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a58a225d7b |
fix(embeddings): a backfill reads text when it embeds, not when it scanned (#4264)
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Every backfill selected the text alongside the id and then iterated that snapshot, sleeping between records. Over a real corpus that is minutes, and anything edited inside the window was re-embedded by its own write path and then OVERWRITTEN with the pre-edit text the scan had captured — stamped at the current chunker version, so the next boot considered it current and never repaired it. The record stayed findable by what it used to say, indefinitely, until someone happened to edit it again. Nothing reported it, and no existing signal separated it from a correct record: the version was right and the vectors were there. All four backfills had it. Three were pre-existing; I wrote the fourth an hour ago for #4251 by copying the third. #4251 also widened the exposure. The race used to need a note-body edit; now every add_task_log re-embeds its task, so any session recording work during a backfill can hit it — which is exactly what "forward work continues while the backfill runs" means. TWO HALVES, SEPARATE ON PURPOSE. Stopping it: the scan takes IDS ONLY and `_current_row` re-reads each record at the moment it is embedded. One indexed primary-key read, negligible beside the forward pass that follows, and it turns a backfill from "replay a snapshot" into "repair to current truth". The residual race shrinks from the length of the run to the width of one record, which the parent-row claim and the single-transaction replacement narrow further. Repairing it: `_vectors_older_than_their_record` adds a third staleness condition beside "no vectors" and "old chunker" — vectors older than the text they encode. A guard that refuses to write a bad value does not undo the bad values already stored (#4202); the rows are what has to change. That check earns its place beyond the bug that prompted it. It equally catches a record whose `embed_note` never ran — no event loop, a swallowed refresh, a process that died between the commit and the index. Every one of those looks identical from the version column and identical from outside. And a work log is part of a task's document while living in its own table, so writing one never moves `notes.updated_at` and the timestamp comparison cannot see it. `_tasks_logged_since_embedding` covers exactly the records the race was most likely to have hit. The live instance has already run #4251's backfill — the prior-art arm is surfacing `## Work log —` passages, which is the thing itself rather than a banner about it. Whether that run clobbered anything is unknown and was not measured; the repair half picks up whatever it did on the next boot, without needing it diagnosed first. The structural guard in the tests was checked against the old shape, not just the new one: reintroducing `select(Note.id, Note.title, Note.body)` makes it fail, so it can catch the next copy of this rather than only agreeing with today's code (#167). Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01821k5B3Ysecp9fNYs92Kuy |
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1fca8c2808 |
feat(retrieval): a System's charter becomes an answer, not just a filter (#4251)
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Step 2 of #4251. A System's `description` is a charter — several hundred words saying what belongs in that area and what does not — and it is the answer to "which part of this codebase does X live in". There was no semantic path to one: `list_systems` enumerates, and `search(system_id=…)` uses a System as a FILTER over notes. So a System could narrow a search and could never be the answer to one, and an agent asking where a record belonged had to read every charter or guess. ITS OWN SEARCH, not a `content_type` over notes, for the reason note 3163 gives about milestones: the row could be shared, the search cannot. A charter competing with the whole note corpus for one top-k is outranked by the records filed under it — the right answer crowded out by its own contents — and "where does this belong?" is a different question from "what prior art is there?", which a caller asking one should not have to read past answers to. So `system_embeddings` (0107) joins note_, rule_ and milestone_embeddings as the fourth sibling, with `system_document`, `upsert_system_embedding`, `semantic_search_systems`, a startup backfill and `search(content_type= "system")`. Scoped like milestones: with a project_id, that project's Systems if the caller can read the project (rule 78); without one, the caller's own. Archived Systems are excluded — an archived area is one the operator has said is no longer where things go, which is exactly the question being asked. `system_document` is the plainest of the four shapes on purpose. A charter is already written as the thing this search has to match, in the words someone asking would use — so there is no trigger to synthesise as `rule_document` must, and no second record to gather as `task_document` must. The stored charter IS the sharp document, the way a snippet's is. `color`, `status` and `order_index` stay out: presentation and bookkeeping, and a vector carrying them would be answering a question nobody asks of a charter. The search publishes `report["best_chunk"]` from the start rather than being retrofitted, which is what #4251 asked of any fourth search. It matters more here than anywhere: a charter runs long and a result shows its NAME, so a match on the paragraph that actually decides where a record belongs would otherwise be previewed by two words that cannot say. The id that comes back is the one `system_id`, `system_ids` and `list_system_records` already take, so the answer to "where does this belong?" is directly usable as "show me what is there" and as "file it here". `embed_system` sits beside `notes.embed_note` at the service for #2056's reason — every door gets it by construction. Not called on delete: that is a soft delete and the search joins through `System`, so the vectors are already unreachable, and leaving them means a restore is findable again immediately. `system_embeddings` is declared in backup's `_NOT_INCLUDED` as derived, beside its three siblings. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01821k5B3Ysecp9fNYs92Kuy |
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aa95c109ea |
feat(retrieval): a task's work logs join the document it is embedded as (#4251)
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Step 1 of #4251. A work log is the richest prose Scribe holds about WHY something is the way it is — written during the work, recording what was tried and ruled out. #4241 made it readable from the agent's door. It was still not findable, so "has anyone tried this approach?" — precisely the question a log answers — could not reach one. The cost is not hypothetical: #4208 was rebuilt in this session because its logs were unreachable. THE DESIGN QUESTION the issue left open was whether logs embed as part of their task's document or as rows of their own. As their own rows, a hit has to be resolved back to a task to be worth anything, and it needs a fourth search, a fourth result shape and a fourth arm. As part of the task, the objection is that a long log drowns a short title. That objection was true before #280 and is not true now. Chunking made one record into one vector per section, so each log becomes its own title-anchored chunk, scored separately, and the task's own prose keeps the chunk it always had — a task is as findable as its best-matching log rather than as the average of everything in it. The other half is this session's other build: a search hands back the chunk that won (#4243), so a hit earned by a log shows that log's passage under the task's title. Without that a reader would have got body[:240] of the task — the opening of a record whose relevance lives three hundred lines further down. So `task_document(title, body, logs)` sits beside `rule_document`: a synthesised embed-time shape, because the stored record is the task row and the logs live in their own table, so the document that should be searchable exists nowhere until it is built. A task with no logs is returned untouched — most notes are not tasks and most tasks carry no log, and their vectors are the corpus every tuned number here was measured against. CHUNKER_VERSION 1 → 2, and its comment now says what the version actually means. It used to read "whenever chunk_document's output can change for the same input", which this change would slip past: `chunk_document` is untouched and every task with a log now embeds differently while its title, body and the chunker all stand still. The invariant is the document a record is embedded as. The startup backfill re-embeds on that. Create, edit and delete of a log all refresh the task through `embed_note`, the one path every writer shares — an edited log whose vectors still carry its old wording keeps matching what it no longer says. No new kind enters the auto-inject menu: tasks were always in it, and this makes recall on them better rather than changing what the menu spans. The calibration stamp will now report shape_version 2 against numbers measured at 1, which is exactly the report #4104 built it to make. Also promoted `session_returning` into tests/helpers beside `make_mock_session` (#2834) — two files had spelled it out identically and a third was about to. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01821k5B3Ysecp9fNYs92Kuy |
