORE COMPARING TWO NUMBERS, and especially before comparing
across a deploy. A counter added last week, read over a 30-day window,
reports a real count against an imagined denominator — and the result is
a plausible fraction rather than an obvious zero, which is what makes it
dangerous. That reading cost milestone #379 five steps aimed at a defect
that did not exist.
`covers_window` is null, never false, when nothing was ever recorded:
"no measurement" is not "partial measurement", the same distinction
`suppression`'s null carries a few paragraphs up.
Read it against `sources["write_path_rule"]`. That surface has never once
declined to fire, and until this block existed there was no way to tell a
well-tuned arm from a bar it cannot fail to clear (#3311). `pull_through`
is the number that tells them apart.
`rule_usage_failed: true` means that read failed while the rest of the
readout stood. The counts are still present so a caller can render, but
+4 -11
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@@ -774,17 +774,10 @@ async def semantic_search_rules(
is the surfacing question, and it has its own machinery
(get_applicable_rules) rather than a second, subtly different copy here.
`tier` narrows to one tier, and NONE is the ordinary case. The write-path
and pre-tool hints deliberately pass nothing: an always-on rule is already
in the session, but being in a list from turn zero is not the same as being
in front of the reader when the action it governs is taken, and filtering
on tier made a whole class of rules permanently ineligible for the one
mechanism that surfaces a rule AT the moment. Relevance is the threshold's
job; see the block above RULEHINT_LIMIT in services/plugin_context.py for
the argument and for what the resulting scores are being read against.
Pass a tier when a caller genuinely wants one class — a listing, an audit,
a UI that renders the tiers apart. Not to approximate relevance.
`tier` narrows to one tier. The write-path hint passes "conditional",
because an always-on rule is ALREADY in the session — surfacing it again as
a suggestion is pure noise, and noise on a hint that fires on every write
is how a hint gets ignored.
Collapses to best-chunk-per-rule like the note search, so a long rule split
across chunks competes once rather than crowding the results with itself.
+12 -60
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@@ -94,17 +94,13 @@ WRITEPATH_DEFAULT_THRESHOLD = 0.68
