Two defects found reviewing the PR.
The insert ran on the turn's own context, so a caller that hung up or timed out
cancelled it. That is exactly the turn worth having. It now runs detached, with
a one-second bound of its own, because a write must not hold the reply.
Retention was enforced on write alone, so a box that goes quiet for a month kept
every row until the next sixty-fourth turn. pruneTracesOnStart closes that, and
RoutingTraceRetention is exported so the daemon reads the same number the store
enforces.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0117tgnmbgZpHVV3XSNw8Qua
internal/decision kept a 25-turn ring and persisted nothing, on the argument
that a turn record is read minutes later or never. The owner reversed that on
06-08-2026: the routing heads cannot be fitted or calibrated without real
utterances, and V-631 measured that 9 of the 31 modes have no seed example at
all. docs/plans/21-persisting-the-routing-trace.md carries the reversal, and
CLAUDE.md now says which of its own sentences stopped being true.
cmd/mavend/routingtrace.go is a second sink beside the ring, which did not move:
the ring is still what /trace reads and still what a test with no store gets. A
failed insert is logged and swallowed, because a trace must never change what he
hears. traceSink keeps a nil store out of the interface, since a typed nil
pointer there would pass the nil check and die on the first turn.
Four fields the ring never carried: which reach the turn arrived on, whether
stage 0 answered before the classifier was consulted, which encoder body was
live (the same EmbedderID string the vector marker uses), and what the action
stage actually did.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0117tgnmbgZpHVV3XSNw8Qua
The study named four live defects in the ecosystem clients and left them in a
plan doc nobody reads by default. Each is now its own task, and the doc points
at the ids so the plan and the tracker agree.
V-587 a Hexis 401 is spoken as an outage, because the vendored client returns a
plain error and unauthorizedEcosystemError's errors.As can never match it.
Worst of the four: it is the only one that makes the owner check a healthy
service.
V-588 a Praxis failure names no service. There is no servicePraxis constant and
the per-verb strings bypass ecosystemGap, so an outage and a refused token both
say "не получилось".
V-590 the Hexis discovery hop carries no correlation id. Two context keys, and
the only bridge sits inside executeCapability, which runs after discovery. The
comment above discoverCapabilities asserts the opposite.
V-591 the causation id is computed, written to Maven's own trace, and never
sent, though both the header and the request field exist.
No code changed. Verified each against the source before filing.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Two theses, tested against the code.
Thesis one, one recurring claimant shape, holds for four seams and fails for
one. The routing cascade, the query source chain, the pre-route resolver ladder
and the digestion tick are one shape. Reach selection is not: ChannelsFor is a
total pure function with no claimants and no losers, and it returns several
winners rather than one.
The digestion tick corrects the brief. loop.Tick is not a first-to-claim walk.
It already has a declared comparator, a gate with named reasons, a loser trace
with LostTo and a loser rescue path. It is the model, not a candidate.
Thesis two holds. The kernel is a package and a convention inside one program.
The framework-sized artifact is the ecosystem contract, and Maven implements its
side twice and a half: Nexus and Praxis share one embedded client, Hexis is a
vendored client in another repo with eleven divergences, four of them defects.
Abstractions: Claim, Record, Arbiter. Claim and Record already exist and neither
is wired. Drop Claimant, because every seam already rejected an interface for
the same reason.
Authorization stays out of both artifacts.
Plan 19 was already taken by 19-dialogue-arbitration.md, so this is 20.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Measures what each claimant on an utterance reports across the 91-case RU
fixture, then argues an ordinal band set from that distribution.
The classifier's cosine is flat against correctness: 62% correct below its
median and 62% above, over a spread only 0.083 wide, with every case above
the 0.55 gate. Its top-two margin is p50 0.009 and never reaches 0.03. So a
calibrated float is not cheaply available and the ledger's assumption holds.
Stage 0 is 20/20 on the cases it claims and asserts 1.0 for all of them. The
LLM router emits two values, and the lower one is a self-veto with a reason
flattened into a number.
Three durable stores said no client machine existed. That was written
when the workstation was only a model host. It is where he sits most of
the day and it has the microphone.
The verdict is unchanged and so is the seam. What changes is the size of
the remaining work: deploying two daemons and asking mavend to listen on
TCP, not acquiring hardware. Note that deploying them does not by itself
prove a wake word — mavwaked gates on energy and has no keyword model
(V-487).
His call, written down so the rig can be prepared. The question was what it
costs in GPU hours to train a small routing model. The answer is that the
question has the wrong shape: routing emits one of 7 intents, one of 5 moods and
a few spans, so it is classification, and a model that generates is being asked
to do the wrong job.