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253fb974f3 |
feat(retrieval): every semantic search hands on the passage that matched
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#4243 fixed one door. Scribe has three semantic searches over three chunk tables, and all three collapsed chunk rows to the best one per record — each of them KNEW which passage earned the hit, and each dropped it. Every surface downstream then previewed the head of the document instead: a span the search had already scored lower, with nothing saying so. Mechanism, one place: - embeddings.record_best_chunk publishes {id: {index, text}} into `report`. Carried in `report`, NOT the return value: all three return list[tuple[float, Record]] and ~30 sites unpack that pair (lesson #4207). - semantic_search_rules and semantic_search_milestones now select chunk_index/chunk_text and publish the winner, as notes already did. semantic_search_milestones gains `report`, which it had no way to take. - services/text.matched_excerpt is the one choice of span, and excerpt_fields the one result block. Doors keep their own field names — the web renders `snippet`, MCP returns `excerpt` — because renaming a field a frontend reads is a different change from fixing what goes in it. Surfaces: - knowledge.query_knowledge, whose own comment calls it "the human's MAIN search surface", was `(note.body or "")[:200]` on every row alike. Now the matched passage on a search, the opening on a browse, and `snippet_is` saying which. KnowledgeView renders that snippet, so this was live. - search(content_type='milestone') gains `matched` — the plan body stays out, but the passage that matched comes along, because recognising a plan means recognising the part you asked about and a description written at the start need not mention it. - The auto-inject menu and the write-path prior-art menu put the passage under their line. Both were title-only, which answers "does this apply?" for a lesson or snippet (the trigger is IN the title) and not at all for an issue or dev-log. No fallback to the body's opening: on a menu that is preamble dressed as a reason, and once indented it cannot be told apart. Left alone deliberately: the rule arms. A rule hint already renders the rule's TRIGGER, which is written to answer exactly "does this apply to me" and beats a matched chunk at it; and that line's budget was measured at #3851. Adding a passage there would duplicate the trigger and spend the budget twice. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01821k5B3Ysecp9fNYs92Kuy |
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fdc07f2a2b |
fix(search): show the passage that matched, not the opening of the body (#4243)
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Raised by the operator: are we limiting what comes back by character count,
and how do we verify the pertinent part is the part displayed?
We were not. mcp/tools/search.py sent (note.body or "")[:240] — a head cut,
with no marker that anything had been removed, so a 240-character preview of
a 4000-character record was indistinguishable from a complete short one.
The opening is the wrong span. The match is semantic and per chunk, and
semantic_search_notes collapses to best-chunk-per-note — its own comment at
the collapse says "the first appearance of a note is its best chunk". So the
system identified the passage that earned the hit and then discarded it:
select(Note, distance) kept no chunk column. A record could rank first on its
sixth paragraph, be previewed by its first, and be judged irrelevant on a
span the search had already scored lower. That biases against long records,
and it is self-concealing — the caller who does not open it never learns the
preview was misleading.
- embeddings: chunk_index/chunk_text ride along in the select, and the
collapse records the winner in report["best_chunk"]. Carried in `report`,
NOT by widening the return tuple: ten callers unpack (score, note) at
~18 sites and nothing would catch the misses (lesson #4207). `report` is
the side-channel this function already uses for best_available_score.
- search(): excerpt / excerpt_is / body_length, and read_full when there is
more. A caller that cannot tell a matched passage from a document opening
cannot judge whether to look deeper, which is the only decision the field
supports.
elide() moves to services/text.py so both callers share one copy, and it
keeps BOTH ends with a stated gap — it is the fallback for when nothing
identifies a better span than "all of it", not the goal.
Also fixes a guard that produced a false failure on the previous commit:
test_pull_telemetry checked `"project_id: int = 0" in body.split("\n")[0]`,
which sees only the first line, so wrapping get_task's signature over four
lines made it report a function that does take the project as one that does
not. Parsed with ast now, and proven to still reject an absent or
wrongly-typed parameter rather than being appeased by reflowing the code.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01821k5B3Ysecp9fNYs92Kuy
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1252d0e305 |
fix(lessons): a derived mirror survives the generic note door, by kind not by name (#3734)
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Groundwork for step 7, and a data-integrity fix in its own right. Two kinds keep a queryable mirror in `notes.data` derived from their body: snippets and, since milestone 385, lessons. Every read prefers the mirror — deliberately, because parsing markdown to answer what an index can answer is how a hot path rots. So a write that moves the body must move the mirror. #3128 found that hole for snippets and plugged it with a hard-coded `if note.note_type == SNIPPET_NOTE_TYPE`. The plug was correct and did not generalise: lessons arrived with the same design and none of the protection, which is precisely the "don't add a fourth instance" defect #3734 was told to avoid. The cost is higher for a lesson. A stale snippet mirror reports the wrong path. A stale lesson mirror reports the wrong TRIGGER, and the trigger is the whole retrieval story — the lesson goes on firing for the situation it used to name while displaying the one it now names. Silent, and confident. So `update_note` now dispatches through `_mirror_recomposers()`, a note_type -> recomposer table. A kind with a derived mirror is covered by registering it, not by someone remembering to widen an if. `lessons.recompose_data` is the lesson's entry. It recovers the subject with `embeddings.untrigger_title` — new, and deliberately placed beside the join it inverts rather than in the caller that wanted it, because a separator spelled in two files is a separator that will one day be changed in one of them (#3207). `TRIGGER_SEP` is now the one spelling, and `parse_snippet_fields` uses it too; it had the third copy inline. The two inverses stay distinct on purpose: a snippet partitions at the first separator (its name is a symbol), a lesson strips an exact known suffix (its subject may legitimately contain a dash). Different algorithms, one constant, so they cannot disagree about where the seam is. Provenance is DROPPED when the body drops it, which is the opposite call from a snippet's `verification` — that is carried because it was never in the body to delete. The body is the authority; carrying a value the reader just removed is the failure the recompose exists to prevent. Tests: test_snippet_mirror_generic_door.py becomes test_derived_mirror_generic_door.py, since the concern is now plural. The registry property is asserted directly (every kind with a mirror is in the table; the dispatch names no kind inline), plus the lesson cases and the join/inverse round-trip. `fake_lesson` moves to tests/helpers.py — it existed in test_lesson_surfacing.py and a second copy was about to be written — and gains the explicit `None`s `fake_snippet` carries, because update_note reads `verify_with` and a MagicMock is truthy. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01821k5B3Ysecp9fNYs92Kuy |
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1361ed7200 |
feat(lessons): the document shape is the stored record, and it travels (#3730)
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Milestone 385 step 3 — the step where the kind either works or is cosmetic.