# THE STRUCTURAL ARGUMENT, which is the only kind admissible here (rule 115).
# Two facts hold on any install, including one with six rules and no telemetry:
#
# 1. The eligible corpus is SMALL — every rule an install owns, still only
# a few dozen documents against thousands of notes. A top-k over a small
# pool always returns something, so "the best match cleared the bar"
# drifts from "a good match exists" toward "N things were ranked". A bar
# calibrated for best-of-thousands is cleared by best-of-forty as
# arithmetic rather than relevance.
# This argument WEAKENED when the arms stopped filtering to one tier
# (see the note on that below): a larger pool makes clearing the bar
# mean more, not less. The threshold was deliberately left where it was
# anyway — moving two variables at once would make the resulting
# distribution unreadable, and this one errs toward silence on purpose.
# 1. The eligible corpus is TINY. The arm searches `tier="conditional"`
# rules only — a handful to a few dozen documents against thousands of
# notes. A top-k over forty candidates always returns something, so
# "the best match cleared the bar" stops meaning "a good match exists"
# and starts meaning "forty things were ranked". A bar calibrated for
# best-of-thousands is cleared by best-of-forty as arithmetic, not
# relevance.
# 2. Rules are short imperative technical English — a far more HOMOGENEOUS
# corpus than note prose. #2223 measured the floor for code against prose
# at 0.55-0.63 and set 0.68 above it. A more homogeneous corpus has a
@@ -132,14 +128,9 @@ RULEHINT_DEFAULT_THRESHOLD = 0.72
# ONE rule per write, not two — and this is deliberately NOT a knob.
#
# With a corpus this small, top-k does as much damage as the threshold: k=2
# over a few dozen candidates means the second line is almost always the
# second-best noise, arriving with the same confident framing as the first.
# Halving k halves that regardless of where the bar sits.
#
# It also BOUNDS the blast radius of widening the pool (below): with k=1 a
# wider corpus can change WHICH rule surfaces and how often one does, but it
# can never make a single hint longer. The loudness of one hint and the
# eligibility of a rule are separate controls, and only one of them moved.
# over forty candidates means the second line is almost always the second-best
# noise, arriving with the same confident framing as the first. Halving k
# halves that regardless of where the bar sits.
#
# It stays a constant because it is a decision about how LOUD one hint may be,
# not a per-install tuning question. The hint already carries prior art, shape
@@ -149,45 +140,6 @@ RULEHINT_DEFAULT_THRESHOLD = 0.72
# adds a way to misconfigure the surface (rule 25 cuts both ways).
RULEHINT_LIMIT = 1
# WHY THE ARMS NO LONGER FILTER TO ONE TIER (#3702).
#
# Both arms used to pass `tier="conditional"`, on the reasoning that an
# always-on rule is already in the session, so surfacing it again is pure
# noise. That reasoning conflates two different things:
#
# PRESENT IN CONTEXT — the rule was delivered at session start.
# SALIENT AT THE MOMENT — the rule is in front of the reader when the
# action it governs is about to be taken.
#
# A rule handed over in a list at turn zero is present while a session writes
# a config value three hundred turns later. It is not surfaced. So the filter
# did not merely skip a redundant hint — it made a whole class of rules
# permanently ineligible for the only mechanism that puts a rule in front of
# an agent AT the moment, and the more important a rule is, the more likely
# it was in that class.
#
# The deeper defect is that the filter was doing the THRESHOLD's job. Whether
# a rule belongs in this hint is a relevance question, and a similarity bar is
# the control for relevance. A categorical exclusion standing in for a
# relevance judgment cannot be tuned, cannot be measured, and cannot be wrong
# in a way anybody notices.
#
# THIS IS A MEASURED CHANGE, NOT A SETTLED ONE. The old comment's fear is
# real — a hint that fires on every write and says obvious things teaches the
# reader to skip the block, and the surface is then lost along with its true
# positives. That fear had simply never been checked. `retrieval_logs` already
# records top_score, result_count and the query for every call, so the
# evidence now arrives on its own:
#
# - rules clear the bar often and at high scores -> the fear was justified,
# the filter was a crude proxy for a bar set too low, and the WORK IS THE
# BAR. Any reinstated filter should then carry a measured reason.
# - rules clear rarely, in a thin band near the bar -> the filter was never
# the right instrument and relevance was always sufficient.
#
# Only the eligibility moved. The bar and k=1 were both left exactly where
# they were, so the resulting distribution has one cause.
# How much of a command reaches the embedding (#3476). A shell call is not a
# file: most are short, and the ones that are not are usually a heredoc or a
# pasted script whose bulk says nothing about which rule applies. The VERB AND
@@ -1253,7 +1205,7 @@ async def build_write_path_hint(
rule_t0 = time.perf_counter()
hits = await semantic_search_rules(
user_id, code or path, limit=RULEHINT_LIMIT,
threshold=cfg["rule_threshold"],
threshold=cfg["rule_threshold"], tier="conditional",
)
rule_ms = (time.perf_counter() - rule_t0) * 1000.0
fresh = [(score, rule) for score, rule in hits if rule.id not in already]
@@ -1385,7 +1337,7 @@ async def build_tool_rule_hint(
t0 = time.perf_counter()
hits = await semantic_search_rules(
user_id, query, limit=RULEHINT_LIMIT,
threshold=cfg["rule_threshold"],
threshold=cfg["rule_threshold"], tier="conditional",
)
duration_ms = (time.perf_counter() - t0) * 1000.0
+1 -71
View File
@@ -217,57 +217,6 @@ def _round(v, places: int = 4):
return None if v is None else round(float(v), places)
async def _complete_from(session, model, user_id) -> dict[str, Any]:
"""When each source in `model` started being recorded, and the instant the
WHOLE table is complete from. Returns {source: earliest_row, "*": latest}.
THE GRAIN IS THE SOURCE, and that is the whole point. `retrieval_logs` has
rows going back months, so a table-level "earliest row" says months and
tells a reader their window is fully covered — while a source added last
week has a week of rows and a counter that silently means something else.
Per-source is the only grain at which partial coverage is visible.
THE AGGREGATE USES THE LATEST, NOT THE EARLIEST. A number that sums several
sources is complete only once EVERY contributor was recording, so "*" is a
max over the sources, not a min. Taking the min here would reproduce the
exact reading this exists to prevent: the oldest source vouching for the
youngest.
All-time, deliberately unfiltered by the window — a query bounded by
`since` can only ever report something at or after `since`, which answers
nothing.