The model already exists on the box. multilingual-e5-small is 118M parameters,
trained on Russian, quantized and resident. It gets three heads on one forward
pass. Intent and mood read the mean-pooled vector, slots read
last_hidden_state as BIO tags. That is about 12k parameters of head, which is
why the serving side needs no second runtime: onnxembedder.go already pulls
last_hidden_state at [1, 128, 384] into Go and pools it there, so the heads are
three dot products over a weights file.
Cost is 10 to 30 minutes on the workstation, under 2GB of VRAM, and it also
finishes overnight on the homesrv CPU. A 100M decoder from scratch is 10 to 20
GPU hours plus a tokenizer plus a corpus, for a worse result. A LoRA on 0.6B is
1 to 4 hours and still generates, so it still needs the grammar and still has no
real confidence.
Two things this buys that no decoder can. Constrained output stops being a
grammar problem, because a softmax cannot emit a value that does not exist. And
max softmax is a calibratable confidence, where Confidence: 1.0 was a hardcode
and V-359 had to rebuild the signal out of structure.
The trap is in the plan twice because it is the one that silently costs
something. Fine-tune a COPY. The resident embedder backs memory recall at ten
points above MiniLM, and training it in place couples routing accuracy to
recall@1 with nothing in the suite to name the trade.
The real cost is the labeled set. 77 routing cases and 30 Praxis cases are a
test set. The stage 0 grammars can self-label the turn history, which distils
the rules into the model, but the fixtures stay out of training or the
measurement reads the rules and reports them as the model.
They appear in no compose file and run as no host process, and the task
asked whether that is a gap to close or a decision to write down. It is a
decision.
The reason is not hardware. homesrv is a Lenovo laptop and
/proc/asound/cards lists its ACP mic array with capture devices, so
passing /dev/snd into a container would work. It would also listen to an
empty room. A wake-word daemon is worth having where he is standing, and
that is not where the server is.
mavenclient is a client by name and design, mavwaked is the gate in
front of it, and the wire already reaches off-box: ipc.Dial takes
tcp://host:port?token=... through the netaddr seam, with the token
checked before internal/ipc sees the connection. So this needs a machine
and a config line, not protocol work.
The honest consequence is worse than the task suggested, and both docs
now say it: the wake word and the VAD gate are covered by unit tests and
by nothing else. QA session 1 step 2 was reworded to claim only what it
checks, which is push-to-talk through /dash. CLAUDE.md listed all nine
binaries with no column for where they run, which is how this went
unnoticed.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Found running QA 253 on 02-08. Every one of the four failed the same
way: the daemon is right and the step is stale.
253/3 expected mavend to boot with the capture methods unknown when
there is no media block. Validate refuses to start instead
(config.go:1651), which is the better behaviour — a capture config with
nowhere to put the audio is a mistake he should hear at boot.
253/10 expected no :transcript note by default. writeNotes writes one
whenever the summary is empty, ignoring save_transcript, so a dead
llama-server does not lose the meeting. The step was therefore false in
exactly the degradation scenario 253/16 creates. It now says "with a
summary present".
255/5 expected "speaker: enrolment on, recognition BLOCKED". That line
no longer ships. Recognizes() was written as the gate, documented as
one, and never called; calling it turned enabled-with-no-model from a
half-working capability into a refusal, and the three methods are now
absent. docs/plans/10-speaker-recognition.md described the old wiring
and is corrected here too.
252/3 quoted "vision: stored image <id-prefix>". vision.go:199 emits
"vision: stored <id>".
The steps themselves live in the Vikunja tasks and were rewritten there.
docs/qa.md records what changed and why, so the next reader does not
re-derive it from a diff.
The gap that made the steps unrunnable is V-514, not this: no shipped
client can start a recording, so 253 steps 7 to 16 stay blocked.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
The task's confirmed defect is out of date. 4e4c917 added day words and a
past-grace refusal, so "завтра в 15:00" dates correctly, and 45a5e37
(V-482, this week) fixed a zone bug the task did not know about. What is
left is explicit dates ("5 августа"), which fail safe by being dropped
rather than stored on the wrong day. The task's third question also has
an answer: both readers hedge, plan.go:174 prefixes "похоже, ".
Everything else hangs on one question that this repo cannot answer, so
the doc names it as his: can the relay app read Android's calendar
provider, or only the notification text? A NotificationListenerService
sees a title and a body and cannot know a meeting's real start, so if
that is all there is, free-text parsing here is not a choice. If it can
read CalendarContract, the parser stops being necessary and nothing is
inferred at all. Reading the phone's calendar does not break the design
constraint, which is about holding a work credential on the homelab.