THE DOCUMENT, and why there is no `lesson_document()` beside `rule_document()`
in embeddings. The step expected one. The difference is where the sharp shape
LIVES. A rule keeps its trigger in a column and its title is a plain name, so
`{title} — {trigger}` has to be synthesised at embed time and exists nowhere
else. A snippet — the only sharp record in the corpus by #2485's measurement,
0.153 top-to-second against 0.010–0.023 — gets there the other way: its STORED
title is already the join and its stored body already opens with the trigger,
so the ordinary `title\nbody` join IS the sharp document. Step 1 chose the
snippet route and step 2 built it, so `lessons.lesson_document` composes what
is STORED and the generic chunker does the rest.
The consequence the step asked about: `chunk_document` is untouched, so
CHUNKER_VERSION does not move and NOTHING re-embeds. The step's "Re-embed"
section describes a change this design does not make.
THE NARRATIVE stays in the body, departing from the step's instruction to keep
it out. `rule_document` excludes `why` because long dated narrative made
sixteen dev-logs land on the centroid of "development" — but that finding
predates chunking (#280). A body over budget is now split, and every chunk is
prefixed with the title, which for a lesson carries the trigger. The story
occupies its own vectors instead of averaging itself into the trigger's, and
each of those is still anchored to when the lesson applies. A guard asserts
exactly that. Holding the story out would cost the reader the only part that
explains the insight, to buy a sharpness the chunker already provides.
GLOBAL IN THE SEARCH is the real new code: `GLOBAL_NOTE_TYPES` and
`include_global_kinds` on `semantic_search_notes`, widening the PROJECT filter
alone. Off by default, because two callers depend on that filter holding — the
near-duplicate gate compares a record only against its own project on purpose,
and a globally visible kind there would let a lesson block an unrelated note's
create on a project its author never touched. It composes with `note_type`
rather than overriding it, so narrowing to snippets does not quietly acquire
lessons, and it changes nothing about the ACL: `notes_visibility_clause` still
gates every row.
Wired into the explicit MCP search only — the operator asked, and there is no
budget to spend. The unasked-for injection arms are step 5's subject (#3732)
and the legibility of a lesson appearing on a foreign project is step 7's
(#3734), so neither is turned on here.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01821k5B3Ysecp9fNYs92Kuy
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0ab15d7d80 |
feat(lessons): the lesson kind, and one join for every trigger title (#3729)
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Milestone 385 step 2, implementing decision #4157 from the step-1 spike. The kind: `note_type='lesson'`, a note findable by WHEN IT APPLIES rather than by what it is about. The trigger lives in `notes.data.when_to_apply`, mirrored into the title and the head of the body — the shape snippets already use, and the reason nothing re-embeds: chunk_document is untouched, so CHUNKER_VERSION does not move. NO MIGRATION, and the step assumed there would be one. `note_type` carries no CHECK — only `task_kind` does (0056, 0065). Migration 0036 added it as plain Text with a server default and nothing has gated it since, so rule 36 has no whitelist to expand and #3128's failure mode (a value the database refuses) cannot arise for this column. The vocabulary that actually decides what a reader can reach is services.knowledge._FACETS, which since #3161 is one table feeding the door's validation, the counts and both dialects of the type filter — so the kind lands there in a single edit. ONE JOIN, not a fourth copy. `{subject} — {trigger}` had three implementations: rule_document, snippets.compose_title, and this step needed another. #3207 records what that costs, so the join moves to embeddings.trigger_title beside embedding_text and all three delegate. Behaviour is unchanged for rules and snippets; the guard calls each through its own public name, so a re-implementation fails it. The #3163 bill is stated in the service docstring rather than left to be inferred: versions, supersession, trash, the share ACL, tags, project and System tagging, chunked embeddings and the duplicate gate are all inherited; status/task_kind/milestone_id and recurrence are not, and verify_with/expires_when are available but outside the kind's contract. The status cell is the one that matters — `is_task` IS `status is not None`, so a lesson that acquired one would become a task. The integration guard asserts the WRITE rather than the constraint: it holds whether or not note_type is ever gated, and goes red only if it is gated without this value. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01821k5B3Ysecp9fNYs92Kuy |
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aee24c9c1c |
feat(retrieval): a tuned number carries the space it was measured in (#4104)
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Milestone 416 step 6. A retrieval floor is a cosine similarity, which only means something inside one embedding model's geometry over documents cut one particular way. Change either and every floor on the install keeps applying while describing nothing — and nothing anywhere says so, because the scores simply come out different and the bar goes on cutting. `CHUNKER_VERSION` already solved this for documents: stamped per row, so the backfill re-embeds precisely what is stale. The same idea, applied to the numbers: - `calibration_stamp()` — embedding model + document shape, one definition. TWO fields, never a fused string (rule 149): a mismatch has to say WHICH half moved, because they call for different responses. - `retrieval_tuning_events` gains `embedding_model` / `shape_version` (migration 0104), stamped on every write. Nullable and NOT backfilled — "unstamped" is the honest answer for a row written before this existed, and it reports as `stale: null`, never as fine. - `current_settings` reports calibration per dial: tuned rows from their event, untouched dials from the registry default's own stamp. - `retrieval_surfaces` and the Settings panel show the mismatch. The panel renders ONLY when something is stale, so seeing it at all is the signal. - `migrate_floor` / `migrate_retrieval_floor` answers "a path for thresholds to be inherited by the next model so that they don't have to recalibrate a lot": the raw cosine cannot cross models, but the PERCENTILE it represented can. Measure what fraction of a surface's logged calls the old floor admitted, re-score those queries under the current model, take the value admitting the same fraction. Dry run by default; applying writes an ordinary tuning event with the arithmetic in its reason. Nothing auto-retunes. A stale stamp says a number is no longer a measurement; it does not say what the number should be, and #4102 measured the one case where the statistic and the correct action pointed opposite ways. The load-bearing test is an ABSENCE: no chat-model identifier may appear anywhere in the calibration path. Claude produces none of these scores, so a Claude upgrade must trigger nothing — a false alarm here teaches the operator to ignore the real one on the day bge-small becomes bge-base. Backup v17 carries both columns, unfilled on the way out and on the way back: a round trip must not turn "we don't know" into a stated fact. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01821k5B3Ysecp9fNYs92Kuy |
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3a501c2cac |
feat(search): milestones are searchable by meaning — "is there already a plan for this?" (#4078)