"""
rows = (
await session.execute(
select(model.source, func.min(model.created_at))
.where(model.user_id == user_id)
.group_by(model.source)
)
).all()
out: dict[str, Any] = {src: ts for src, ts in rows if ts is not None}
stamps = list(out.values())
out["*"] = max(stamps) if stamps else None
return out
def _coverage(complete_from, since) -> dict:
"""The two keys every counter block carries, from one timestamp.
`covers_window` is None — never False — when nothing was ever recorded.
"No rows at all" is not "partial coverage", it is no measurement, and the
null convention #3497 established for `suppression` holds here for the
same reason: absent must not read as a verdict.
"""
return {
# iso() already returns None for an unset value (#2845) — the guard
# belongs on covers_window, which is a verdict, not a serialisation.
"complete_from": iso(complete_from),
"covers_window": (
None if complete_from is None else complete_from <= since
),
}
async def retrieval_summary(user_id: int | None, *, days: int = 30) -> dict:
"""What the retrieval telemetry says, per surface, over a window.
@@ -334,9 +283,6 @@ async def retrieval_summary(user_id: int | None, *, days: int = 30) -> dict:
by_source_rows = None
rule_rows = None
distinct_rules_surfaced = distinct_rules_pulled = 0
# None means the coverage read did not happen — distinct from a table with
# no rows, which is {"*": None}. Same reason `read_failed` exists.
note_complete = rule_complete = None
try:
async with async_session() as session:
@@ -365,15 +311,8 @@ async def retrieval_summary(user_id: int | None, *, days: int = 30) -> dict:
.group_by(RetrievalLog.source)
)
).all()
log_complete = await _complete_from(session, RetrievalLog, user_id)
for row in rows:
source = row[0]
bucket = _bucket(list(row[1:]))
# Per SOURCE, not per table: retrieval_logs goes back months
# while any individual arm may be days old, and the table's
# age would vouch for an arm that has barely started.
bucket.update(_coverage(log_complete.get(source), since))
out["sources"][source] = bucket
out["sources"][row[0]] = _bucket(list(row[1:]))
# The corpus side, at its own grain. `ambient` mirrors
# note_usage.usage_for_notes: an ambient surfacing was not a scored
@@ -400,7 +339,6 @@ async def retrieval_summary(user_id: int | None, *, days: int = 30) -> dict:
.group_by(NoteUsageEvent.event, NoteUsageEvent.source)
)
).all()
note_complete = await _complete_from(session, NoteUsageEvent, user_id)
# Distinct-note counts need their OWN queries, and this is not
# fussiness: count(distinct note_id) per (event, source) group
@@ -528,9 +466,6 @@ async def retrieval_summary(user_id: int | None, *, days: int = 30) -> dict:
.group_by(RuleUsageEvent.event, RuleUsageEvent.source)
)
).all()
rule_complete = await _complete_from(
session, RuleUsageEvent, user_id,
)
# The rows carry `source`, so the ranked/ambient split is done
# below rather than in SQL — the bulk surfaces started emitting
# on 2026-09-03 (#3473), so there IS an ambient class now.
@@ -640,10 +575,6 @@ async def retrieval_summary(user_id: int | None, *, days: int = 30) -> dict:
}
usage["by_source"] = by_source
# The SECTION's coverage, from the latest source to start recording — a
# figure that sums several sources is complete only once every one of them
# was being written. `_complete_from` computes that as "*".
usage.update(_coverage((note_complete or {}).get("*"), since))
out["usage"] = usage
# ── Rules, deliberately a SEPARATE block ────────────────────────────
@@ -721,7 +652,6 @@ async def retrieval_summary(user_id: int | None, *, days: int = 30) -> dict:
round(rule_usage["pulled_by_agent"] / rule_usage["surfaced"], 4)
if rule_usage["surfaced"] else None
)
rule_usage.update(_coverage((rule_complete or {}).get("*"), since))
out["rule_usage"] = rule_usage
return out
-40
View File
@@ -195,46 +195,6 @@ def test_displaced_topics_live_on_a_delivered_surface():
)
# The SECOND pull (milestone 333 step 3). `list_always_on_rules()` fetches the
# resident tier; this one says that tier is not all of them, and that a
# conditional rule has to be gone looking for. However a surface words the
# surrounding prose, it names the call.
RETRIEVE = 'content_type="rule"'
def test_every_session_start_surface_states_the_conditional_retrieval():
"""The push/pull asymmetry, one level in.