Decision: keep the endpoint, make a structured event the primary shape,
keep the free-text parse as the degraded path, delete only if the relay
is not being built. And do not patch the date parser first — that is the
patch the task explicitly refuses as closure, and it is the wrong order.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
The decision the task asked for. Build it, in a smaller shape than the
task imagined, because most of it is already there: the tasks table, the
capture parse, the recite matcher and the /tasks page all landed under
#130, #129 and #128.
Three findings changed the shape.
The intake form cannot live on the voice path. resolveConfirm is a
binary yes/no slot with a 90-second life, so filling four fields is a
mechanism nobody has written, and the definition of done is the worst
possible field to dictate through whisper. It moves to the page. Voice
captures a line and recites the list; the page turns a candidate into an
open item.
The stage-0 trick stretches to recite and to status change, both of
which are a marker plus a lookup. It does not stretch to intake, and it
does not have to.
A task is write-once except for its status. SetTaskStatus is the only
mutation, so the form has nothing to save into until an edit path
exists. That is now step 2 of four, and it was not in the task text.
The argument stays unbuilt. Same line internal/memory/behavior.go
already drew for habits: she counts a stall and never assesses one.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Seventeen markdown files at the repo root, twelve of them dated one-shot
reports sitting next to CLAUDE.md. That is why stale docs read as
current: nothing in the path said which was which.
Root now keeps CLAUDE.md and AGENTS.md. Living docs move under docs/
and carry a Last verified line. Dated measurements move to docs/evals/
ISO-prefixed, and are never edited after the day, so a newer number is
a new file. The senior review moves to docs/archive/.
Every reference was rewritten across markdown, Go comments, the Makefile
and the recall fixture. The touched Go packages still build.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Maven can now be told who someone is. She cannot yet tell who is speaking,
and this commit is careful to say so rather than pretend otherwise.
What works: profiles are enrolled from several deliberately recorded samples,
listed, and deleted. They live in the existing memory_vectors table under a
"speaker:" id prefix, so there is no migration; what that needed was a wider
interface than memory.Store, hence memory.Catalog with ByPrefix and Delete.
Delete is the load-bearing half — a voiceprint someone asked to be rid of has
to actually go, and a search-only store cannot do that. InMemoryStore.Insert
became an upsert by id to match what the persistent store already did.
What does not work, and why it is not faked: there is no speaker-embedding
model on this box. Sixteen ggufs in /mnt/hdd1/llms, all text; no ECAPA, no
x-vector, no titanet, no wespeaker, no .onnx anywhere under /mnt/hdd1. So
newSpeakerEmbedder returns nil, internal/speaker falls back to
speaker.Disabled, Identify answers ErrDisabled, and the daemon logs which
half is off at startup. The plan's "simple MFCC + GMM" floor is refused in
the package comment: MFCC cosine distance detects channel and loudness as
much as voice, and a biometric that is confidently wrong writes false claims
about named people into his memory. A bad floor is worse than none here.
Refused as well, and the reason is in enroll.go's doc comment: the plan asked
for unknown speakers to be enrolled on first interaction with a TTS "кто
это?". There is no request shape in the protocol that could express that.
Taking a biometric of whoever walks past the microphone does it to guests who
are not party to the exchange, and a synthesised question into a room is not
consent from whoever answers.
Authority: enrolment is AuthStepUp, because it is a deliberate sit-down act
that writes a biometric of a named person and never something done by voice
mid-conversation. Deletion is one rung lower at AuthWrite, deliberately
inverting the usual pattern — getting rid of a biometric must never be the
harder half. Listing is AuthRead and never returns the vectors themselves.
Off unless configured: no speaker block means the three methods answer
ErrUnknownMethod, so a default box has no wire path that takes a voiceprint.
make build and make test pass.
Vikunja #255
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01TrVSBKe3RFDF4fGYKWYQnX
Maven can record a meeting when she is told to, transcribe it through the
STT she already has, and write a summary note. The audio lives in the blob
store #252 introduced, under the same retention loop.
Nothing here listens. Recorder.Append is the only way audio enters and it
refuses every frame unless someone explicitly started a session, so audio
arriving at an idle core is dropped rather than buffered. The plan document
asked for a keyword trigger ("maven record" heard in the room) and that is
refused: noticing a keyword means listening to the room, which is the one
behaviour this capability must not have.