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`search` covered notes, tasks and rules, and a milestone — the record a plan lives in — could not be found. A project whose roadmap was written as milestones had every later plan opened beside the one that already described it, because nothing could have told the session it existed. - milestone_embeddings (migration 0102): the third sibling of note_ and rule_embeddings, for note 3163's reason — the search is milestone-specific. The document is title — description, then description and the plan body, so a roadmap milestone with no description is still found by its design. - Written on create, on a title/description/body update, and for a plan made through start_planning / create_records, fire-and-forget with the parent-row claim (#3262); a startup backfill covers every existing milestone. Derived, so it joins _NOT_INCLUDED beside the other embeddings. - semantic_search_milestones: a project's milestones when the caller can read it (access.can_read_project), otherwise the caller's own; optional status. - search(content_type="milestone"): id, title, description, status, project and progress. Its own shape, and not part of "all", whose results are note-shaped. The docstring says what it is for: ask before start_planning. - Integration test on real Postgres: found in its project and not another, status narrows, an unreadable project returns nothing. Milestone 415 step 3. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01821k5B3Ysecp9fNYs92Kuy |
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188e78bbcd |
feat(rules): retrieval honours a rule's home — global everywhere, a project's rules only in that project (#4074)
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semantic_search_rules searched every rule the user owned, and every hook arm called it without a project, so each project's rules were injected into every other project's sessions and a project rule meant nothing a session could feel. The search now takes a scope: global rules by default (an unbound session, or a caller that forgets to say), global plus project N when given project_id (N's rules only if the caller can read that project, through access.can_read_project), and every owned rule with everywhere=True. The four hook arms and the report preference lookup pass the session's project; an explicit search(content_type="rule") scopes to its project_id, or asks the whole rulebook without one. Milestone 414 step 1. Guarded by an AST walk that every hook call site passes project_id, and an integration test on real Postgres that a rule is reached only from its home. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01821k5B3Ysecp9fNYs92Kuy |
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c149ef31a3 | wip(394): steps 6+7 — backend path and instruction surfaces | ||
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d5f96563fd |
feat(rules): a slot a preference cannot lose (#3894)
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Milestone 399 step 4. A rule and a preference are not equally served by one
ranking, because their losses are not equal:
- a RULE crowded out at the prompt boundary still fires at an act arm. A
push reaches pre_tool_rule, a write reaches write_path_rule. The prompt
hit is a preview of a second chance.
- a PREFERENCE about how to answer has no second chance. The response IS
the act, so crowded out there it is never delivered at all.
A straight ranking therefore favours the record whose loss is recoverable
over the one whose loss is total, and does it INVISIBLY: the rule that won is
a legitimate hit, the telemetry reads healthy, and the only symptom is a
preference that quietly never arrives. reuse_slot exists for the same shape
one corpus over (#2463).
`semantic_search_rules` gains a `kind` filter, so the slot's query can only
answer with what the slot is for. Verifying afterwards would be weaker — an
unfiltered search that happened to return a rule would spend the slot on it,
and that line would be indistinguishable from one that earned its place.
THE SLOT BUYS POSITION, NOT A LOWER BAR, matching reuse_slot. A weak
preference cannot buy it, so silence stays the default. The task asked for a
separate threshold; I did not add one, and the reason is that the worry
behind it — reading a miss rate as a fact about preferences — is answered by
`preference_slot` being its own logged source, where best_available_id names
which preference was refused. A knob added on a guess is a way to
misconfigure the surface; a bar moved on evidence is an argument. The
evidence arrives on its own now.
IT EXTENDS, IT NEVER DISPLACES — and here it parts from reuse_slot, which
evicts its menu's weakest hit. A displaced hit sits in prompt_rule's
retrieval_logs row while never being surfaced, so that source's two tables
stop agreeing and #3668's identity breaks for a reason nothing in the data
explains. Milestone #379 is what losing that identity costs: five steps
planned against two counters disagreeing, not a write path dropping rows. One
extra line in a rare case is the cheaper price.
It also runs BEFORE the bail-out. An empty general result is not proof no
preference qualifies: that search overfetches by distance then collapses, so
a preference ranked below the window is invisible to it while a kind-filtered
query finds it at once. Bailing first would make the slot dead in exactly the
corpus it exists for.
One existing assertion repinned from a bare call_count to a per-source
filter: the slot logs its own query on the same call, and a count would pin
the number of arms rather than the property — going red the next time one is
added, which is rule 167's false alarm about the thing it protects.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_011cPyzNnegXHr5iRMzzy5KJ
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d5ac8408f6 |
feat(telemetry): record WHAT the bar turned away, not only how close it came (#3807)
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#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 |
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623464323e |
fix(telemetry): a search that never ran is not a decline (#3765)
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`best_available_score` was added by #3670 so a bar could be judged from what it rejected, and it arrived null on four unrelated causes: the corpus offered nothing, the query was empty, the embedder was down, or the DATABASE QUERY FAILED. Only the first is a measurement. The fourth is the #2663 shape — a swallowed failure rendering as a clean zero — inside the field added to fix an instance of the #2663 shape. Found while trying to explain why reuse_slot returned nothing on 45 of 45 calls, and auto_inject on 153 of 161. That investigation is still open; what it established first is that the readout could not answer it. THE FIX IS NOT A NEW COLUMN. A call that never searched writes no row, so every remaining null means one thing: searched, and nothing came close. That is the convention the pre-tool arm already follows for a blank command — "a row here would report a call that never happened and drag the clear-rate down with phantom declines" — extended from the case a caller can see in advance to the ones only the search knows about. Both searches stamp `report["searched"]` FALSE before anything can return and True only where a real result set exists, so every early return leaves it false. It has to be the first thing done to the dict: a return added above that line would leave the key absent. ABSENT IS A THIRD STATE AND IT DEFAULTS TO TRUE. A caller that passes no report cannot know, and the safe reading there is the old behaviour. Only a real search can report False, so absent means "nobody asked" and never "it failed" — which is also why 66 existing mocked searches across twelve test files keep working unchanged rather than being rewritten to simulate a flag they do not care about. A FAILURE IS NOT MADE INVISIBLE. semantic_search_notes already logs a WARNING on a query failure, which is where a broken search belongs: a counter cannot say "I am broken" without a reader already trusting it. Three tests, and the middle one is what makes them discriminate — a blanket `return` passes the first and fails the second, because a call that searched and came back empty is the only evidence a threshold is too high (#3497). Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_011cPyzNnegXHr5iRMzzy5KJ |
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e7c1af32a0 |
fix(telemetry): the bar can only be judged from what it rejected (#3670)