The tests above pin that a session PULLS the resident rules rather than
trusting the SessionStart push. This pins the same shape between the two
TIERS: an always-on rule is delivered, a conditional one is retrieved, and
a surface that states only the first leaves a session reading its loaded
set as the whole rulebook.
That reading is wrong in the direction that costs something. "Nothing was
pushed" and "no rule applies" are different claims, and only one of them
has been checked — the same asymmetry as #2198, now between tiers instead
of between channels.
It is also what made the always-on tier the only one that worked, on any
install rather than this one (rule 115). A rule nothing retrieves has to be
resident to bind at all, so every rule worth keeping becomes resident; and
a resident rule costs tokens in every session forever, so a rulebook that
only delivers cannot grow past what one session can hold. Retrieval is what
lifts that ceiling — and it only fires if something asks.
"""
missing = []
for path in SESSION_START_SURFACES:
if RETRIEVE not in path.read_text():
missing.append(str(path.relative_to(ROOT)))
assert not missing, (
f"these surfaces state the always-on pull but never tell the agent to "
f"retrieve a conditional rule ({RETRIEVE}): {missing}. A session that "
f"reads its loaded set as the whole rulebook will act on \"I was not "
f"told\" as if it meant \"there is no rule\" (milestone 333 step 3)."
)
def test_no_surface_names_the_push_without_stating_the_pull():
"""The exact shape #2497 took.
-120
View File
@@ -1,120 +0,0 @@
"""Both rule-creation tools run the propose-then-approve loop (#3557).
WHY THIS EXISTS
Every other gate on `create_rule` and `create_project_rule` is about SHAPE:
is this a rule or a process, is it one thing you could violate, is it general
enough for a rulebook, is it a near-duplicate. All of those improve a rule
someone has already decided to write. None of them asks the prior question —
whether the person the rule will bind has agreed to be bound by it.
That question belongs at the tool, because the tool is the last surface a
caller reads before the write, and because the write is less reversible than
it looks. The operator's yes is not merely consent; it is the one moment the
rule is certainly IN FRONT of them. Afterwards it may not be again for
months: a conditional rule is not read aloud at session start, and a
project-scoped rule does not appear in an unfiltered `list_rules()` at all.
The proposal IS the review, so there had better be one.
WHY IT IS PHRASED AS A PRACTICE AND NOT A PROHIBITION
The first cut of this guidance opened "NOT YOURS TO CALL UNPROMPTED." That is
the wrong instrument, and the failure it invites is worse than the one it
prevents: a caller reading a prohibition stops NOTICING rule-shaped things,
rather than noticing them and asking. The wanted behaviour is more proposals,
not fewer — spotting that something has hardened into a standing instruction
is valuable work, and the only step that was ever missing came after it.
So the docstrings describe what to DO: propose readily, state four things,
close with a question the operator answers in one word. This test is written
the same way — it asserts the parts of the loop are present, and has nothing
to say about any wording that forbids.
The fourth element — how the rule would be ENFORCED — is not ceremony. It is
the part that sometimes dissolves the rule: a thing a test can assert should
be that test, and a rule is what is left when nothing mechanical can hold it.
A rulebook grows by default and shrinks only on purpose, so the question that
prevents a rule earns more than any question that improves one's wording.
WHAT THIS PINS, AND WHAT IT DOES NOT
STRUCTURE, never wording — the same bargain the disambiguator guard (#3123)
strikes next door. Each element matches a family of synonyms, so the prose
stays free to be rewritten, reordered or sharpened; only DELETING one fails.
Pinning phrasing would make every improvement a red build, and a test that
punishes editing is a test someone deletes.
It cannot tell whether an agent actually proposes. Nothing in a docstring
can. It catches the regression that really happens: guidance tidied away in
a later pass by someone who read it as throat-clearing in front of the Args.