Off unless configured twice over. No media block means nowhere to keep
audio, no capture block means no recorder, and in either case the four IPC
methods answer ErrUnknownMethod. On an unconfigured box there is no wire
path that begins a recording at all.
A forgotten session ends itself at max_minutes, checked on every append,
and the audio collected before the cap is kept. Stop with discard set is
what "забудь, не записывай" maps to and it leaves nothing behind. The
verbatim transcript is not saved unless save_transcript says so; the
summary is.
Long audio against n_ctx 4096 is handled by map-reduce over 3000-rune
windows rather than by truncation, because a truncated meeting summary
reads as complete and is not. Transcription is windowed at five minutes so
the whisper worker stays responsive to the voice path.
No second STT: internal/capture takes the stt.Transcriber the voice path
already holds. Capture with voice off is refused rather than degraded,
since hours of unreadable audio of other people is worse than no recording.
The three write methods are AuthWrite, not AuthStepUp: step-up needs a
passkey gesture the voice path cannot make, which would leave "запиши
встречу" impossible by voice. capture_status is AuthRead.
make build and make test both pass.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01TrVSBKe3RFDF4fGYKWYQnX
Vision needs a second model this box does not have, so the shipped half is
the part that works without one: an image arrives, is sniffed, is stored
content-addressed, and is prepared for inference. The describing half is
written and tested against a fake server, and refuses any endpoint that is
not on this box.
internal/media is the intake all three senses share — hearing and speaker
recognition store their audio in the same place under the same retention.
Blobs stay out of the sqlite store; only the derived text becomes a note,
and only when the caller asks. Retention is enforced by an hourly prune
loop rather than by a comment.
The plan's RemoteProvider step is refused: no cloud model, inference stays
on the box, and vision.NewLocal validates that at construction.
The network fallback behind the local sources, off unless configured.
internal/crawl is pure: a stdlib robots.txt parser (group specificity,
wildcards, Crawl-delay, cached per host), HTML-to-plaintext extraction, and a
watcher that notes a watched page only when its text changed. It has no store
access and no net/http; cmd/mavend/crawls.go is the impure half.
Every limit is code and tested: the guarded fetcher from #258 enforces the host
allowlist/denylist, refuses private addresses in the dialer Control hook (so DNS
rebinding and each redirect hop are covered), caps size and redirects, times out,
and spaces requests per host. A robots.txt Disallow is refused with no override.
On demand, reading is a query source placed last in the chain, after his memory,
his notes, and the local Kiwix ZIMs once those are wired: no URL in the
utterance means no fetch, and only the URL ever leaves the box. Scheduled
watches write notes and announce nothing.
The vendored tree has no x/net/html, goquery or temoto/robotstxt, so the parsers
are stdlib. No new dependency.
internal/rss parses RSS 2.0 and Atom, and polls each configured feed on its own
interval; internal/webfetch is the one door either of them uses to touch the
network. The poller writes items as notes with source "rss:<feed>" and nothing
else: the answer path reads them back when he asks "что нового в лентах?", and
nothing is announced on arrival. A feed that dispatched would be a nag, which is
why the plan's breaking-news rule was left out rather than built.
webfetch is where the limits live, as code rather than a paragraph: http(s)
only, an allowlist (the configured feeds' hosts) and a denylist, a 2 MiB body
cap, a 3-redirect cap, one request per host per second, and a refusal to connect
to any private address — checked in the dialer's Control hook so it holds for
every resolved address and every redirect hop, not just for a literal IP.
Off unless configured: no "feeds" block, no poller, no outbound request. How far
a feed was read is a config fact (rss:latest:<name>), so a restart does not
re-note yesterday's headlines.
Behavioural memory, narrowed on purpose. internal/memory/behavior.go builds a
profile out of self-facts — distinct days per weekday, median time of day — and
reads it back in RU; router.ParseHabitQuery finds the weekday deterministically;
a `habits` query source answers the question.
Three things the plan doc asks for are deliberately absent, and the doc now
records why:
- The profile is COUNTED, not LLM-generated. A 1.7B asked to summarise a year of
habits writes fluent claims about the owner's life that no row supports, and a
wrong claim about him is the most expensive kind of wrong maven can be.
- No cached profile fact, so no "update on fact write" machinery. It is
recomputed on the question; a cache that can disagree with its own rows is two
truths.
- No proactive daily plan nudge. A dispatcher proposal at 08:00 every day is the
definition of a nag. The path from "she noticed a pattern" to "she acts on it"
already exists in internal/pattern with the proposal queue on /routines, and it
goes through him.