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`cleared_threshold` was documented as the number to read first. It was a tautology. The search applies the threshold before returning, so every returned result cleared it by construction and a call with no results has no top_score to compare — the condition was true exactly when `result_count > 0`. It was `calls - zero_result_calls` under a name that promised a second opinion, and `zero + cleared == calls` held on all nineteen source/window readings ever taken, today's live seven included. The reading procedure built on it asked the reader to compare a number with itself, and a threshold change was unobservable through it: raise the bar and both numbers move together, so the field could never show a bar set too high. REPLACED, NOT JUST REMOVED. The question the table exists to answer is whether the bar is in the right place, and that is only answerable from the calls that returned NOTHING: how close did the best rejected candidate come? A 0.72 bar turning away a stream of 0.71s is set too high by a hair; the same bar turning away 0.30s is working. Both render as a zero-result call today and nothing separates them, because the losing score is discarded inside the search. So both searches now rank WITHOUT the bar and apply it in Python. The qualifying set is provably identical — rows arrive ordered by distance, so every above-bar row sorts ahead of every below-bar one, and an over-fetch that returned N above-bar rows returns the same N plus some losers. What changes is that the losers are visible instead of dropped in the query. `report` carries the score out without changing what a search RETURNS: eight of eleven call sites want hits and nothing else. New column (migration 0096), nullable and unbackfilled. A row written before this genuinely does not know, and a 0.0 would read as "the corpus held nothing remotely relevant" — a claim invented out of a caller's silence, which is the substitution this whole milestone corrects. The new aggregate is a percentile_cont WITHIN GROUP over a CASE, one step from the shape that produced #2663, where a rejected query was swallowed by the broad except and every counter read zero. It carries an integration guard for that reason: only real Postgres can say it parses, and the symptom of failure is silence. Also adds a guard that no int field in a bucket equals `calls - zero_result_calls`. That identity is what `cleared_threshold` satisfied for its whole life, and it survived because it had its own name and nobody added the two numbers beside it. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_011cPyzNnegXHr5iRMzzy5KJ |
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dd1e6e2645 |
feat(rules): the rule arms stop filtering the corpus to one tier (#3702)
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Both arms passed tier="conditional", on the reasoning that an always-on
rule is already in the session so re-surfacing it is pure noise. That
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 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 likelier it sat in that
class.
Underneath, the filter was doing the THRESHOLD's job. Whether a rule belongs
in a 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.
MEASURED, NOT SETTLED. 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. It
had simply never been checked, and retrieval_logs already records the scores
to check it with. Rules clearing often and high means the fear was justified
and the BAR is the work; rules clearing rarely in a thin band means relevance
was always sufficient.
Only eligibility moved. The bar stays at 0.72 and k stays at 1, so the
resulting distribution has one cause — and k=1 bounds the blast radius: a
wider pool can change which rule surfaces and how often, never how long a
single hint gets.
The threshold rationale's first premise ("the eligible corpus is TINY —
tier=conditional only") is updated rather than deleted: a larger pool makes
clearing the bar mean MORE, so that argument weakened, and the bar was left
alone anyway rather than move two variables at once.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_011cPyzNnegXHr5iRMzzy5KJ
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9d8104f7a5 |
fix(embeddings): key_share alone is FOR NO KEY UPDATE, not FOR KEY SHARE (#3262)
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SQLAlchemy spells Postgres's four row locks as a read/key_share pair, so `with_for_update(key_share=True)` renders FOR NO KEY UPDATE — an exclusive lock that two refreshes of the same record would fight over, and that an ordinary concurrent edit would block. The claim needs `read=True` as well to be the FOR KEY SHARE the docstring describes. Caught by the unit test that compiles the statement, which is the whole reason it asserts on the rendered lock mode rather than on behaviour that looks identical either way. |
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7827b4ce63 |
fix(embeddings): the index refresh loses the race it used to deadlock (#3262)
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An embedding refresh replaces a record's vectors as delete-then-insert, which takes the chunk rows first and the parent row second (via the insert's foreign key). A cascading delete of the parent takes exactly those two locks in the other order. Postgres calls the cycle a deadlock and kills one side: sometimes the detached embedder, silently, and sometimes the user's delete, as a 500 on an operation that should have worked. Both upserts now claim the parent row with FOR KEY SHARE NOWAIT before touching any chunk row. That removes the cycle instead of narrowing it — either the embedder is first and the delete queues behind it, or the delete already holds the row and the embedder loses at once, which is the side designed to lose. FOR KEY SHARE is the lock the insert would take anyway, so an ordinary edit is unaffected. The note twin, recorded as unverified on the issue, has the same shape and the same fix; a trash purge is the hard delete that reaches it. Unit tests pin the ORDER and the lock mode by compiling the statement; the integration pair holds a real delete open in one transaction and proves the embedder returns having written nothing, with a deadline so a regression fails instead of hanging. |
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02c1e37620 |
feat(rules): the write path can notice a standing rule it was never given (#3031, milestone 307 step 5, hook arm)
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A conditional rule is not resident, so a session can be about to violate one it was never handed. This arm notices: when what is being written resembles a rule's trigger, the hint names it and says to read it before deciding it does not apply. A SUGGESTION, and the plan was wrong about why it could be more. It claimed the hook "already resolves a path to an area" — it does not, and nothing in Scribe maps a path to a System or a canonical area (build_write_path_hint resolves paths against snippet LOCATIONS, a different index; the learned-alias idea belongs to another project). Correction logged on the task. Rather than invent path→area inference to make a stale claim true, the arm does what D7 already decided and what this surface already IS: tags bind at enter_project, meaning suggests here. The header of the hook says NEVER BLOCKS; dressing a hint up as binding would have been the actual mistake. CONDITIONAL RULES ONLY. An always-on rule is already in the session, so re-offering it is noise — and noise on a hint that fires on every write is how a hint gets ignored. Telemetry goes to retrieval_logs, NOT note_usage_events, and that is a correctness call rather than a preference: note_usage ids are REMAPPED on a backup restore, so a rule id written there would come back attached to whatever note took that number — silently corrupting the evidence the next true-up is supposed to read. retrieval_logs is never restored and `source` already separates surfaces. record_retrieval's `results` type widened to match what it actually needs (an `.id`), instead of passing a Rule to something annotated Note. The rule dedup gets its OWN state file and query parameter, like the three channels before it — #2708's lesson was that one shared channel lets a hint of one class silence a different class that had never been shown. Plugin version bumped: a hook change clients cannot see did not ship (#1040). The stub is autouse in conftest rather than added to forty-odd call sites: the arm loads an embedding model, and every existing test that stubs the NOTES search would otherwise pull a real model in through the one arm it had no way to know about. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> |