"""
import pytest
from tests.helpers import tool_doc as _doc
# Both surfaces, because the one that needs it most is the one that looks
# minor. A project rule is the least visible record the system can hold —
# absent from an unfiltered list_rules(), and absent from session start too
# whenever it is conditional — so the surface that writes one carries the
# larger risk while reading as the smaller act.
_SURFACES = [
("scribe.mcp.tools.rulebooks", "create_rule"),
("scribe.mcp.tools.rulebooks", "create_project_rule"),
]
# The loop, element by element, each as a family of ways to say it. A
# docstring satisfies an element by containing ANY member — that is the room
# left for rewriting. The families deliberately exclude bare words a
# docstring would hold by accident ("why", "how", "reason", "rule"), which
# would let the assertion pass on prose that says nothing of the kind.
_ELEMENTS = {
"the invitation to propose": ("propose", "proposal"),
"the operator's approval": ("approve", "approval", "says yes", "a yes"),
"the rule's intent": ("intent", "what it changes about how work"),
"why it is being proposed now": (
"why now", "arose_from_id", "the incident", "prompted it",
),
"how it would be enforced": ("enforc",),
"the answers offered back": ("as written", "talk about it", "discuss"),
}
@pytest.mark.parametrize(("module", "name"), _SURFACES)
@pytest.mark.parametrize("element", sorted(_ELEMENTS))
def test_a_rule_surface_carries_every_part_of_the_proposal_loop(
module, name, element
):
"""Each element of propose → state four things → ask survives."""
doc = _doc(module, name).lower()
assert any(token in doc for token in _ELEMENTS[element]), (
f"{name}'s docstring no longer mentions {element}. A caller reads "
f"this immediately before writing a rule that will bind every future "
f"session, and the proposal is the one moment that rule is certain to "
f"be seen by the operator. Say it in whatever words you like; this "
f"guard only checks it is still said. See create_rule's opening."
)
@pytest.mark.parametrize(("module", "name"), _SURFACES)
def test_the_proposal_loop_comes_before_the_parameter_contract(module, name):
"""It has to be read to work, and the Args: block is where reading stops.
A caller who has decided to make the call skims down to the parameters.
Guidance parked below them — or folded into one argument's description —
arrives after the decision it was meant to inform, which is the same as
not being there.
"""
doc = _doc(module, name).lower()
args_at = doc.find("args:")
assert args_at > 0, f"{name}'s docstring has no Args: block"
loop_at = min(
(doc.find(t) for t in _ELEMENTS["the invitation to propose"]
if doc.find(t) >= 0),
default=-1,
)
assert 0 <= loop_at < args_at, (
f"{name} introduces the proposal loop at or after its Args: block "
f"(loop {loop_at}, args {args_at}). Move it to the opening — a "
f"caller who has already decided to write the rule reads the "
f"parameters, not the prose under them."
)
+1 -9
View File
@@ -160,15 +160,7 @@ async def test_the_arm_searches_on_its_OWN_bar_not_the_code_one():
kw = search.await_args.kwargs
assert kw["threshold"] == 0.81, "the arm is still using the code threshold"
assert kw["limit"] == pc.RULEHINT_LIMIT
# NO tier filter (#3702). The arms search every rule the caller owns,
# because "already in the session" is not the same as "in front of the
# reader at the moment it applies" — and relevance is the threshold's
# job, not a category's. If this assertion is failing because a tier
# argument came back, read the block above RULEHINT_LIMIT first: the
# filter may legitimately return, but only carrying a measured reason.
assert "tier" not in kw or kw["tier"] is None, (
"the arm is filtering the rule corpus by tier again"
)
assert kw["tier"] == "conditional"
@pytest.mark.asyncio
-153
View File
@@ -638,156 +638,3 @@ async def test_ambient_alone_reports_no_ratio(_dispose_engine):
assert ru["pull_through"] is None
finally:
await cleanup()
# ── Window coverage (#3712) ────────────────────────────────────────────
#
# A counter added last week, read over a 30-day window, reports a real count
# against an imagined denominator. The result is a plausible FRACTION rather
# than an obvious zero, which is what makes it dangerous — #379 spent five
# planned steps on a defect that turned out to be a window opening before the
# recording it was measuring existed.
def test_coverage_says_nothing_rather_than_false_when_nothing_was_recorded():
"""Null, never False. "No measurement" is not "partial measurement".
The same distinction `suppression`'s null carries (#3497): absent must not
read as a verdict. A False here would assert the window is under-covered,
which is a claim nobody is in a position to make.