A one-off is not a habit: an activity needs two distinct days before she will
call it usual, and until then she says she does not know yet. Only self-facts
count — env rows are the world, config rows are her own tuning state. The typical
time is a median so one 03:00 outlier cannot move a morning habit into the night.
An unrecognised fact key is read back verbatim rather than glossed into something
she made up.
The source sits before "calendar" in querySources, and its matcher requires a
habit marker, so "что я делаю в среду?" still reaches the calendar — answering a
question about this coming Wednesday with a statistical average would be
answering a different question.
Verified: make build and make test both exit 0.
Ships the real, local, testable part of the memory-evaluation plan
(docs/plans/03-memory-evaluation.md): Maven reads back her own recent
memory on a slow ticker, asks the resident model what it notices, and
records the confident answers as notes.
internal/memeval — not internal/memory/eval.go as the plan says, because
internal/store imports internal/memory for the vector backend and an
evaluator has to read store.Fact/Note/Nudge, which would close the
cycle. Evaluate() gathers RecentFacts/RecentNotes/RecentNudges, prompts
under a GBNF grammar bounded to three {observation, confidence,
suggested_action} objects, drops anything under min_confidence,
deduplicates against what earlier runs wrote, and writes the rest as
notes with source infer:memory-eval. /dash already renders notes with
their source, so the output is visible with no UI change.
cmd/mavend/memoryeval.go drives it on its own goroutine and ticker, not
on the 60s tick: an evaluation is a multi-second round-trip on the same
llama-server that answers voice turns, and it runs hourly at most. The
memory_eval config block is absent by default and absence means the
goroutine does not exist. No llama-server phraser also means no loop —
there is no template fallback, because a "memory evaluation" assembled
from templates is a fixed sentence pretending to be an observation.
What it deliberately cannot do, since this is the feature most likely to
turn Maven into a nag:
- It cannot speak. No dispatcher reference, no channel, no nudge. An
observation is a thought she wrote down and he reads on /dash.
Announcing them is a separate decision with its own opt-in.
- It cannot act. suggested_action is recorded as text and interpreted
by nobody — no reminder, routine or fact is created from it.
- It says nothing about an empty store: no memory means no LLM call,
so there are no observations invented out of two facts.
- Its own notes are excluded from the next evaluation's input, and are
written with a nil embedding so they stay out of the recall pool.
The plan's remaining items (dispatching observations, an /eval IPC
method and trace view, RecentEvents) and the fact that output quality is
entirely unmeasured are written up at the bottom of the plan doc.
Add a read-only /ecosystem page that consumes the sibling services'
JSON APIs (Nexus entities, Praxis attention, Hexis capabilities),
fetched concurrently with honest per-panel error states. Siblings stay
headless — mavweb is their human surface (arch §16). Wired via mavweb
-nexus/-praxis/-hexis flags; mavweb joins the ecosystem compose network.
Fix mobile horizontal overflow across all pages: .content is a flex
child with default min-width:auto, so it refused to shrink below the
tables' intrinsic width. min-width:0 lets wide tables pan inside .scroll
instead of dragging the page sideways. Verified via CDP geometry check
(scrollWidth === clientWidth at 430px).
Also includes in-progress Ethos UI redesign, ecosystem deploy compose,
and planning docs.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Route contract is now a JSON array of action objects (one per ask) so
compound utterances route all their intents, not just the first. Grammar
root emits `[{intent...},...]`; parseActions tolerates a bare object.
Cascade still returns one Decision — full N-action dispatch lands with the
engine turn-on (marked in-code).
Router prompt rewritten shorter + decision-ordered (prompt-guy feedback),
fact redefined as "implicit update" not "trackable state", kept in Russian
to match the CPT base + phraser. "интент" → "намерение".
CLAUDE.md: routing-architecture section + refreshed open items.
docs/plans: route-data generation plan.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_017GMrVfuYN3nE4L1vEiFYC9
Daemon side of Decision B: parse {"response","mood"} across the 4 consumers
(replier, nudges, reminders, chat), fall back to legacy formats. Drop the
LLM router — the classifier handles routing; replier/phraser share one
llm.Client (timeout 20s->60s). llm.Client reads reasoning_content when
content is empty (thinking models).
Docs: TTS piper-student plan (OmniVoice teacher -> piper student, from
scratch, phoneme-first). CLAUDE.md training guide.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
- Add reactive_notes_test.go: tests for context-aware reactive nudge
generation using LLM phraser with dialogue history.
- Add docs/plans/2026-07-10-router-lfm-foundation.md: architecture research
on replacing classifier cascade with LFM-based router.
claude
kami