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6ada97bb0b |
fix(rules): resolve the Rule forward ref for ruff and readers (#3030)
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F821: the quoted `"Rule"` in semantic_search_rules' return annotation evaluates fine at runtime — a string inside a subscript is a value, not a name lookup — but it points at nothing a reader or a type checker can follow, which is what ruff is objecting to and it is right to. A TYPE_CHECKING import resolves it at zero runtime cost, while the real import stays inside the function so this module still does not pull in the rulebook models. Placed after the import block, where isort wants the guard. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> |
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95a37318fc |
feat(rules): rules become findable by meaning (#3030, milestone 307 step 4)
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Rules were the only major record type with no vector, so `search` could never return one and a rule could arrive only by being preloaded. That single fact is what made every rule compete for one always-on budget. THE DECISION THE TASK ASKED FOR, made explicitly: a sibling rule_embeddings table, not a polymorphic embedding row. The ROW could have been generalised; the SEARCH could not. semantic_search_notes is Note-specific scoping end to end — the visibility clause, the supersession penalty, note_type/task_kind/system filters — and a rule shares none of it, scoping instead by rulebook ownership or project. Generalising the row while still needing two searches is the worst of both: a key with referential integrity to neither table, on the path every session start runs, to share four columns. What is genuinely common is BEHAVIOUR — get_embedding, chunk_document, embedding_text, CHUNKER_VERSION — and those are reused as-is. Sharing them is the DRY win; sharing the table would have been the DRY costume. The document shape is measured, not chosen (note 2485). That pass found the snippet was the only discriminative record in the corpus — a 0.153 top-to-second gap against 0.010-0.023 — and that the cause was its SHAPE: purpose stated twice in a short single-topic document. rule_document reproduces it: the trigger in the title AND as the body's first line. And it excludes `why`, which matters more than any of it. `why` is dated incident narrative — rule 46's runs to 4,300 characters — and long multi-topic prose is exactly what made sixteen dev-logs mutually indistinguishable. Adding it would not give the vector more to work with; it would give every rule the SAME thing to work with. rule_document takes no `why` parameter at all, so a well-meaning caller cannot pass one. A rule with no trigger degrades to title + statement — findable, less sharp. That is an argument for backfilling triggers (step 6), not for padding the document with whatever text is nearby. search(content_type="rule") returns the rule WITH its why and how_to_apply: they are its operational half, the session payload never carries them, and a caller who went looking should not have to re-fetch. Writes re-index fire-and-forget like notes; startup backfills in its own try block so neither backfill can skip the other. rule_embeddings is derived, so it joins note_embeddings in the backup's explicitly-NOT-included list. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> |
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041d8defbc |
feat(embeddings): best-chunk-per-note on every retrieval surface (#280 step 4)
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A note's relevance is now its best chunk's similarity, everywhere: - semantic_search_notes keeps the indexed raw-distance top-k and over-fetches chunk rows (x4, composing with the x3 supersession over-fetch), then collapses to first-appearance-per-note — rows arrive distance-ordered, so first is best. Every ranked consumer (MCP/REST search, Browse, auto-inject, write-path, gate) inherits through the one function. - list_notes semantic q swaps its join for a correlated MIN-distance subquery — the join would have repeated a long note once per matching chunk and made total count chunks. - the duplicate report groups its self-join by note pair on MIN(distance): pair similarity = closest chunk pair, and the < join now also drops cross-chunk self-pairs that would flag every long note against itself. - the write gate queries once per chunk of the candidate (capped at 8), so a note duplicating an existing record in ONE SECTION is caught — the whole-document query diluted exactly the section that mattered. Integration test now seeds a two-chunk note and pins the collapse against real pgvector. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01UaYUaouG9jjhATyuxCKrQs |
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0e70a3896b |
feat(embeddings): per-chunk rows — schema, write path, version-aware backfill (#280 steps 2+3)
note_embeddings becomes one row per chunk: PK (note_id, chunk_index), plus chunk_text (what this vector actually encodes) and chunker_version. Migration 0077 clears the table — embeddings are derived (0067 precedent) and the old whole-document rows are indistinguishable from single-chunk notes, so the startup backfill regenerates the corpus at the new shape. The backfill is now version-aware: a future shape change is a CHUNKER_VERSION bump that re-embeds exactly the stale notes, not another wipe. upsert_note_embedding takes (title, body) and chunks internally — one path for the write path, the recurrence spawn and the backfill. The recurrence spawn's own embed call is deleted outright: create_note already embeds via embed_note (#2056), so the spawn was a second copy of the rule. An emptied record now CLEARS its stale vectors instead of leaving them findable. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01UaYUaouG9jjhATyuxCKrQs |
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6b5043a69c |
feat(embeddings): chunk_document — the chunked document shape (#280 step 1)
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bge-small reads 512 tokens and fastembed truncates silently, so a single whole-document vector permanently lost everything past ~400 words. The new shape: split at markdown headings (fence-aware), merge small sections, split oversize ones at paragraph boundaries, title-anchor every chunk, repeat the section heading on continuation pieces. A record that fits the window yields exactly one chunk identical to the historical title\nbody shape, so the corpus's sharpest records are byte-for-byte unaffected. CHUNKER_VERSION added so later shape changes re-embed by version comparison instead of a table wipe. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01UaYUaouG9jjhATyuxCKrQs |
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f11a547cd2 |
fix(lists): shared-project records appear, and a list's q means what search means
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#2462, both decided halves. ## The ACL defect list_notes filtered on Note.user_id == user_id with no scope parameter at all — never a per-call decision, the capability was absent. query_knowledge beside it was deliberately browse-scoped with a comment saying why. So a task in a shared project was invisible in list_tasks, enter_project's open-task list, the SessionStart todo count and the web UI's task views, while the same project's notes and snippets appeared. Now the shared clause: notes_visibility_clause(user_id, "browse"). Browse and not read, per decision #2094 — an ambient list must never surface a record someone shared one-to-one; those stay search-only. This is the remaining half of a fix made twice before (#2159 widened fetch, #2092 widened meaning), and the guard below is what stops a fourth half appearing. Guarded by source inspection in test_retrieval_scopes: every list-shaped service references a shared visibility clause AND carries no bare Note.user_id comparison that would quietly re-narrow it. An owner-only list returns correct-looking rows and simply omits the shared ones — the shape no behavioural test catches. ## q is semantic (operator: "make it match") The UI's note list keyword-matched while the UI's Browse