"""
from datetime import datetime, timezone
from scribe.services.retrieval_telemetry import _coverage
since = datetime(2026, 9, 1, tzinfo=timezone.utc)
assert _coverage(None, since) == {
"complete_from": None, "covers_window": None,
}
def test_coverage_reads_a_start_before_the_window_as_covered():
from datetime import datetime, timezone
from scribe.services.retrieval_telemetry import _coverage
since = datetime(2026, 9, 1, tzinfo=timezone.utc)
older = datetime(2026, 8, 1, tzinfo=timezone.utc)
newer = datetime(2026, 9, 5, tzinfo=timezone.utc)
assert _coverage(older, since)["covers_window"] is True
assert _coverage(newer, since)["covers_window"] is False, (
"a counter that started inside the window covers only part of it"
)
assert _coverage(newer, since)["complete_from"] == newer.isoformat()
@pytest.mark.integration
@pytest.mark.asyncio
async def test_coverage_is_per_source_because_the_table_is_older_than_its_arms(
_dispose_engine,
):
"""THE grain question, and the reason a per-table answer is useless.
`retrieval_logs` accumulates for months. A table-level "earliest row"
therefore says months for every source it holds — including one added
days ago whose counter means something quite different. The old source
would vouch for the young one, which is exactly the reading this exists
to prevent.
"""
from datetime import datetime, timedelta, timezone
from sqlalchemy import delete
from scribe.models import async_session
from scribe.models.retrieval_log import RetrievalLog
from scribe.services.retrieval_telemetry import retrieval_summary
UID = 990077
now = datetime.now(timezone.utc)
async with async_session() as s:
# An old surface, recording since well before any window we ask for,
# AND still recording inside it. Both rows are needed: `complete_from`
# comes from the all-time query, but a source only gets a bucket at all
# if it has rows in the window, so the 90-day row alone would leave
# nothing to assert on.
s.add(RetrievalLog(
user_id=UID, source="auto_inject", result_count=1,
created_at=now - timedelta(days=90),
))
s.add(RetrievalLog(
user_id=UID, source="auto_inject", result_count=1,
created_at=now - timedelta(days=1),
))
# A young arm, first written INSIDE the window below.
s.add(RetrievalLog(
user_id=UID, source="pre_tool_rule", result_count=1,
created_at=now - timedelta(days=2),
))
await s.commit()
try:
out = await retrieval_summary(UID, days=30)
assert out["sources"]["auto_inject"]["covers_window"] is True
assert out["sources"]["pre_tool_rule"]["covers_window"] is False, (
"the young arm was reported as covering a 30-day window — the "
"table's age has been allowed to vouch for one of its sources"
)
finally:
async with async_session() as s:
await s.execute(delete(RetrievalLog).where(RetrievalLog.user_id == UID))
await s.commit()
@pytest.mark.integration
@pytest.mark.asyncio
async def test_a_section_is_complete_only_from_its_latest_contributor(
_dispose_engine,
):
"""A sum is complete once EVERY contributor was being written — so the
section takes the LATEST first-row, not the earliest.
Taking the earliest would be worse than reporting nothing: it would pick
the oldest source in the table and use it to certify a total that a
newer source is still only partly contributing to. That is the original
error in miniature.
"""
from datetime import datetime, timedelta, timezone
from sqlalchemy import delete
from scribe.models import async_session
from scribe.models.rule_usage import RuleUsageEvent
from scribe.services.retrieval_telemetry import retrieval_summary
UID = 990078
now = datetime.now(timezone.utc)
old = now - timedelta(days=90)
young = now - timedelta(days=2)
async with async_session() as s:
s.add_all([
RuleUsageEvent(
user_id=UID, rule_id=1, event="surfaced",
source="list_always_on_rules", created_at=old,
),
RuleUsageEvent(
user_id=UID, rule_id=2, event="surfaced",
source="pre_tool_rule", created_at=young,
),
])
await s.commit()
try:
out = await retrieval_summary(UID, days=30)
ru = out["rule_usage"]
assert ru["complete_from"] == young.isoformat(), (
"the section reported completeness from its OLDEST source; a "
"total is only as complete as its newest contributor"
)
assert ru["covers_window"] is False
finally:
async with async_session() as s:
await s.execute(delete(RuleUsageEvent).where(RuleUsageEvent.user_id == UID))
await s.commit()