search semantic-matched, over the same records, with nothing saying so. Now one meaning: q joins the embedding index and orders by cosine distance at the interactive floor, with every lifecycle filter still applied in the same indexed query. Relevance ordering wins over `sort` when q is present — a query is a relevance claim, and sorting its results by date would shuffle the answer. ILIKE survives only as the embedder-down fallback: degraded, never empty. Stated position: superseded records are NOT demoted in list-q. The penalty reorders a top-k; reordering a paginated, counted list would make page boundaries lie. The search surfaces carry the demotion. ## The interactive floor becomes one constant INTERACTIVE_SEARCH_THRESHOLD = 0.3 in embeddings.py, consumed by routes/search.py (was a commented constant), knowledge.py (was a bare literal), and the new list-q. This closes #2463's finding 3 early — the same number lived in two files with the reasoning attached to only one. ## Deferred, deliberately The return-shape unification (ORM objects vs dicts) stays undone. It is a 14-caller refactor whose motivation — callers being unable to swap paths — shrinks now that both paths share the clause and the meaning of q. If swap pressure recurs it deserves its own change, not a rider on an ACL fix. Refs #2462, #2463 |
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3f1523b19f |
feat(systems): read-side teeth — the vocabulary at session start, a search filter, and the state/chronicle instructions
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Step 4 of #278, product half. The audit that motivated it: one System in project 2, thirty records tagged, nothing since July 28 — three days after the feature landed. Not a discipline failure; retrieval was completely blind to the association (zero references in embeddings, knowledge, search, auto-inject, or enter_project), so tagging was a write-side label with no read-side payoff, and labels nobody reads don't get maintained. Three changes, ordered by what makes the others workable: 1. enter_project returns the project's Systems (id, name, first line of the charter). Load-bearing for the tagging instruction: you cannot ask an agent to check a record against a vocabulary it never sees. Trimmed because it rides on every session start; the full charter stays get_system's job. Present-and-empty rather than absent when a project has none — "no named areas yet" is information the create-the-System instruction acts on. 2. search accepts system_id, MCP and REST (#33). Implemented once in semantic_search_notes as an EXISTS against record_systems — an association filter deciding candidate-set membership before scoring, like project_id, not a ranking signal. The REST route's missing project filter stays #2463's: it carries a default-scope UI decision this change must not preempt. 3. The instructions (#119, _INSTRUCTIONS + using-scribe skill; plugin 0.1.25 for the cache): - Tag as you write, with an executable test — "would someone investigating that subsystem want this in the pile list_system_records returns?" — rather than "tag appropriately", which is what died. - Create the System when the area has no record: the two-or-more test snippets use, plus "don't wait to be asked to name an area that plainly exists", because the agent's default was leaving un-modelled areas un-modelled forever. - State vs chronicle: dev-logs are written once and never rewritten; durable findings live in the System's reference note, updated in place — safe because note versions are the changelog, which has existed since the feature shipped and was never named as one. list_system_records' docstring now sells it as the way to READ a subsystem, reference note first. No auto-inject boost by System — vocabulary and filter first, measure before adding ranking behaviour (the #2486 lesson). Refs #278, #2546 |
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f20c019f2a |
feat(supersession): demote what a later note overtook, and label it
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Step 3 of #278. First step with visible effect. ## Where the demotion happens, and why not in SQL Applied AFTER the pgvector fetch, over an over-fetched candidate set, not as part of the ORDER BY. Ordering by `distance + penalty` would be exact and would turn an indexed top-k into a scan-and-sort of every embedded note — the HNSW index from migration 0067 can only serve a raw-distance ordering. So the query fetches 3x the requested rows by raw distance and the re-rank happens in Python. Demoting after a LIMIT k with no over-fetch would have been theatre: the cut already happened, so a superseded record pushed down still sits in the results and the live record that should have replaced it was never fetched. The cost is stated in the code: a live record outside the over-fetch window cannot be promoted in. With a 0.05 penalty against neighbours ~0.014 apart, that needs the true answer more than three ranks down, which no observed query approaches. ## Demote, never hide — enforced in three places The penalty applies to the RANKING score, not to the relevance threshold. The floor decides whether a record is relevant at all; the penalty decides which relevant record comes first. Applying it to the floor would drop a superseded record out of the results entirely, which is the one thing this must not do. It is small on purpose. Supersession is a claim about SOME of a record's content, so one that strongly answers a question nothing else answers still surfaces — just behind anything comparable that is current. Its test asserts both bounds, the upper one citing the operator's constraint rather than an optimisation. And every test here that could be satisfied by dropping a record instead asserts the record is still present. ## The dedup gate opts out A superseded record is still a duplicate of what you are about to write — the claim is that it is no longer current, not that it is gone. Demoting it there would let the same note be recorded a second time, and the second copy would be the one nothing warns about. ## The label Auto-inject marks a superseded line SUPERSEDED with a pointer to check the later record. One query for the whole menu. An agent handed stale material with nothing marking it acts on it with full confidence, which is worse than never having surfaced it — the ranking is only half the fix. Fails open: a supersession lookup error returns unpenalised results rather than none, because unpenalised ranking is the behaviour that shipped for months and a broken search is not. Refs #278 |
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bbba0b3ae3 |
refactor(embeddings): one definition of the document a record is embedded as
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`f"{title}\n{body}"` was written out four times. #2486 found three — the write
path, the recurring-task spawn, the startup backfill. The guard added here
found the fourth immediately, and it was the one that mattered most.
`dedup.find_duplicate_note` built the same string as a QUERY, compared against
embedded documents. Shaped differently from the corpus it searches, the gate
degrades silently: it still returns neighbours, just less apt ones, and nothing
says the query and the index stopped agreeing. The spawn path has the same
shape of risk — a recurring task embedded differently from everything else is
ranked against documents it doesn't match.
None of the four had diverged. That is what makes this worth doing now rather
than after: they are identical today, so collapsing them is a no-op, and the
whole point is that the next change to the shape can't hit three of four.
Which is imminent. #2486 measured a dev-log separating from five unrelated
dev-logs by 0.023 where a snippet separates by 0.153 — the difference being
that a snippet states its purpose twice in a short document. Whether that shape
is right is the open question; testing an alternative against four copies would
mean testing a shape that isn't the one in production. This is the precondition
the issue named.
The guard is source inspection, matching the f-string pattern rather than a
variable name, so a copy that renames its locals is still caught. A behavioural
test cannot see this: an inlined copy produces the same string today and
diverges the day the shape changes.
Refs #2486
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f8522fb28f |
fix(retrieval): give reuse a slot, and let experience reach the write path
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Two mirror-image scoping mistakes, neither deliberate (#2246). AUTO-INJECT let every kind compete on raw cosine. That is fatal rather than merely imperfect here, because Scribe's project records are ABOUT software work: a task titled "surface snippets before the agent writes code" is a near-perfect lexical match for "write a function…" while answering none of it. Measured live, a prompt asking for a helper returned three records about BUILDING the retrieval system and zero snippets. Snippets are ~0.5% of the corpus, and the ratio worsens as the project record grows — which is the direction Scribe is meant to grow, so no threshold tuning fixes it. Now the best snippet or process takes the LAST slot when none won on score. Deliberately NOT held to the margin band: that band measures distance from the top overall score, and the top score is the very thing snippets lose to. It still must clear the configured threshold, so a weak snippet cannot buy the slot — silence stays the default. Skipped entirely when reuse already won, so the fix is invisible in the case it isn't needed. WRITE-PATH was snippets-only — the same mistake inverted. An issue recording "we tried this and it deadlocked" could never reach the moment that code was about to be written, though it is arguably the better prior art: it says what NOT to do. Widened to snippets plus recorded experience. That needed a filter the search layer couldn't express. "Experience" is issues plus dev-logs, which differ on is_task, so neither note_type nor is_task alone covers it. semantic_search_notes gains task_kind, which restricts TASKS to the given kinds while leaving non-task notes untouched — so note_type=("snippet", "note") + task_kind="issue" yields snippets, fixed problems and durable notes, without the open to-do list. note_type now accepts a sequence too. Non-snippet hits are labelled with their kind, because an unlabelled issue on that menu reads as "here is code to reuse", the opposite of what it says. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01UaYUaouG9jjhATyuxCKrQs |
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e0328f2b1c |
feat(plugin): write-path trigger — offer prior art before code is rewritten
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The milestone headline. Auto-inject fires on the operator's prompt; the moment reuse is actually lost is later, when the agent decides mid-task to write a helper. A PreToolUse hook on Write|Edit now fires there. Channel: `additionalContext` with NO permissionDecision, so the note reaches Claude beside the tool result and the write is never blocked — a recall aid must not be able to stop the operator's work. Plain stdout would have been invisible to the model, and deny/ask would have made a nudge into a gate. Two arms, different in kind: - BY PLACE — a snippet recorded at this path (or its directory) is prior art by definition, not resemblance, so it is neither scored nor thresholded. This is what #2083's reverse lookup was built to answer. - BY MEANING — semantic search restricted to snippets (new `note_type` filter on semantic_search_notes) over the code about to be written. Place ranks first; the top-k cap spans both arms. Gates carried over from milestone 93 verbatim: threshold, margin, session dedup, titles-never-bodies. Own `source='write_path'` in retrieval_logs so precision is tunable separately — the docstring records that the place arm is unlogged and hands that to #2085. Its own on/off in Settings but the SAME threshold/top-k: one "how loud may Scribe be" knob is easier to reason about than two that drift, and splitting them later is then a data-backed change rather than a guess. Details worth keeping: the hook sends a REPO-RELATIVE path because that is how locations are recorded; the git remote resolves to a project and is never used as the location `repo` filter (different namespaces, would silently match nothing); the endpoint stays a GET because a read-scoped API key cannot POST and every other hook depends on that. plugin.json 0.1.17 -> 0.1.18. Refs #2082, milestone #232. |
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ef1dbdfc86 |
feat(acl): unify the retrieval scopes; mark shared rows in Knowledge browse
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Closes #2092 and the Knowledge-browse provenance gap. The two halves of a hybrid search disagreed: the keyword half honoured shares while the semantic half was pinned to NoteEmbedding.user_id, so a shared record was findable by wording and invisible by meaning — the case a semantic search exists to serve. semantic_search_notes now scopes on Note via a `scope` parameter, and each of its five callers declares which kind of act it is: mcp/tools/search.py read the agent asked routes/search.py read the user typed it knowledge.py (semantic) read matches the keyword half beside it plugin_context.py browse nobody asked; never a one-to-one share dedup.py own a verdict that blocks a write must not hinge on another person's notes That last one is the reason this isn't a single global widening: the dedup gate returns "update the existing one instead", so matching a stranger's record would refuse a legitimate create and point at something the caller can't edit. Scope defaults to "own" so a caller that forgets is wrong in the safe direction, and an unknown scope raises rather than falling back — a typo there would be a data-exposure bug. Auto-inject keeps the browse scope, which still admits a collaborator's note via a shared project. Its menu line is the only provenance an agent sees, so a foreign hit now reads: #12 "Title" (0.71) - shared by alex, treat as a suggestion. MCP and REST search results carry shared/owner too. Knowledge browse: the feed hydrates cards from /api/knowledge/batch rather than the list route, so both paths label rows now, and KnowledgeView shows "by <owner>" on records the viewer doesn't own. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01RLwAaV4DQEmVyn496HnEvt |
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513019786e |
feat(search): pgvector substrate — vector(384) + HNSW for semantic search
Move semantic_search_notes off the full-table Python cosine scan onto a native pgvector column: indexed ORDER BY embedding <=> :q LIMIT k (HNSW, cosine). Migration 0067 enables the extension, converts the JSONB embedding column to vector(384) (stale-dim rows dropped and regenerated by the startup backfill), and builds the HNSW cosine index. Postgres image moves postgres:16-alpine -> pgvector/pgvector:pg17 across prod, quickstart, and CI. Scribe: project 2, milestone 93, task 1031. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Xz4j1H7pjYSjKsEpgcNH5E |
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70ab3f38c6 |
chore: remove pre-pivot dead code + finish Scribe rebrand (#599 t1-3)
- Header wordmark Fabled -> Scribe; fable:calendar-changed event -> scribe:calendar-changed; SettingsView CSS comment. - Drop dead Project.auto_summary + summary_updated_at columns (migration 0063) -- the Ollama-era summarizer is gone; model + 2 frontend types + projects test updated. - Remove pivot vestiges: diagnostics _curator_busy()/curator_busy heartbeat field, tz BRIEFING_DAY_START_HOUR/user_briefing_date dead aliases, the ignored 'model' param on get_embedding (+ its test). ruff src/ clean; CI is the gate. Part of scribe plan #599. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
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b255a0f90e |
refactor: rename package fabledassistant -> scribe (code-only)
Renames src/fabledassistant -> src/scribe and all imports, plus the default DB name and DB user/password (fabled -> scribe) in config + compose. 952 refs / 154 files. Reverses the old 'internal name stays fabledassistant' convention. Code-only: live databases are still physically named 'fabledassistant'. Deployed environments must set POSTGRES_DB / POSTGRES_USER (or rename the DB) since the defaults now resolve to 'scribe'. Repo (FabledScribe), git host (fabledsword), MCP (fabled-git) and the image name (fabledscribe) are intentionally unchanged. ruff check src/ clean locally; CI (typecheck + pytest) is the gate. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |