Stop the docs claiming the LLM router is off

CLAUDE.md's routing section said "llmrouter is wired nil" and called the
classifier cascade the committed default. That stopped being true when the
integration merge landed: voice.go:214 wires pickLLMRouter, DefaultLLMRouter is
on, and deploy/mavend.json sets llm_router true. It is the first thing anyone
reads before touching the router, so it was pointing the next reader at a
wiring job that is already done.

Rewritten to say the LLM router is the default, the classifier is the failure
floor and must not be deleted, and what the two actually measure — 36.8% at
p50 31ms against 67.5%/72.7% at p50 ~2.7s, a trade accepted on purpose. Names
the one thing still open on that path: Confidence is hardcoded 1.0 in
llmrouter.go, so the LLM never asks for clarification (#359).

Also in CLAUDE.md: the persona line pointed at a memory file that does not
exist, so the actual rule was nowhere in the repo. Written out instead —
feminine self-reference, informal singular address, pet names forbidden but his
name allowed — plus the three eval checks that enforce it.

MODEL-BAKEOFF: three claims had gone stale within hours of being written. There
IS a make eval-models target now; the routing numbers ARE the production path,
not a bench artifact waiting on a wiring change; and the truncated 293 MB gguf
is deleted. Struck through rather than removed, since the caveats are part of
how the evening read at the time.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CGeSZxh1DCtRxmFVSYVGvJ

CLAUDE.md

@@ -7,9 +7,20 @@ talking over unix sockets; one resident small model for routing + phrasing; whis
 Deploy target is a Ryzen laptop (homesrv) with Vulkan offload to the Vega iGPU (`n_gpu_layers: 99`,
 compose passes `/dev/dri` + the render gid) — the resident model stays ≤1.7B either way.
 
-**Resident model:** currently **Qwen3.5-0.8B** (`Q4_K_M`), the smallest checkpoint in the gguf
-library, picked for CPU/iGPU latency. The **target** is the locally CPT'd **Qwen3-1.7B**; that
-training is still in flight (Vikunja #122), so no such gguf exists yet. Model files live in
+**Resident model:** currently **Qwen3-1.7B** (`UD-Q4_K_XL`), stock — not yet the CPT'd one.
+It replaced Qwen3.5-0.8B on 2026-07-31 because it measured better on both fixtures we have:
+67.5% vs 59.7% intent-only on the 77-case RU routing fixture, and 20/27 vs 11-17/27 on the
+talk fixture. See `MODEL-BAKEOFF-31-07-2026.md`. It is a Thinking variant, so `n_ctx` is 4096
+— reasoning tokens need the room, and 4096 is what the scores above were measured at.
+
+The **target** is still the locally CPT'd **Qwen3-1.7B** (Vikunja #122, training in flight).
+Stock already speaks good Russian; what it gets wrong is the persona — it writes `я рад`,
+masculine, where Maven needs `рада`. That is what the CPT is for.
+
+**Do not bother with sub-500M models.** LFM2.5-230M and 350M were measured on 2026-07-31 and
+both are unusable in Russian: the 350M routes at 5.2% (worse than guessing) and answers
+"столица Франции?" with the invented non-word "Сторзит"; the 230M replies to Russian in
+Spanish. Their strong published IFEval/BFCL numbers are English-only. Model files live in
 `/mnt/hdd1/llms`, bind-mounted to `/opt/maven/models/llm` — which **shadows** the repo's
 `models/llm/`, so the LFM2.5 gguf sitting there is not loaded by anything. Swapping the resident
 model is a one-line change to `phraser.model_path` in `deploy/mavend.json`.
@@ -58,19 +69,30 @@ protocol; the config in `deploy/mavend.json` (with `${VAR}` env expansion from g
 
 ## Routing — read this before touching the router
 
-`internal/router/` has TWO layered engines and the committed default is an **interim
-stopgap, not the intended design** (see memory `routing-architecture-target`):
+`internal/router/` has TWO layered engines. **The LLM router is now the default and it is
+on in deploy** — this section used to say it was wired `nil`, which stopped being true on
+2026-07-31.
 
-- **Target (REARCH.md):** LLM-as-router. One resident Qwen3-1.7B (`llmrouter.go`) emits
-  GBNF-constrained structured JSON, and the SAME model phrases replies. Embedder is demoted
-  from a routing gate to a RAG hint.
-- **Current stopgap:** `llmrouter` is wired `nil` (around `voice.go`), so the
-  `classifier.go` + `embedder.go` nearest-neighbour cascade actually runs. It routes by
-  similarity to frozen seed phrases — the known cause of weak RU query handling.
+- **LLM router (the intended design, REARCH.md):** the resident Qwen3-1.7B (`llmrouter.go`)
+  emits GBNF-constrained structured JSON, and the SAME model phrases replies. Embedder is
+  demoted from a routing gate to a RAG hint. Wired at `voice.go:214` via
+  `pickLLMRouter(cfg.Voice.UseLLMRouter(), llmClient)`; the flag is `voice.llm_router`
+  (`config.go`), `DefaultLLMRouter` is **on**, and `deploy/mavend.json` sets it `true`.
+- **Classifier cascade (the failure floor, not dead code):** `classifier.go` +
+  `embedder.go` nearest-neighbour over frozen seed phrases. It runs when the LLM router is
+  off, when there is no llama-server to talk to (`pickLLMRouter` logs that and degrades),
+  and on any per-turn LLM error. Do not delete it — routing by seed similarity is the known
+  cause of weak RU query handling, but a turn must never break on the model.
 
 Cascade order: `stage0.go` exact-match fast-path → LLM router (when non-nil) → classifier
 fallback. Any LLM error falls through to the classifier so a turn never breaks on the model.
 
+Measured on the 77-case RU fixture (`MODEL-BAKEOFF-31-07-2026.md`): the classifier scores
+36.8% full accuracy at p50 31ms; Qwen3-1.7B scores 67.5% intent-only / 72.7% through the
+cascade at p50 ≈2.7s. Accuracy roughly doubled, latency is ~90× worse, and that trade was
+accepted deliberately. Still open: `Confidence: 1.0` is hardcoded in `llmrouter.go`, so the
+LLM path never asks for clarification (6/6 refusal cases missed) — Vikunja #359.
+
 ## LLM output contract
 
 All phrasing paths emit `{"response":"...","mood":"..."}` (parsed in `replier_llm.go` and
@@ -83,7 +105,11 @@ workspace enforces that the Go and relabelling prompts remain identical.
 ## Non-goals (hard constraints)
 
 Not a nag, not autonomous. Maven's persona is **feminine** — Russian
-self-reference must use feminine forms (the user is male; see memory `maven-persona-gender`).
+self-reference must use feminine forms — `рада`, not `рад`; `поняла`, not `понял`. The owner
+is male and is addressed informally: "ты", singular, never "вы"/"ваш" and never "он"/"его"
+(she talks TO him, not about him). Pet names ("милый", "дорогой") are forbidden; his name
+("Ками") is not. The eval enforces this: `CheckAddress`, `CheckFeminine` and `CheckCringe` in
+`internal/phraser/eval/checks.go`, scored by `make eval-phrasing`.
 
 **"Never phones home" is DEPRECATED** (owner's call, 2026-07-31). It used to be a hard
 constraint and it is not one any more: a 0.8B — and a 1.7B — does not know enough to answer

MODEL-BAKEOFF-31-07-2026.md

@@ -1,15 +1,28 @@
 # Resident model bake-off — 31-07-2026
 
-**Recommendation: keep Qwen3.5-0.8B.** LFM2.5-1.2B is worse at routing (52.6% vs 60.5%
-intent accuracy), and the loss is almost entirely Russian (18/61 vs 22/61 RU, while EN is a
-wash). It is also 2.4× slower. The Thinking variant is far worse again.
+**Outcome: the resident model is stock Qwen3-1.7B** (`UD-Q4_K_XL`). Two sweeps ran this
+evening and the second one changed the answer — read to the end before acting on any table
+here. [Second sweep](#second-sweep-same-evening--five-models-and-a-resident-model-change)
+is the one that holds.
+
+## First sweep — LFM2.5-1.2B vs Qwen3.5-0.8B
+
+**Verdict, scoped to this pair: keep Qwen3.5-0.8B over LFM2.5-1.2B.** LFM2.5-1.2B is worse
+at routing (52.6% vs 60.5% intent accuracy), and the loss is almost entirely Russian
+(18/61 vs 22/61 RU, while EN is a wash). It is also 2.4× slower. The Thinking variant is
+far worse again. This verdict still stands as written — it rejects LFM2.5-1.2B. It is
+**not** a recommendation to keep 0.8B as the resident model; the second sweep replaced it
+with Qwen3-1.7B.
 
 Settles Vikunja **#278 / #250**.
 
 - Same fixture and scorer as `ROUTING-EVAL-31-07-2026.md`: `internal/router/eval/`
   (`ru_routing_v1.json`, 76 held-out cases).
 - Reproduce: `MAVEN_LLM_URL=http://127.0.0.1:<port> make eval-router`
-  (`TestLLMRouterBaseline`). Note: there is no `make eval-models` target.
+  (`TestLLMRouterBaseline`). (This line used to say there is no `make eval-models` target.
+  There is one now — start a server with the gguf you want, then
+  `make eval-models MAVEN_LLM_URL=http://127.0.0.1:<port>`. It runs only the LLM test, since
+  the classifier baselines do not depend on the model.)
 - All three models served by the same `llama-server` flags — `-c 2048 -ngl 99 -t 6`, only
   `-m` and `--port` differ. One server at a time on an otherwise idle box, so latencies are
   real and not contention.
@@ -99,3 +112,112 @@ thinking trace costs time without buying accuracy on a short enum classification
 Routing only. LFM2.5 might still phrase better, and phrasing is the resident model's other
 job — that needs its own fixture. But routing is the load-bearing path and Maven is
 Russian-first, so on the evidence here the switch is not worth making.
+
+---
+
+# Second sweep, same evening — five models, and a resident-model change
+
+The sections above compared LFM2.5-1.2B against Qwen3.5-0.8B on routing and concluded
+"the switch is not worth making". That still holds. This sweep asked a different
+question — whether a *smaller* model could work, since LFM2.5's published
+instruction-following scores beat Qwen3.5-0.8B badly — and answered it, plus found a
+better resident model by accident.
+
+**Outcome: the resident model is now stock Qwen3-1.7B.** Sub-500M is a dead end.
+
+## Routing — 77 Russian cases, one run each
+
+| model | on disk | llm-only (full) | llm-only (intent) | cascade + fallback |
+|---|---|---|---|---|
+| LFM2.5-230M-Q8_0 | 246 MB | 23.4% | 33.8% | 36.4% |
+| LFM2.5-350M-Q8_0 | 379 MB | 2.6% | **5.2%** | 20.8% |
+| Qwen3.5-0.8B-Q4_K_M | 527 MB | 36.4% | 59.7% | 61.0% |
+| Qwen3.5-2B-UD-Q4_K_XL | 1.34 GB | 42.9% | 62.3% | 63.6% |
+| **Qwen3-1.7B-UD-Q4_K_XL (stock)** | 1.13 GB | **44.2%** | **67.5%** | **72.7%** |
+
+Qwen3-1.7B wins every column, including against a model 20% larger than it.
+
+## Talk fixture — 27 cases, three runs each, idle box
+
+| | Qwen3.5-0.8B | Qwen3-1.7B stock |
+|---|---|---|
+| composite | 13, 11, 8 | **20, 21, 18** |
+| address | 21, 18, 18 | **26, 25, 23** |
+| feminine | 27, 25, 26 | 26, 27, 26 |
+| lang | 27, 27, 26 | 26, 27, 27 |
+| ontopic | 16, 19, 19 | **22, 23, 23** |
+| canned fallbacks | 8, 5, 6 | **0, 2, 0** |
+
+This also fills the row `TALK-EVAL-31-07-2026.md` had to void for contamination:
+**600ch/1024tok on Qwen3.5-0.8B scores 13, 11, 8.**
+
+`address` is the headline. It sat at 18-22 of 27 on the 0.8B no matter how the prompt
+was worded — the prompt explicitly forbids "вы" and the model writes `вашей`,
+`подождите`, `делаете` anyway. That was read as "prompting is out of levers", and it
+was really "0.8B is out of capacity". The 1.7B mostly holds the constraint.
+
+The fallback column matters too: 5-8 of 27 turns on the 0.8B end in a hardcoded
+`"не знаю."`, meaning it failed to emit parseable JSON about a quarter of the time.
+The 1.7B does that 0-2 times.
+
+## Latency — the long tail is not the Thinking block
+
+| | p50 | p95 |
+|---|---|---|
+| Qwen3.5-0.8B | 2.4s, 2.9s, 2.0s | 17.4s, 17.6s, 17.4s |
+| Qwen3-1.7B stock | 2.7s, 2.6s, 2.8s | 16.4s, 6.6s, 3.9s |
+
+p50 is flat across a 2× size difference. The first instinct on seeing the 1.7B's
+16s p95 was "that is the reasoning trace, cap it" — wrong. The 0.8B's p95 is a
+consistent 17s and the 1.7B beat it in two of three runs. The tail is shared and
+lives somewhere else. Do not spend time on `/no_think` on this evidence.
+
+## Sub-500M: not close, and the benchmarks say otherwise for a reason
+
+LFM2.5-350M publishes IFEval 76.96 against Qwen3.5-0.8B's 59.94, and BFCLv3 44.11
+against 35.08 — better at instruction-following and structured output, at 2/3 the
+size. Those numbers are real and they are **English**. Every benchmark in that
+table except Multi-IF is English-only.
+
+In Russian, with a 300-token budget and temperature 0:
+
+- **350M**, «Столица Франции? Ответь кратко.» → *«Сторзит в Париже.»* — `Сторзит` is
+  not a word; it is invented morphology.
+- **350M**, asked to read back a reminder → a fortune cookie about being attentive
+  and confident. No reminder in it.
+- **230M**, «Привет, как дела?» → answered **in Spanish**.
+
+The 230M beating the 350M six-fold on routing (33.8% vs 5.2%) is the other tell:
+when the larger sibling collapses like that it is format compliance failing, not
+reasoning.
+
+This is a pretraining gap, not a fine-tuning gap. Teaching Russian to a 350M from
+near-zero is not an afternoon on a Colab, which was the premise worth checking.
+
+## Why this vindicates the 1.7B CPT
+
+Stock Qwen3-1.7B, untrained and unprompted, answers all three probes in fluent
+correct Russian. What it gets wrong is the persona: *«Привет! Я рад, что ты здесь»*
+— `рад` is masculine and Maven needs `рада`. That is the right kind of remaining
+problem, and it is exactly what the CPT (Vikunja #122) is for.
+
+The 1.7B was the correct model choice. What was wrong was treating it as a
+**blocker**: stock already beats what was deployed, so it ships now and gets
+swapped again when the CPT lands.
+
+## Caveats
+
+- Routing is one run per model, not three. The gaps between families are far larger
+  than the run-to-run spread seen on the talk fixture, but the 2B-vs-1.7B gap (62.3
+  vs 67.5) is not safe to call on one run.
+- ~~The routing numbers only reach production once the LLM router is wired on. It is
+  still `nil`.~~ **Resolved the same evening:** the LLM router is wired at `voice.go:214`
+  behind `voice.llm_router`, the default is on, and `deploy/mavend.json` sets it `true`.
+  These numbers are the production path now, so the p50 ≈2.7s is a real per-turn cost and
+  not a bench artifact.
+- ~~`/mnt/hdd1/llms/LFM2.5/Qwen3-1.7B-UD-Q4_K_XL.gguf` is a 293 MB truncated download
+  in the wrong directory.~~ **Deleted 2026-07-31.** The good 1.13 GB copy in `qwen3/` is
+  what `deploy/mavend.json` loads.
+- Harness: `scratchpad/bakeoff.sh`, one server at a time, health-checked before each
+  run, `/v1/models` recorded per run. Never run two LLM consumers at once — see the
+  contamination note in `TALK-EVAL-31-07-2026.md`.

TALK-EVAL-31-07-2026.md

@@ -0,0 +1,150 @@
+# Conversational phrasing eval — 31-07-2026
+
+Every score measured tonight, on the three paths the nudge eval never touched:
+chat, query-with-notes, and general knowledge.
+
+**Short version: the plumbing got fixed and the score barely moved.** Grammar and
+Russian prompts together took the composite from ~9 to ~14 of 27. Everything
+still failing is the model not knowing things or not holding a constraint, and
+prompting is out of levers. Settles the measurement half of Vikunja #395 / #398 /
+#400.
+
+## How to reproduce
+
+```sh
+# llama-server: -c 4096 -ngl 99 -t 6, model /mnt/hdd1/llms/qwen3.5/Qwen3.5-0.8B.Q4_K_M.gguf
+MAVEN_LLM_URL=http://127.0.0.1:18099 no_proxy=127.0.0.1,localhost \
+  deps/go/go/bin/go test -count=1 -timeout 40m \
+  -run TestLLMTalkBaseline ./internal/phraser/eval/ -v
+```
+
+Three runs per configuration, always. The fixture is 27 cases, so one reply
+changing moves the composite by 3.7 points — a single run cannot tell a real
+change from sampling noise. This was learned the expensive way: an earlier claim
+that "one nudge case fails every run" turned out to be three different cases
+across three runs.
+
+**Run the box otherwise idle.** See the contamination note at the bottom.
+
+## Composite, per configuration
+
+| config | overall /27 | chat /9 | query /9 | knowledge /9 | canned fallbacks |
+|---|---|---|---|---|---|
+| baseline, no grammar | 7, 12, 7 | 1, 1, 0 | 2, 4, 2 | 4, 7, 5 | 0, 0, 0 |
+| + GBNF grammar (#398) | 14, 15, 8 | 1, 3, 0 | 5, 6, 3 | 8, 6, 5 | 0, 0, 0 |
+| + Russian prompts (#400) | 11, 17, 15 | 1, 5, 3 | 5, 6, 8 | 5, 6, 4 | 0, 0, 0 |
+| + truncation fix, 1000ch/768tok | 12, 13, 10 | 2, 2, 1 | 7, 7, 5 | 3, 4, 4 | 3, 3, 6 |
+| + rebalanced, 600ch/1024tok | **void — contaminated** | | | | |
+
+"Canned fallbacks" counts replies that came back as the hardcoded `"не знаю."`
+or `"поговорили."`. It is not a check, it is a health signal: those strings mean
+the phraser gave up, and the eval scores them as ordinary bad replies.
+
+## Per-check
+
+| check | no grammar | + grammar | + RU prompts | + truncation fix |
+|---|---|---|---|---|
+| nonempty | 27, 27, 27 | 27, 27, 27 | 27, 27, 27 | 27, 27, 27 |
+| ellipsis | 20, 19, 23 | 27, 27, 27 | 27, 27, 27 | 27, 27, 27 |
+| lang | 13, 16, 15 | 23, 26, 26 | 25, 26, 25 | 26, 27, 27 |
+| feminine | — | — | 25, 24, 26 | 25, 25, 27 |
+| address | — | — | 21, 22, 22 | 22, 21, 22 |
+| ontopic | — | — | 17, 24, 18 | 17, 19, 14 |
+
+`nonempty` reading 27/27 everywhere is not good news — it was a broken check.
+It tested for a non-blank string, so replies of literally `{` and `"15-16"`
+passed it. Fixed on `overnight/fix-truncation`; it needs a letter now.
+
+## What each change actually bought
+
+**GBNF grammar (#398) — the biggest single win.** Qwen3.5-0.8B writes
+`Thinking Process:` as plain text with no tags, `stripThink` only handles
+`</think>`, so the JSON never closed and the plain-text fallback shipped the
+literal reasoning. `ellipsis` went 20→27 and `lang` 13→26. The router had been
+using a grammar for ages; the phraser asking nicely in the prompt was the
+oversight.
+
+**Russian prompts (#400) — modest, plus a large latency win.** Chat 1.3→3.0
+average, query 4.7→6.3, knowledge 6.3→5.0. All inside the run-to-run spread, so
+"probably better on the paths it targeted, not provable in three runs". p50
+latency dropped from ~11.5s to ~2.3s and that part is consistent across all
+three runs — shorter prompts, and she stopped emitting English reasoning first.
+
+**Truncation fix — necessary, and did not help the score.** Two real bugs
+(replies of `{`, and a `nonempty` check that passed them), both fixed, and the
+composite went nowhere. A complete rambling wrong answer fails the same checks a
+truncated one did. Worth doing anyway: the daemon was shipping `{` to a
+text-to-speech voice.
+
+## The truncation bug, since the cause was counter-intuitive
+
+The grammar's `string ::= ... {0,400}` rule was the cause, not the token cap.
+Measured against Qwen3.5-0.8B at three caps — 256, 768 and 2048 — the reply came
+back **exactly 400 characters every time, cut mid-word** (`"Нужно записать и,"`).
+
+Then I raised the bound to 1000 while the cap was 768 tokens and made it worse:
+Russian runs ~1.5 characters per token here, so generation died on the *token*
+cap instead, mid-object, and the new guard correctly refused it and shipped
+`"не знаю."` — 3, 3 and 6 fallbacks per run, from zero. **The two limits have to
+agree.** 600 characters needs ~400 tokens; the cap is 1024.
+
+## Where the remaining failures live
+
+`address` is stuck at 21-22 of 27 and `ontopic` at 14-19. Both resist prompting.
+
+**The prompt now explicitly forbids exactly what she does.** It says never "вы",
+use the singular — and she writes `вашей`, `подождите`, `делаете`, `хотите`,
+`напишите`. Telling a 0.8B "never do X" does not work. Same for
+`feminine`: `я готов`, `я понял`, `я нашел`, `я заметил`, `я сказал`.
+
+**Some of `ontopic` is the fixture, not the model.** `chat-how-are-you` got
+`"Привет! Я здесь, чтобы поговорить. Как дела сегодня?"` — a fine reply that
+fails because `want_any` is `[норм, хорош, порядк, тут, работ]`. It fails in
+every run, so it inflates the count. The `ontopic` column currently measures the
+fixture as much as the model. Not fixed yet, deliberately: changing it would
+break comparability with the runs above.
+
+**Two replies worth reading, because they are not fixable by prompting:**
+
+- Thunder and lightning: *"Скорость молнии — 8-10 тысяч километров в секунду, но
+  звук — 300 метров в секунду, что делает молнию громче."* Confidently wrong,
+  and it concludes lightning is *louder* rather than sound being *slower*.
+- "расскажи обо мне": *"Ты — прекрасное существо, с душой и вниманием… Спасибо за
+  твою улыбку… О тебе — заповедь любви."* Sycophantic filler, zero information,
+  and precisely the "not a relationship" non-goal.
+- Boiling an egg: `"15-16"` one run, `"1"` another. No unit, wrong number.
+
+The first argues for reading instead of recalling (#403 — Kiwix retrieval scores
+8/8 on the same questions given English keywords). The second and third argue
+for templates on the paths where correctness matters (#392).
+
+## Contamination note — how the last row got voided
+
+I started the query-rewrite agent against the same llama-server the sweep was
+using, and assumed contention would only affect latency. It did not. The
+knowledge path collapsed to 0 of 9 with eight canned `"не знаю."` replies, p95
+tripled to 23.7s, and **the report still said "0 errors"**.
+
+That is Vikunja #397, and it is worse than filed: a merely *busy* server
+produces a clean-looking report with a third of the fixture silently answering
+`"не знаю."`. `PhraseChat` and `PhraseQuery` swallow every failure and return a
+hardcoded string, so infrastructure trouble is indistinguishable from bad
+phrasing in the score. The talk test guards the *start* and *end* of a run with
+a model check, which catches a dead server but not a loaded one.
+
+**Until #397 is fixed, treat any run made on a busy box as void.**
+
+## Next
+
+- Re-run 600ch/1024tok clean, to fill the void row.
+- Score `Qwen3.5-2B-UD-Q4_K_XL` (already at `/mnt/hdd1/llms/qwen3.5/`, never
+  measured) on this fixture and the router fixture. Not the 4B — too big for
+  this box, owner's call.
+- Newer sub-500M candidates (LFM2.5 200M/300M) are worth a run for routing.
+  Note `MODEL-BAKEOFF-31-07-2026.md` found LFM2.5-**1.2B** worse than
+  Qwen3.5-0.8B at Russian routing and 2.4× slower — but those are a different,
+  older generation, so that result does not predict the small ones.
+- Fix `chat-how-are-you`'s `want_any`, and re-baseline once, so `ontopic`
+  measures the model.
+- #397 first if anything, since it decides whether any of the above is
+  trustworthy.

cmd/mavend/clarify.go

@@ -3,6 +3,8 @@ package main
 import (
 	"context"
 	"log"
+	"math/rand"
+	"strings"
 	"time"
 
 	"github.com/kami/maven/internal/dialogue"
@@ -21,8 +23,12 @@ const clarifyTTL = 90 * time.Second
 // raw utterance, chat and system have nothing to fill in. For those a clarify
 // decision keeps the canned "не поняла" reply — inventing a question for noise
 // is worse than admitting she missed it.
+// A reminder wants BOTH what to remind about and when. Subject first: "напомни
+// в 11" has a time and nothing to say at 11, and a reminder with no subject is
+// not worth setting. Order here is the order she asks in — she still only asks
+// about the first one missing.
 var wantedSlots = map[router.Intent][]dialogue.Slot{
-	router.IntentReminder: {dialogue.SlotTime},
+	router.IntentReminder: {dialogue.SlotText, dialogue.SlotTime},
 	router.IntentFact:     {dialogue.SlotKey},
 	router.IntentAct:      {dialogue.SlotFn},
 }
@@ -35,7 +41,8 @@ var wantedSlots = map[router.Intent][]dialogue.Slot{
 // questions, so there is no gender agreement to get wrong; the feminine
 // self-reference lives in the reply she gives when she drops the request.
 var clarifyQuestions = map[dialogue.Slot]string{
-	dialogue.SlotTime: "На когда напомнить?",
+	dialogue.SlotTime: "Когда?",
+	dialogue.SlotText: "О чём напомнить?",
 	dialogue.SlotKey:  "Что записать?",
 	dialogue.SlotFn:   "Что сделать?",
 }
@@ -45,11 +52,55 @@ var clarifyQuestions = map[dialogue.Slot]string{
 // landed. Feminine self-reference ("поняла"), as everywhere.
 const clarifyGaveUp = "Прости, я не поняла. Скажи, пожалуйста, по-другому."
 
-// clarifyExpired — his answer came after the TTL, so the parked request is
-// already gone. Same tone as clarifyGaveUp, different reason: too much time
+// clarifyExpiredVariants — his answer came after the TTL, so the parked request
+// is already gone. Same tone as clarifyGaveUp, different reason: too much time
 // passed, not "I did not understand". Feminine self-reference ("ждала",
 // "отпустила"); he is addressed with a plain imperative.
-const clarifyExpired = "Прости, я слишком долго ждала ответа и отпустила прошлую просьбу. Если она ещё нужна, скажи заново."
+//
+// Five phrasings, not one. This is the line he hears whenever he walks off
+// mid-request, so it is the line that repeats most — and the same sentence every
+// time is what makes a house assistant sound like a kiosk. They all carry the
+// same two facts (the old request is gone; say it again if it still matters),
+// because the wording may vary and the meaning may not.
+//
+// Fixed templates rather than model output, for the same reason as
+// clarifyQuestions: this text has to be right every time, and it is not worth a
+// generation to say something this small.
+var clarifyExpiredVariants = []string{
+	"Прости, я слишком долго ждала ответа и отпустила прошлую просьбу. Если она ещё нужна, скажи заново.",
+	"Кажется, прошлая просьба уже не важна — я её отпустила. Если я ошибаюсь, повтори.",
+	"Ты как-то резко замолчал, и я не стала ждать дальше. Если та просьба ещё нужна, скажи заново.",
+	"Я не дождалась ответа и убрала прошлую просьбу. Повтори, если она всё ещё нужна.",
+	"Столько времени прошло, что я отпустила прошлую просьбу. Скажи заново, если она в силе.",
+}
+
+// clarifyExpiredLine picks one of them at random.
+func clarifyExpiredLine() string {
+	return clarifyExpiredVariants[rand.Intn(len(clarifyExpiredVariants))]
+}
+
+// isClarifyExpired reports whether s opens with any of the expiry lines. The
+// notice is glued in front of this turn's reply (see withNotice), so a caller
+// checking for it has to match a prefix, not the whole string.
+func isClarifyExpired(s string) bool {
+	for _, v := range clarifyExpiredVariants {
+		if strings.HasPrefix(s, v) {
+			return true
+		}
+	}
+	return false
+}
+
+// trimClarifyExpired strips a leading expiry notice, leaving this turn's actual
+// reply. "" ⇒ the notice was the whole thing.
+func trimClarifyExpired(s string) string {
+	for _, v := range clarifyExpiredVariants {
+		if strings.HasPrefix(s, v) {
+			return strings.TrimSpace(strings.TrimPrefix(s, v))
+		}
+	}
+	return strings.TrimSpace(s)
+}
 
 // clarifyExpiredNotice returns that line when a parked question had just timed
 // out, and "" when nothing was parked. Call it right after
@@ -63,7 +114,7 @@ func (h *reactiveHandler) clarifyExpiredNotice() string {
 		return ""
 	}
 	log.Printf("voice: clarify — parked question expired, telling him and routing the words fresh")
-	return clarifyExpired
+	return clarifyExpiredLine()
 }
 
 // withNotice glues the expiry notice in front of this turn's reply. One turn

cmd/mavend/clarify_test.go

@@ -56,10 +56,13 @@ func TestClarifyQuestionForMissingSlot(t *testing.T) {
 		want  string
 		asked bool
 	}{
-		{"reminder without a time", clarifyDec(router.IntentReminder, router.Slots{Text: "напомни позвонить маме"}, "напомни позвонить маме"), "На когда напомнить?", true},
+		{"reminder without a time", clarifyDec(router.IntentReminder, router.Slots{Text: "напомни позвонить маме"}, "напомни позвонить маме"), "Когда?", true},
 		{"fact without a key", clarifyDec(router.IntentFact, router.Slots{Text: "запиши"}, "запиши"), "Что записать?", true},
 		{"act without a fn", clarifyDec(router.IntentAct, router.Slots{Text: "сделай это"}, "сделай это"), "Что сделать?", true},
-		{"reminder that already has a time", clarifyDec(router.IntentReminder, router.Slots{HasTime: true}, "напомни в 11"), "", false},
+		// A time with nothing to say at that time is still half a reminder, so
+		// the subject is what she asks about — not silence.
+		{"reminder that has a time but no subject", clarifyDec(router.IntentReminder, router.Slots{HasTime: true}, "напомни в 11"), "О чём напомнить?", true},
+		{"reminder that has both", clarifyDec(router.IntentReminder, router.Slots{Text: "позвонить маме", HasTime: true}, "напомни в 11 позвонить маме"), "", false},
 		{"chat is never worth a question", clarifyDec(router.IntentChat, router.Slots{Text: "мгм"}, "мгм"), "", false},
 		{"query is never worth a question", clarifyDec(router.IntentQuery, router.Slots{Text: "а"}, "а"), "", false},
 	}
@@ -78,7 +81,7 @@ func TestClarifyReminderCompletesOnAnswer(t *testing.T) {
 	h, st, _ := newClarifyHandler(t)
 
 	question, asked := h.askClarify(clarifyDec(router.IntentReminder, router.Slots{Text: "напомни позвонить маме"}, "напомни позвонить маме"))
-	if !asked || question != "На когда напомнить?" {
+	if !asked || question != "Когда?" {
 		t.Fatalf("expected the time question, got %q asked=%v", question, asked)
 	}
 
@@ -152,7 +155,7 @@ func TestClarifyAsksThreeTimesThenSaysSo(t *testing.T) {
 		if !handled {
 			t.Fatalf("answer %d must be consumed as an answer", i)
 		}
-		if reply != "На когда напомнить?" {
+		if reply != "Когда?" {
 			t.Fatalf("attempt %d should ask again, got %q", i, reply)
 		}
 		if h.clarifyStore.Get(voiceDialogueID, h.now()) == nil {
@@ -304,17 +307,17 @@ func TestClarifyExpiryIsAnnouncedAndWordsStillRoute(t *testing.T) {
 	*now = now.Add(clarifyTTL + time.Second)
 
 	reply := h.handleText(ctx, "как дела")
-	if !strings.HasPrefix(reply, clarifyExpired) {
+	if !isClarifyExpired(reply) {
 		t.Fatalf("expired question must be announced first, got %q", reply)
 	}
-	if strings.TrimSpace(strings.TrimPrefix(reply, clarifyExpired)) == "" {
+	if trimClarifyExpired(reply) == "" {
 		t.Fatalf("the new words must still be answered, got only the notice: %q", reply)
 	}
 	if h.clarifyStore.Get(voiceDialogueID, h.now()) != nil {
 		t.Fatal("the expired question must be gone")
 	}
 	// The notice is said once, not on every later utterance.
-	if reply := h.handleText(ctx, "как дела"); strings.Contains(reply, clarifyExpired) {
+	if reply := h.handleText(ctx, "как дела"); isClarifyExpired(reply) {
 		t.Fatalf("notice repeated on a later turn: %q", reply)
 	}
 }

cmd/mavend/main.go

@@ -278,6 +278,7 @@ func run(args []string) error {
 				NGpuLayers:   cfg.Phraser.NGpuLayers,
 				NCtx:         cfg.Phraser.NCtx,
 				Timeout:      time.Duration(cfg.Phraser.Timeout),
+				LLMNudges:    cfg.Phraser.LLMNudges,
 				ContextBlock: contextBlockFn(cfg, time.Now),
 			}
 			if pc.BinPath == "" {
@@ -448,6 +449,7 @@ func run(args []string) error {
 					NGpuLayers:   cfg.Phraser.NGpuLayers,
 					NCtx:         cfg.Phraser.NCtx,
 					Timeout:      time.Duration(cfg.Phraser.Timeout),
+					LLMNudges:    cfg.Phraser.LLMNudges,
 					ContextBlock: contextBlockFn(cfg, time.Now),
 				}
 				if pc.BinPath == "" {

cmd/mavend/replier_llm.go

@@ -34,7 +34,7 @@ func newLLMReplier(c completer, block func() string) *llmReplier {
 	return &llmReplier{c: c, stub: voice.NewStubReplier(), block: block}
 }
 
-const replySystem = `Ты — Maven, домашняя ассистентка (о себе — в женском роде). Владелец — мужчина, говоришь с ним на "ты", в единственном числе; никогда не "вы"/"ваш" и не "он"/"его". Подтверди действие РОВНО ОДНИМ коротким предложением (≤120 символов), тепло и по-русски. Не задавай вопросов, не повторяй слова, не добавляй ничего после точки. Отвечай ТОЛЬКО одним объектом JSON с полями "response" (текст) и "mood" (ровно одно из: neutral, happy, thinking, tired, confused).
+const replySystem = `Ты — Maven, домашняя ассистентка (о себе — в женском роде). Владелец — мужчина, говоришь с ним на "ты", в единственном числе; никогда не "вы"/"ваш" и не "он"/"его". Подтверди действие РОВНО ОДНИМ коротким предложением (≤120 символов), по-русски, спокойно и без официальных формулировок. Не задавай вопросов, не повторяй слова, не добавляй ничего после точки. Отвечай ТОЛЬКО одним объектом JSON с полями "response" (текст) и "mood" (ровно одно из: neutral, happy, thinking, tired, confused).
 Пример: {"response": "Записала, что ты выпил стакан воды.", "mood": "neutral"}
 Никогда не пиши "..." в поле response.`
 

deploy/mavend.json

@@ -6,11 +6,12 @@
   "state_dir": "/var/lib/maven",
 
   "phraser": {
-    "model_path": "/opt/maven/models/llm/qwen3.5/Qwen3.5-0.8B.Q4_K_M.gguf",
+    "model_path": "/opt/maven/models/llm/qwen3/Qwen3-1.7B-UD-Q4_K_XL.gguf",
     "bin_path": "llama-server",
     "n_gpu_layers": 99,
-    "n_ctx": 2048,
-    "timeout": "60s"
+    "n_ctx": 4096,
+    "timeout": "60s",
+    "llm_nudges": false
   },
 
   "telegram": {

internal/config/config.go

@@ -369,6 +369,12 @@ type PhraserConfig struct {
 	NGpuLayers int      `json:"n_gpu_layers,omitempty"`
 	NCtx       int      `json:"n_ctx,omitempty"`
 	Timeout    Duration `json:"timeout,omitempty"`
+
+	// LLMNudges — let the model word nudges again. Off by default: nudges are
+	// worded from hand-written Russian templates now (the model broke the
+	// persona and invented units). Chat, query and reminder phrasing always go
+	// through the model regardless. See phraser.Config.LLMNudges.
+	LLMNudges bool `json:"llm_nudges,omitempty"`
 }
 
 // EmbedderConfig — paths for the ONNX multilingual embedder. The daemon

internal/config/config_test.go

@@ -35,6 +35,27 @@ func TestLoadDefaults(t *testing.T) {
 	}
 }
 
+// Nudges come from templates unless the config says otherwise.
+func TestPhraserLLMNudgesDefaultsOff(t *testing.T) {
+	p := writeConfig(t, `{"phraser":{"model_path":"/tmp/m.gguf"}}`)
+	c, err := Load(p)
+	if err != nil {
+		t.Fatalf("Load: %v", err)
+	}
+	if c.Phraser.LLMNudges {
+		t.Error("llm_nudges defaults on; templates must be the default")
+	}
+
+	p = writeConfig(t, `{"phraser":{"model_path":"/tmp/m.gguf","llm_nudges":true}}`)
+	c, err = Load(p)
+	if err != nil {
+		t.Fatalf("Load: %v", err)
+	}
+	if !c.Phraser.LLMNudges {
+		t.Error("llm_nudges:true did not parse")
+	}
+}
+
 func TestLoadDurationsParse(t *testing.T) {
 	p := writeConfig(t, `{"tick_interval":"90s","repeat_interval":"10m"}`)
 	c, err := Load(p)

internal/kiwix/client.go

@@ -82,7 +82,7 @@ type rss struct {
 		Description struct {
 			Inner string `xml:",innerxml"`
 		} `xml:"description"`
-		WordCount   string `xml:"wordCount"`
+		WordCount string `xml:"wordCount"`
 	} `xml:"channel>item"`
 }
 

internal/kiwix/rewrite_test.go

@@ -81,7 +81,7 @@ func TestRewriteConstrainsTheCall(t *testing.T) {
 func TestRewriteRejectsBadModelOutput(t *testing.T) {
 	bad := []string{
 		`{"query":"почему небо синее"}`, // never translated
-		`{"query":""}`,                  // empty
+		`{"query":""}`, // empty
 		`{"query":"the sky is blue because sunlight is scattered by air"}`, // an answer
 		// Note: a SHORT English prose fragment ("Let me analyze this request")
 		// is under the word cap and cannot be caught here. The grammar is what

internal/phraser/broken_json_test.go

@@ -0,0 +1,54 @@
+package phraser
+
+import (
+	"errors"
+	"strings"
+	"testing"
+)
+
+// A reply that starts a JSON object and never finishes it is a failed
+// generation, not a reply. Before this, the parser returned ("", "") for these
+// and every caller then shipped the raw fragment as the thing Maven said. A
+// real run produced replies of literally "{" and "{\n  \"".
+func TestParseResponseMoodRejectsUnfinishedJSON(t *testing.T) {
+	for _, raw := range []string{
+		`{`,
+		"{\n  \"",
+		`{"response": "неполн`,
+		`{"response": "текст", "mood":`,
+	} {
+		text, mood, err := parseResponseMood(raw)
+		if !errors.Is(err, errBrokenJSON) {
+			t.Errorf("parseResponseMood(%q) err = %v, want errBrokenJSON", raw, err)
+		}
+		if text != "" || mood != "" {
+			t.Errorf("parseResponseMood(%q) leaked %q/%q — a fragment must never come back as a reply", raw, text, mood)
+		}
+	}
+}
+
+// Bare prose is still fine. Small models sometimes answer without any JSON at
+// all, and that reply is usable — so the new error must not swallow it.
+func TestParseResponseMoodAllowsBareProse(t *testing.T) {
+	for _, raw := range []string{
+		"норм, а ты как?",
+		"вот что я нашла: ключ у соседа",
+	} {
+		text, mood, err := parseResponseMood(raw)
+		if err != nil {
+			t.Errorf("parseResponseMood(%q) err = %v, want nil", raw, err)
+		}
+		// No JSON means no fields; the caller ships raw as-is.
+		if text != "" || mood != "" {
+			t.Errorf("parseResponseMood(%q) = %q/%q, want empty", raw, text, mood)
+		}
+	}
+}
+
+// The measured failure: the model wants more than 400 characters and the old
+// grammar cut it off mid-word. Guards the bound against being tightened back.
+func TestGrammarStringBoundHasRoomForARealAnswer(t *testing.T) {
+	if !strings.Contains(responseGrammar, "{0,1000}") {
+		t.Error("grammar string bound is not 1000; 400 truncated real replies mid-word (see the comment on responseGrammar)")
+	}
+}

internal/phraser/eval/address_multi_test.go

@@ -31,3 +31,35 @@ func TestAddressDeduplicates(t *testing.T) {
 		t.Errorf("detail repeats the same break %d times: %q", n, res.Detail)
 	}
 }
+
+// The fragments a real run produced. All of them scored as non-empty replies
+// before checkNonEmpty looked for letters.
+func TestNonEmptyNeedsLetters(t *testing.T) {
+	for _, body := range []string{
+		"{",
+		"{\n  \"",
+		"15-16",
+		`{"`,
+		"   ",
+		"...",
+	} {
+		if got := checkNonEmpty(body); got.Pass {
+			t.Errorf("checkNonEmpty(%q) passed — that is not a reply", body)
+		}
+	}
+}
+
+// And it must not start failing real replies. Latin counts as well as Cyrillic:
+// answers about ssd or vpn are legitimately part English.
+func TestNonEmptyAcceptsRealReplies(t *testing.T) {
+	for _, body := range []string{
+		"норм, а ты как?",
+		"вот что я нашла: ключ у соседа",
+		"ssd быстрее hdd.",
+		"9 минут.",
+	} {
+		if got := checkNonEmpty(body); !got.Pass {
+			t.Errorf("checkNonEmpty(%q) failed: %s", body, got.Detail)
+		}
+	}
+}

internal/phraser/eval/checks.go

@@ -623,11 +623,24 @@ const (
 	CheckEllipsis = "ellipsis" // she finished the sentence
 )
 
+// A reply needs words in it, not just characters. This check used to test for a
+// non-empty string, which scored 27/27 on a run where two replies were "{" and
+// "{\n  \"" — punctuation passed as content. Braces, quotes, digits and spaces
+// are all empty in the only sense that matters.
+//
+// Digits alone fail too, and that is deliberate: the same run answered "сколько
+// варить яйцо вкрутую?" with "15-16". No unit, no words, and it is also the
+// wrong number. Whatever that is, it is not something she said.
 func checkNonEmpty(body string) Result {
 	if strings.TrimSpace(body) == "" {
 		return Result{CheckNonEmpty, false, "empty reply"}
 	}
-	return Result{CheckNonEmpty, true, ""}
+	for _, r := range body {
+		if unicode.IsLetter(r) {
+			return Result{CheckNonEmpty, true, ""}
+		}
+	}
+	return Result{CheckNonEmpty, false, fmt.Sprintf("no letters in the reply %q — punctuation or digits only", strings.TrimSpace(body))}
 }
 
 // checkEllipsis — a reply ending in "…" or "..." is a generation that ran out of

internal/phraser/eval/templates_test.go

@@ -0,0 +1,58 @@
+package eval
+
+import (
+	"context"
+	"math/rand"
+	"testing"
+
+	"github.com/kami/maven/internal/phraser"
+)
+
+// TestTemplateNudges scores the hand-written Russian templates on the same
+// fixture the model is scored on. No model, no network — it runs in milliseconds.
+//
+// The bar is every case, not most of them: the templates are hand-written, so a
+// failure is a bug in one line of Russian, not model variance.
+func TestTemplateNudges(t *testing.T) {
+	f, err := Load()
+	if err != nil {
+		t.Fatalf("Load: %v", err)
+	}
+	// Fixed seed: the score must not depend on which variant came up.
+	nt, err := phraser.NewNudgeTemplates(rand.NewSource(20260731))
+	if err != nil {
+		t.Fatalf("NewNudgeTemplates: %v", err)
+	}
+	rep, err := Score(context.Background(), "ru templates", nt, f)
+	if err != nil {
+		t.Fatalf("Score: %v", err)
+	}
+	t.Log("\n" + rep.String())
+	t.Log("\n" + rep.Messages())
+	if rep.Passed != rep.Total {
+		t.Errorf("templates scored %d/%d, want every case:\n%s",
+			rep.Passed, rep.Total, rep.Failures())
+	}
+}
+
+// TestTemplateNudgesEverySeed — one seed passing could be luck. Every variant of
+// every rule has to pass every check, so sweep seeds until each has been used.
+func TestTemplateNudgesEverySeed(t *testing.T) {
+	f, err := Load()
+	if err != nil {
+		t.Fatalf("Load: %v", err)
+	}
+	for seed := int64(0); seed < 60; seed++ {
+		nt, err := phraser.NewNudgeTemplates(rand.NewSource(seed))
+		if err != nil {
+			t.Fatalf("NewNudgeTemplates: %v", err)
+		}
+		rep, err := Score(context.Background(), "ru templates", nt, f)
+		if err != nil {
+			t.Fatalf("Score: %v", err)
+		}
+		if rep.Passed != rep.Total {
+			t.Errorf("seed %d: %d/%d\n%s", seed, rep.Passed, rep.Total, rep.Failures())
+		}
+	}
+}

internal/phraser/grammar_test.go

@@ -35,6 +35,8 @@ func newGrammarSpy(t *testing.T) *grammarSpy {
 }
 
 // callAllPhrasingPaths hits every path that expects the JSON contract.
+// LLMNudges must be set on the phraser under test: nudges come from templates
+// by default and never reach the model at all.
 func callAllPhrasingPaths(t *testing.T, p *LLMPhraser) {
 	t.Helper()
 	ctx := context.Background()
@@ -58,7 +60,7 @@ func TestGrammarIsAttachedToEveryPhrasingRequest(t *testing.T) {
 		t.Fatal("responseGrammar is empty")
 	}
 	spy := newGrammarSpy(t)
-	p := NewLLMPhraserAt(spy.srv.URL, Config{})
+	p := NewLLMPhraserAt(spy.srv.URL, Config{LLMNudges: true})
 
 	callAllPhrasingPaths(t, p)
 
@@ -74,7 +76,7 @@ func TestGrammarIsAttachedToEveryPhrasingRequest(t *testing.T) {
 
 func TestNoGrammarConfigDisablesIt(t *testing.T) {
 	spy := newGrammarSpy(t)
-	p := NewLLMPhraserAt(spy.srv.URL, Config{NoGrammar: true})
+	p := NewLLMPhraserAt(spy.srv.URL, Config{NoGrammar: true, LLMNudges: true})
 
 	callAllPhrasingPaths(t, p)
 
@@ -97,7 +99,10 @@ func TestGrammarStringRuleIsNotASCIIOnly(t *testing.T) {
 // Russian body with an escaped quote inside, hand-built to test the contract.
 func TestGrammarShapedJSONParses(t *testing.T) {
 	raw := `{"response": "он сказал \"привет\" и ушёл.\nвот так.", "mood": "confused"}`
-	text, mood := parseResponseMood(raw)
+	text, mood, err := parseResponseMood(raw)
+	if err != nil {
+		t.Fatalf("grammar-shaped JSON did not parse: %v", err)
+	}
 	if want := "он сказал \"привет\" и ушёл.\nвот так."; text != want {
 		t.Errorf("response = %q, want %q", text, want)
 	}

internal/phraser/llmphraser.go

@@ -31,6 +31,10 @@ type LLMPhraser struct {
 	cmd    *exec.Cmd
 	cancel context.CancelFunc
 	wg     sync.WaitGroup
+
+	// tmpl — the hand-written Russian nudges. Default path for nudges; see
+	// Config.LLMNudges. nil only if the template file failed to load.
+	tmpl *NudgeTemplates
 }
 
 type Config struct {
@@ -46,6 +50,19 @@ type Config struct {
 	// nil ⇒ no block, the prompts stand alone.
 	ContextBlock func() string
 
+	// LLMNudges puts the model back in charge of nudge wording.
+	//
+	// Off by default, and that is a deliberate deprecation of LLM-phrased
+	// nudges: hand-written templates (nudges_ru_v1.json) word every nudge now.
+	// A nudge has nothing to be creative about, and measured over many runs the
+	// 0.8B broke the persona (formal "вы", plural imperatives, masculine
+	// self-reference) and invented facts and units. Templates score 15/15 on the
+	// nudge fixture, the model 11-13/15.
+	//
+	// The LLM path is kept, not deleted: flip this on to get it back. Chat,
+	// query and reminder phrasing are untouched and still go through the model.
+	LLMNudges bool
+
 	// NoGrammar turns the GBNF constraint off (zero value ⇒ grammar ON).
 	// The escape hatch exists because the target resident model — the
 	// locally CPT'd Qwen3-1.7B — does not exist yet: if its chat template
@@ -71,6 +88,7 @@ func NewLLMPhraser(ctx context.Context, cfg Config) (*LLMPhraser, error) {
 		cfg:    cfg,
 		client: &http.Client{Timeout: cfg.Timeout},
 		cancel: cancel,
+		tmpl:   loadNudgeTemplates(),
 	}
 	if err := p.start(ctx); err != nil {
 		cancel()
@@ -92,9 +110,22 @@ func NewLLMPhraserAt(baseURL string, cfg Config) *LLMPhraser {
 		client: &http.Client{Timeout: cfg.Timeout},
 		port:   strings.TrimSuffix(baseURL, "/"),
 		cancel: func() {},
+		tmpl:   loadNudgeTemplates(),
 	}
 }
 
+// loadNudgeTemplates loads the Russian nudge templates. A broken template file
+// must not stop the daemon booting, so a failure logs and leaves the LLM path
+// in charge of nudges.
+func loadNudgeTemplates() *NudgeTemplates {
+	nt, err := NewNudgeTemplates(nil)
+	if err != nil {
+		log.Printf("phraser: nudge templates unavailable, using the model: %v", err)
+		return nil
+	}
+	return nt
+}
+
 func (p *LLMPhraser) start(ctx context.Context) error {
 	args := []string{
 		"-m", p.cfg.ModelPath,
@@ -185,12 +216,21 @@ func (p *LLMPhraser) Close() error {
 }
 
 func (p *LLMPhraser) PhraseNudge(ctx context.Context, c loop.Candidate) (delivery.PhrasedNudge, error) {
+	// Templates first — see Config.LLMNudges for why this is the default.
+	if !p.cfg.LLMNudges && p.tmpl != nil {
+		return p.tmpl.PhraseNudge(ctx, c)
+	}
 	prompt := buildNudgePrompt(c)
 	resp, err := p.chat(ctx, prompt)
 	if err != nil {
 		return delivery.PhrasedNudge{}, err
 	}
-	body, mood := parseResponseMood(resp)
+	body, mood, perr := parseResponseMood(resp)
+	if perr != nil {
+		// Truncated JSON. Not a nudge — use the plain Russian fallback.
+		log.Printf("phraser: PhraseNudge: %v", perr)
+		body, mood = "", ""
+	}
 	if body == "" {
 		// fallback: try old body/summary format
 		body, _ = parsePhrase(resp)
@@ -216,11 +256,16 @@ func (p *LLMPhraser) PhraseQuery(ctx context.Context, utterance string, notes []
 		// prompt is the single tested source in router.KnowledgePrompt.
 		sys := persona.Prepend(p.cfg.ContextBlock, router.KnowledgePrompt())
 		prompt := fmt.Sprintf("Пользователь спрашивает: \"%s\".", utterance)
-		resp, err := p.chatWithSystem(ctx, sys, prompt, 256)
+		resp, err := p.chatWithSystem(ctx, sys, prompt, 768)
 		if err != nil || resp == "" {
 			return "не знаю.", nil
 		}
-		if text, _ := parseResponseMood(resp); text != "" {
+		text, _, perr := parseResponseMood(resp)
+		if perr != nil {
+			log.Printf("phraser: PhraseQuery: %v", perr)
+			return "не знаю.", nil
+		}
+		if text != "" {
 			return text, nil
 		}
 		return resp, nil
@@ -230,17 +275,22 @@ func (p *LLMPhraser) PhraseQuery(ctx context.Context, utterance string, notes []
 	}
 	sys := p.querySystemPrompt()
 	prompt := fmt.Sprintf(
-		`The user asks: "%s". Your notes matching the query contain: "%s". Answer them naturally and briefly. If the notes don't answer the question, say so.`,
+		`Он спрашивает: "%s". В твоих заметках по этому вопросу написано: "%s". Ответь ему коротко и своими словами. Если в заметках ответа нет — так и скажи.`,
 		utterance, strings.Join(notes, `"; "`),
 	)
-	resp, err := p.chatWithSystem(ctx, sys, prompt, 256)
-	if err != nil {
+	resp, err := p.chatWithSystem(ctx, sys, prompt, 768)
+	text, _, perr := parseResponseMood(resp)
+	if err != nil || perr != nil {
+		// Read the notes out rather than ship a broken fragment.
+		if perr != nil {
+			log.Printf("phraser: PhraseQuery: %v", perr)
+		}
 		if len(notes) == 1 {
 			return "вот что я нашла: " + notes[0], nil
 		}
 		return "вот что я нашла: " + strings.Join(notes, "; "), nil
 	}
-	if text, _ := parseResponseMood(resp); text != "" {
+	if text != "" {
 		return text, nil
 	}
 	return resp, nil
@@ -263,12 +313,17 @@ func (p *LLMPhraser) PhraseChat(ctx context.Context, utterance string, history [
 	combined += utterance
 	msgs = append(msgs, chatMsg{Role: "user", Content: strings.TrimSpace(combined)})
 
-	resp, err := p.chatWithMessages(ctx, msgs, 512)
+	resp, err := p.chatWithMessages(ctx, msgs, 768)
 	if err != nil {
 		log.Printf("phraser: PhraseChat: %v", err)
 		return "поговорили.", nil
 	}
-	if text, _ := parseResponseMood(resp); text != "" {
+	text, _, perr := parseResponseMood(resp)
+	if perr != nil {
+		log.Printf("phraser: PhraseChat: %v", perr)
+		return "поговорили.", nil
+	}
+	if text != "" {
 		return text, nil
 	}
 	// fallback: plain text without JSON
@@ -281,11 +336,13 @@ func (p *LLMPhraser) PhraseChat(ctx context.Context, utterance string, history [
 // chatSystemPrompt returns the system prompt for conversational chat.
 // Prepends the shared context block when the phraser has one.
 func chatSystemPrompt(block func() string) string {
-	base := `You are maven, a self-hosted personal assistant. You're talking with your owner. 
-Keep replies brief (1-3 sentences) and natural. You're helpful, curious, and a little warm.
-Respond in the user's language (Russian or English, matching their last message). 
-Never roleplay emotions you don't have, but stay friendly. 
-Respond ONLY with valid JSON: {"response": "...", "mood": "neutral"}. "response" is your reply text; "mood" reflects your tone (neutral/happy/thinking/tired/confused).`
+	// No self-introduction here: the persona block prepended one line above
+	// already says who she is, same as router.KnowledgePrompt.
+	base := `Ты разговариваешь с хозяином. О себе говоришь в женском роде ("я подумала", "я рада"). Он мужчина: обращайся к нему на "ты", в мужском роде ("ты сказал", "ты забыл"). Никогда не "вы"/"ваш" и никогда "он"/"его" — ты говоришь ему, а не о нём.
+
+Отвечай по-русски, коротко: одна-три фразы, живым языком. Ты доброжелательная, тебе интересно, но чувства не изображай.
+
+Отвечай ТОЛЬКО одним объектом JSON: {"response": "...", "mood": "neutral"}. В "response" — твой ответ. В "mood" — ровно одно из: neutral, happy, thinking, tired, confused.`
 	return persona.Prepend(block, base)
 }
 
@@ -349,7 +406,12 @@ func (p *LLMPhraser) PhraseReminder(ctx context.Context, d loop.ReminderDecision
 	if err != nil {
 		return delivery.PhrasedReminder{}, err
 	}
-	body, mood := parseResponseMood(resp)
+	body, mood, perr := parseResponseMood(resp)
+	if perr != nil {
+		// Truncated JSON. Fall through to the reminder's own text.
+		log.Printf("phraser: PhraseReminder: %v", perr)
+		body, mood = "", ""
+	}
 	if body == "" {
 		// fallback: try old body/summary format
 		body, _ = parsePhrase(resp)
@@ -394,10 +456,16 @@ type chatReq struct {
 // Russian, so an ASCII-only rule would make every reply empty. The escape rule
 // is what lets the model close a string it opened with a quote inside. Length
 // is bounded so a repetition loop truncates the field, not the JSON object.
+//
+// That bound was 400 and 400 was too tight. Measured against Qwen3.5-0.8B: on
+// "почему гром слышно позже молнии?" the reply came back exactly 400 characters
+// long, cut mid-word ("Нужно записать и,"), at every token cap from 256 to 2048.
+// So the token cap was never what stopped it — this rule was. 1000 characters is
+// roughly six Russian sentences, still short enough to stop a repetition loop.
 const responseGrammar = `
 root   ::= "{" ws "\"response\"" ws ":" ws string ws "," ws "\"mood\"" ws ":" ws mood ws "}"
 mood   ::= "\"neutral\"" | "\"happy\"" | "\"thinking\"" | "\"tired\"" | "\"confused\""
-string ::= "\"" ([^"\\] | "\\" ["\\/bfnrt]){0,400} "\""
+string ::= "\"" ([^"\\] | "\\" ["\\/bfnrt]){0,1000} "\""
 ws     ::= [ \t\n]*
 `
 
@@ -483,12 +551,21 @@ func (p *LLMPhraser) chatWithSystem(ctx context.Context, system, user string, ma
 // Russian only, feminine self-reference, second person masculine (the owner is
 // a man). She talks TO him, informally, singular — never "вы", never "он".
 // One short sentence — the nudge is spoken aloud.
+//
+// What the ban on обращения forbids is pet names ("дорогой", "милый"), not his
+// name: "Ками, ноутбук на трёх процентах" is exactly how she talks, and the
+// unqualified word read as forbidding that too. Hence "ласковые обращения".
+//
+// The examples also never claim a physical act. She has no hands and no smart
+// plug — she can tell him the battery is at three percent, she cannot put the
+// laptop on charge. An example that says she did teaches the model to invent
+// actions Maven never took, which is worse than a missing nudge.
 const nudgeSystem = `Ты — Maven, домашняя ассистентка. О себе говоришь в женском роде ("я проверила", "я записала"). Владелец — мужчина, обращайся к нему в мужском роде ("ты пил", "ты забыл").
 Говоришь с ним на "ты", в единственном числе ("выпей", "встань"). Никогда не "вы"/"вас"/"ваш" и никогда "он"/"его" — ты говоришь ему, а не о нём.
 
 Пиши ОДНО короткое напоминание по-русски: не больше 120 символов и не больше 16 слов. Только по делу.
 
-Запрещено: обращения ("дорогой", "милый"), эмодзи, извинения ("прости", "извини"), вопросы о самочувствии, похвала, больше одного восклицательного знака, английские слова кроме имён сервисов.
+Запрещено: ласковые обращения ("дорогой", "милый"), эмодзи, извинения ("прости", "извини"), вопросы о самочувствии, похвала, больше одного восклицательного знака, английские слова кроме имён сервисов.
 
 Отвечай ТОЛЬКО одним объектом JSON с полями "response" и "mood".
 "response" — сам текст напоминания.
@@ -496,7 +573,7 @@ const nudgeSystem = `Ты — Maven, домашняя ассистентка. О
 
 Так выглядит правильный ответ по форме. Темы здесь посторонние — их в запросе не будет:
 {"response": "Стиральная машина закончила. Развесь бельё.", "mood": "neutral"}
-{"response": "Ноутбук на трёх процентах. Я поставила его на зарядку.", "mood": "confused"}
+{"response": "Ками, ноутбук на трёх процентах. Поставь его на зарядку.", "mood": "confused"}
 
 Это примеры ФОРМЫ, а не темы. Пиши только про ту ситуацию, которую тебе дали в запросе. Не копируй примеры и никогда не пиши "..." в поле response.`
 
@@ -507,7 +584,9 @@ func (p *LLMPhraser) systemPrompt() string {
 // querySystemPrompt returns the system prompt for PhraseQuery (notes + general
 // knowledge). Prepends the configured persona when set.
 func (p *LLMPhraser) querySystemPrompt() string {
-	base := "You are maven, a self-hosted personal assistant answering from your notes. Answer briefly and naturally in Russian starting with \"вот что я нашла: \". Respond ONLY with valid JSON: {\"response\": \"...\", \"mood\": \"neutral\"}."
+	// No self-introduction here: the persona block prepended one line above
+	// already says who she is, same as router.KnowledgePrompt.
+	base := "Ты отвечаешь ему по своим заметкам. Отвечай по-русски, коротко и своими словами, начинай с \"вот что я нашла: \". О себе — в женском роде (\"нашла\", \"записала\"). Он мужчина, обращайся к нему на \"ты\". Respond ONLY with valid JSON: {\"response\": \"...\", \"mood\": \"neutral\"}."
 	return persona.Prepend(p.cfg.ContextBlock, base)
 }
 
@@ -629,21 +708,39 @@ type responseMood struct {
 	Mood     string `json:"mood"`
 }
 
+// errBrokenJSON — the model started a JSON object and never finished it.
+// That is a failed generation, not a reply. Callers must use their fallback.
+var errBrokenJSON = fmt.Errorf("phraser: model output starts as JSON but does not parse")
+
 // parseResponseMood extracts {"response","mood"} from LLM output, tolerant
-// of thinking tokens and extra text before/after the JSON block. Returns
-// ("", "") when no valid JSON is found.
-func parseResponseMood(raw string) (response, mood string) {
+// of thinking tokens and extra text before/after the JSON block.
+//
+// Three outcomes:
+//   - parsed fine → the fields, nil error.
+//   - output never looked like JSON → ("", "", nil). The caller may ship it
+//     as-is; small models sometimes answer in bare prose and that is fine.
+//   - output starts with "{" but does not parse → errBrokenJSON. The grammar
+//     guarantees a valid *prefix*, so a generation that hits the token cap
+//     mid-object comes back as a fragment like `{` or `{\n  "`. Shipping that
+//     as a reply is the bug this error exists to stop.
+func parseResponseMood(raw string) (response, mood string, err error) {
 	cleaned := strings.TrimSpace(raw)
 	start := strings.Index(cleaned, "{")
 	end := strings.LastIndex(cleaned, "}")
 	if start < 0 || end < 0 || end <= start {
-		return "", ""
+		if strings.HasPrefix(cleaned, "{") {
+			return "", "", errBrokenJSON
+		}
+		return "", "", nil
 	}
 	var parsed responseMood
-	if err := json.Unmarshal([]byte(cleaned[start:end+1]), &parsed); err != nil {
-		return "", ""
+	if e := json.Unmarshal([]byte(cleaned[start:end+1]), &parsed); e != nil {
+		if strings.HasPrefix(cleaned, "{") {
+			return "", "", errBrokenJSON
+		}
+		return "", "", nil
 	}
-	return parsed.Response, parsed.Mood
+	return parsed.Response, parsed.Mood, nil
 }
 
 func parsePhrase(raw string) (body, summary string) {

internal/phraser/nudge_templates.go

@@ -0,0 +1,261 @@
+package phraser
+
+// Hand-written Russian nudges instead of generated ones.
+//
+// Why: on a nudge there is nothing to be creative about. Measured over many
+// runs, Qwen3.5-0.8B breaks the persona (formal "вы", plural imperatives,
+// masculine self-reference) and invents facts and units — it once told him to
+// boil an egg for "90-95 секунд". A nudge is five words of known content, so
+// wording it with a model buys nothing and risks the persona every time.
+//
+// The wording lives in nudges_ru_v1.json so it can be edited without touching
+// Go. This file only picks one and fills in the values.
+
+import (
+	"context"
+	_ "embed"
+	"encoding/json"
+	"fmt"
+	"math/rand"
+	"regexp"
+	"strings"
+	"sync"
+	"time"
+	"unicode"
+
+	"github.com/kami/maven/internal/delivery"
+	"github.com/kami/maven/internal/loop"
+)
+
+//go:embed nudges_ru_v1.json
+var nudgeTemplateJSON []byte
+
+// NudgeTemplateSchemaVersion — the version this code understands.
+const NudgeTemplateSchemaVersion = 1
+
+type nudgeRuleSet struct {
+	Mood     string   `json:"mood"`
+	Variants []string `json:"variants"`
+}
+
+type nudgeTemplateFile struct {
+	SchemaVersion int                     `json:"schema_version"`
+	Name          string                  `json:"name"`
+	Notes         []string                `json:"notes"`
+	Rules         map[string]nudgeRuleSet `json:"rules"`
+}
+
+// NudgeTemplates picks a hand-written Russian nudge for a candidate.
+//
+// Safe for concurrent use. Random, but never the same variant twice in a row
+// for the same rule — being nagged with identical words is what makes a nudge
+// easy to tune out.
+type NudgeTemplates struct {
+	mu   sync.Mutex
+	rnd  *rand.Rand
+	last map[string]string // rule family -> the text used last time
+	file nudgeTemplateFile
+}
+
+// NewNudgeTemplates loads the embedded template file. Pass a source to make the
+// picking reproducible in tests; nil means seed from the clock.
+func NewNudgeTemplates(src rand.Source) (*NudgeTemplates, error) {
+	var f nudgeTemplateFile
+	if err := json.Unmarshal(nudgeTemplateJSON, &f); err != nil {
+		return nil, fmt.Errorf("nudge templates: parse: %w", err)
+	}
+	if f.SchemaVersion != NudgeTemplateSchemaVersion {
+		return nil, fmt.Errorf("nudge templates: schema_version %d, want %d",
+			f.SchemaVersion, NudgeTemplateSchemaVersion)
+	}
+	if len(f.Rules) == 0 {
+		return nil, fmt.Errorf("nudge templates: no rules")
+	}
+	if src == nil {
+		src = rand.NewSource(time.Now().UnixNano())
+	}
+	return &NudgeTemplates{
+		rnd:  rand.New(src),
+		last: map[string]string{},
+		file: f,
+	}, nil
+}
+
+// PhraseNudge implements the nudge half of the Phraser interface, so the
+// templates can be scored by the same harness as the model.
+func (t *NudgeTemplates) PhraseNudge(_ context.Context, c loop.Candidate) (delivery.PhrasedNudge, error) {
+	body, mood := t.Nudge(c)
+	return delivery.PhrasedNudge{Candidate: c, Body: body, Summary: body, Mood: mood}, nil
+}
+
+// Nudge returns the text and the mood for one candidate. Never fails: if no
+// template fits it uses the plain per-rule fallback.
+func (t *NudgeTemplates) Nudge(c loop.Candidate) (body, mood string) {
+	rule := c.Rule.Name
+	family := t.family(rule)
+	set, ok := t.file.Rules[family]
+	if !ok {
+		return fallbackNudge(c), "neutral"
+	}
+	vals := nudgeValues(c)
+
+	// Only variants whose placeholders all have a value.
+	usable := make([]string, 0, len(set.Variants))
+	for _, v := range set.Variants {
+		if text, ok := fillTemplate(v, vals); ok {
+			usable = append(usable, text)
+		}
+	}
+	if len(usable) == 0 {
+		return fallbackNudge(c), "neutral"
+	}
+
+	mood = set.Mood
+	if mood == "" {
+		mood = "neutral"
+	}
+	return t.pick(family, usable), mood
+}
+
+// pick chooses at random, skipping whatever this rule said last time.
+func (t *NudgeTemplates) pick(family string, usable []string) string {
+	t.mu.Lock()
+	defer t.mu.Unlock()
+
+	choices := usable
+	if len(usable) > 1 {
+		choices = make([]string, 0, len(usable))
+		for _, v := range usable {
+			if v != t.last[family] {
+				choices = append(choices, v)
+			}
+		}
+		if len(choices) == 0 { // every variant equals the last one
+			choices = usable
+		}
+	}
+	got := choices[t.rnd.Intn(len(choices))]
+	t.last[family] = got
+	return got
+}
+
+// family maps a rule name to a block in the template file: an exact match
+// first, then the prefix of "routine:зарядка" / "morning:утро", then "default".
+func (t *NudgeTemplates) family(rule string) string {
+	if _, ok := t.file.Rules[rule]; ok {
+		return rule
+	}
+	if i := strings.IndexByte(rule, ':'); i > 0 {
+		if _, ok := t.file.Rules[rule[:i]]; ok {
+			return rule[:i]
+		}
+	}
+	return "default"
+}
+
+// placeholderRE — the {name} slots a template may use.
+var placeholderRE = regexp.MustCompile(`\{([a-z]+)\}`)
+
+// nudgeValues collects what this candidate can fill in. A key missing here
+// means every template needing it is skipped, so nothing half-filled is ever
+// spoken.
+func nudgeValues(c loop.Candidate) map[string]string {
+	vals := map[string]string{}
+	rule := c.Rule.Name
+
+	// {since} — only at hour scale. Below an hour the phrase would be minutes,
+	// and none of the templates read well with "сорок минут".
+	if d, ok := c.State.Since(rule); ok && d >= time.Hour {
+		if s := ruSinceWords(d); s != "" {
+			vals["since"] = s
+		}
+	}
+	// {service} — the aggregate fact's key carries the service name.
+	if f, ok := c.State.Fact(rule); ok && f.Key != "" && f.Key != rule {
+		vals["service"] = f.Key
+	}
+	// {what} — the Russian suffix of "routine:таблетки" / "morning:утро".
+	if i := strings.IndexByte(rule, ':'); i > 0 && i+1 < len(rule) {
+		vals["what"] = rule[i+1:]
+	}
+	return vals
+}
+
+// fillTemplate substitutes the placeholders. Returns false when a value is
+// missing, so a raw "{since}" can never reach the text-to-speech voice.
+func fillTemplate(tmpl string, vals map[string]string) (string, bool) {
+	missing := false
+	out := placeholderRE.ReplaceAllStringFunc(tmpl, func(m string) string {
+		name := m[1 : len(m)-1]
+		v, ok := vals[name]
+		if !ok || v == "" {
+			missing = true
+			return m
+		}
+		return v
+	})
+	if missing || strings.ContainsAny(out, "{}%") {
+		return "", false
+	}
+	return capitalizeFirst(out), true
+}
+
+// capitalizeFirst — a placeholder can start the sentence, and "полтора часа без
+// перерыва" should be spoken as a sentence, not a fragment.
+func capitalizeFirst(s string) string {
+	for i, r := range s {
+		return string(unicode.ToUpper(r)) + s[i+len(string(r)):]
+	}
+	return s
+}
+
+// hourWords — hours spelled out. "3 ч" is fine on a screen and wrong in a
+// Russian voice, so the number goes out as words.
+var hourWords = []string{
+	"ноль", "один", "два", "три", "четыре", "пять", "шесть", "семь", "восемь",
+	"девять", "десять", "одиннадцать", "двенадцать", "тринадцать",
+	"четырнадцать", "пятнадцать", "шестнадцать", "семнадцать", "восемнадцать",
+	"девятнадцать", "двадцать", "двадцать один", "двадцать два", "двадцать три",
+}
+
+// hourPlural — час / часа / часов by Russian counting rules.
+func hourPlural(h int) string {
+	if h%100 >= 11 && h%100 <= 14 {
+		return "часов"
+	}
+	switch h % 10 {
+	case 1:
+		return "час"
+	case 2, 3, 4:
+		return "часа"
+	default:
+		return "часов"
+	}
+}
+
+// ruSinceWords — "полтора часа", "два с половиной часа", "семь часов".
+// Empty string means "do not say it" (under an hour, or over a day).
+func ruSinceWords(d time.Duration) string {
+	if d < time.Hour {
+		return ""
+	}
+	h := int(d.Hours())
+	m := int(d.Minutes()) % 60
+	if m >= 45 {
+		h++
+		m = 0
+	}
+	if h >= len(hourWords) {
+		return "больше суток"
+	}
+	if h == 1 {
+		if m >= 15 {
+			return "полтора часа"
+		}
+		return "час"
+	}
+	if m >= 15 {
+		return hourWords[h] + " с половиной часа"
+	}
+	return hourWords[h] + " " + hourPlural(h)
+}

internal/phraser/nudge_templates_test.go

@@ -0,0 +1,202 @@
+package phraser
+
+import (
+	"context"
+	"math/rand"
+	"strings"
+	"testing"
+	"time"
+
+	"github.com/kami/maven/internal/loop"
+	"github.com/kami/maven/internal/store"
+)
+
+// cand builds a candidate the way a tick would.
+func cand(rule string, sinceMin int, factKey string) loop.Candidate {
+	now := time.Date(2026, 7, 31, 21, 40, 0, 0, time.UTC)
+	st := loop.State{Now: now, Facts: map[string]store.Fact{}}
+	if sinceMin > 0 || factKey != "" {
+		key := rule
+		if factKey != "" {
+			key = factKey
+		}
+		st.Facts[rule] = store.Fact{Key: key, Ts: now.Add(-time.Duration(sinceMin) * time.Minute)}
+	}
+	return loop.Candidate{Rule: loop.Rule{Name: rule, Severity: loop.Sev1}, Severity: loop.Sev1, State: st}
+}
+
+func newTestTemplates(t *testing.T, seed int64) *NudgeTemplates {
+	t.Helper()
+	nt, err := NewNudgeTemplates(rand.NewSource(seed))
+	if err != nil {
+		t.Fatalf("NewNudgeTemplates: %v", err)
+	}
+	return nt
+}
+
+func TestNudgeTemplatesLoad(t *testing.T) {
+	nt := newTestTemplates(t, 1)
+	for _, rule := range []string{"water", "meal", "break", "service_down", "netdata_critical", "routine", "morning", "default"} {
+		set, ok := nt.file.Rules[rule]
+		if !ok {
+			t.Errorf("no templates for %q", rule)
+			continue
+		}
+		if len(set.Variants) < 5 {
+			t.Errorf("%s: only %d variants", rule, len(set.Variants))
+		}
+		// Every rule needs one variant that needs no value, or a candidate
+		// without context has nothing to say. routine and morning are exempt:
+		// they always carry a name and must always say it.
+		plain := 0
+		seen := map[string]bool{}
+		for _, v := range set.Variants {
+			if !placeholderRE.MatchString(v) {
+				plain++
+			}
+			if seen[v] {
+				t.Errorf("%s: duplicate variant %q", rule, v)
+			}
+			seen[v] = true
+		}
+		if plain == 0 && rule != "routine" && rule != "morning" {
+			t.Errorf("%s: every variant needs a placeholder value", rule)
+		}
+	}
+}
+
+// The whole point of the picker: never the same words twice in a row.
+func TestNudgeNoImmediateRepeat(t *testing.T) {
+	nt := newTestTemplates(t, 7)
+	prev := ""
+	for i := 0; i < 200; i++ {
+		body, _ := nt.Nudge(cand("water", 200, ""))
+		if body == prev {
+			t.Fatalf("repeat at %d: %q", i, body)
+		}
+		prev = body
+	}
+}
+
+// Same seed, same sequence — otherwise the fixture score would drift run to run.
+func TestNudgeDeterministicWithSeed(t *testing.T) {
+	var runs [2][]string
+	for r := range runs {
+		nt := newTestTemplates(t, 42)
+		for i := 0; i < 20; i++ {
+			body, _ := nt.Nudge(cand("break", 100, ""))
+			runs[r] = append(runs[r], body)
+		}
+	}
+	for i := range runs[0] {
+		if runs[0][i] != runs[1][i] {
+			t.Fatalf("run %d differs: %q vs %q", i, runs[0][i], runs[1][i])
+		}
+	}
+}
+
+// A variant is only used when its value exists, and nothing half-filled ships.
+func TestNudgeNoLeftoverPlaceholders(t *testing.T) {
+	nt := newTestTemplates(t, 3)
+	cases := []loop.Candidate{
+		cand("water", 0, ""),   // no duration
+		cand("water", 30, ""),  // under an hour
+		cand("water", 200, ""), // hours
+		cand("service_down", 3, "vaultwarden"),
+		cand("service_down", 3, ""), // no service name
+		cand("routine:таблетки", 0, ""),
+		cand("morning:утро", 0, ""),
+		cand("unknown_rule", 0, ""),
+	}
+	for _, c := range cases {
+		for i := 0; i < 40; i++ {
+			body, mood := nt.Nudge(c)
+			if body == "" {
+				t.Fatalf("%s: empty body", c.Rule.Name)
+			}
+			if strings.ContainsAny(body, "{}%") {
+				t.Fatalf("%s: unfilled template %q", c.Rule.Name, body)
+			}
+			if mood != "neutral" {
+				t.Fatalf("%s: mood %q", c.Rule.Name, mood)
+			}
+		}
+	}
+}
+
+// The routine name must actually land in the text.
+func TestNudgeSubstitutesWhat(t *testing.T) {
+	nt := newTestTemplates(t, 11)
+	for i := 0; i < 40; i++ {
+		body, _ := nt.Nudge(cand("routine:таблетки", 0, ""))
+		if !strings.Contains(strings.ToLower(body), "таблетки") {
+			t.Fatalf("routine text lost the name: %q", body)
+		}
+	}
+}
+
+func TestRuSinceWords(t *testing.T) {
+	cases := []struct {
+		min  int
+		want string
+	}{
+		{30, ""},
+		{60, "час"},
+		{95, "полтора часа"},
+		{150, "два с половиной часа"},
+		{190, "три часа"},
+		{240, "четыре часа"},
+		{430, "семь часов"},
+		{660, "одиннадцать часов"},
+		{60 * 30, "больше суток"},
+	}
+	for _, c := range cases {
+		got := ruSinceWords(time.Duration(c.min) * time.Minute)
+		if got != c.want {
+			t.Errorf("%d min: got %q want %q", c.min, got, c.want)
+		}
+	}
+}
+
+// Templates are the default: a nudge must not reach the model at all.
+func TestLLMPhraserUsesTemplatesByDefault(t *testing.T) {
+	spy := newGrammarSpy(t)
+	p := NewLLMPhraserAt(spy.srv.URL, Config{})
+	pn, err := p.PhraseNudge(context.Background(), cand("water", 200, ""))
+	if err != nil {
+		t.Fatalf("PhraseNudge: %v", err)
+	}
+	if len(spy.grammars) != 0 {
+		t.Errorf("nudge hit the model %d times, want 0", len(spy.grammars))
+	}
+	if !strings.Contains(strings.ToLower(pn.Body), "вод") {
+		t.Errorf("nudge is not the water template: %q", pn.Body)
+	}
+}
+
+// ...and the flag brings the model back.
+func TestLLMNudgesFlagRestoresTheModel(t *testing.T) {
+	spy := newGrammarSpy(t)
+	p := NewLLMPhraserAt(spy.srv.URL, Config{LLMNudges: true})
+	pn, err := p.PhraseNudge(context.Background(), cand("water", 200, ""))
+	if err != nil {
+		t.Fatalf("PhraseNudge: %v", err)
+	}
+	if len(spy.grammars) != 1 {
+		t.Fatalf("nudge hit the model %d times, want 1", len(spy.grammars))
+	}
+	if pn.Body != "ага" {
+		t.Errorf("body = %q, want the model's reply", pn.Body)
+	}
+}
+
+func TestNudgeTemplatesPhraseNudge(t *testing.T) {
+	nt := newTestTemplates(t, 5)
+	pn, err := nt.PhraseNudge(context.Background(), cand("water", 200, ""))
+	if err != nil {
+		t.Fatalf("PhraseNudge: %v", err)
+	}
+	if pn.Body == "" || pn.Summary != pn.Body || pn.Mood != "neutral" {
+		t.Fatalf("bad nudge: %+v", pn)
+	}
+}

internal/phraser/nudges_ru_v1.json

@@ -0,0 +1,129 @@
+{
+  "schema_version": 1,
+  "name": "russian nudge templates v1",
+  "notes": [
+    "Hand-written Russian nudges. Edit the wording here, no Go changes needed.",
+    "Rules: she is feminine about herself, he is a man addressed as ты. Never вы/вас/ваш, never plural imperatives (выпейте), never он/его about him.",
+    "One short sentence. No questions, no emoji, no pet names, no emotional support.",
+    "Placeholders: {since} how long it has been (only used when it is at least an hour), {service} the service name, {what} the routine name. A variant whose placeholder has no value is skipped, so every rule needs at least one variant with no placeholder. The exception is routine and morning: those only exist for rules like routine:таблетки that always carry a name, and a routine nudge that drops the name is useless.",
+    "mood must be one of: neutral, happy, thinking, tired, confused."
+  ],
+  "rules": {
+    "water": {
+      "mood": "neutral",
+      "variants": [
+        "Ты не пил воду {since} — выпей стакан.",
+        "Пора выпить воды.",
+        "Стакан воды не помешает.",
+        "Воду ты не пил уже {since}.",
+        "Напоминаю про воду.",
+        "Сходи за водой, дела подождут.",
+        "Сделай глоток воды, пока помнишь.",
+        "Между делом выпей воды.",
+        "Вода — простое дело: выпей стакан.",
+        "Отвлекись на стакан воды."
+      ]
+    },
+    "meal": {
+      "mood": "neutral",
+      "variants": [
+        "Ты не ел {since} — поешь.",
+        "Пора поесть, сделай перекус.",
+        "Еда важнее ещё одного часа за столом.",
+        "Без еды уже {since}, поешь.",
+        "Напоминаю про еду — поешь.",
+        "Возьми перерыв на обед.",
+        "Сделай себе перекус, это пять минут.",
+        "Поешь, потом вернёшься к работе.",
+        "Поешь нормально, а не на ходу.",
+        "Еды не было {since} — разогрей что-нибудь."
+      ]
+    },
+    "break": {
+      "mood": "neutral",
+      "variants": [
+        "Ты за столом {since} — встань и разомнись.",
+        "Пора сделать перерыв.",
+        "Встань на пять минут.",
+        "{since} без перерыва — отойди от экрана.",
+        "Напоминаю про перерыв.",
+        "Разомни спину, потом продолжишь.",
+        "Короткая пауза не сорвёт дела.",
+        "Отойди от компьютера на минуту.",
+        "Сидишь без перерыва {since}.",
+        "Встань, пройдись, вернись."
+      ]
+    },
+    "service_down": {
+      "mood": "neutral",
+      "variants": [
+        "Сервис {service} не отвечает.",
+        "{service} упал — сервис не отвечает.",
+        "{service} не отвечает, сервис нужно поднимать.",
+        "Сервис {service} недоступен.",
+        "Проверь {service}: сервис не отвечает.",
+        "Сервис перестал отвечать.",
+        "Сервис {service} лежит, нужно смотреть.",
+        "{service} не отвечает уже {since}.",
+        "Мониторинг сообщает: {service} лежит.",
+        "Сервис {service} не отвечает, посмотри логи."
+      ]
+    },
+    "netdata_critical": {
+      "mood": "neutral",
+      "variants": [
+        "Netdata: критический алярм, проверь диск.",
+        "Критический алярм в netdata — посмотри диск.",
+        "Netdata поднял тревогу по диску.",
+        "Проверь диск: netdata ругается.",
+        "Алярм от netdata, критический.",
+        "Netdata: критический уровень, дело в диске.",
+        "Диск требует внимания — критический алярм в netdata.",
+        "Критический алярм: проверь место на диске.",
+        "Netdata сообщает о критической проблеме с диском.",
+        "Открой netdata: там критический алярм по диску."
+      ]
+    },
+    "routine": {
+      "mood": "neutral",
+      "variants": [
+        "По распорядку: {what}.",
+        "Пора — {what}.",
+        "Напоминаю: {what}.",
+        "В списке на сейчас: {what}.",
+        "{what} — сейчас самое время.",
+        "Не пропусти: {what}.",
+        "{what}: пора сделать.",
+        "Сейчас по плану {what}.",
+        "Твой распорядок: {what}.",
+        "{what} — по распорядку сейчас."
+      ]
+    },
+    "morning": {
+      "mood": "neutral",
+      "variants": [
+        "{what} — пора начать день.",
+        "{what}: пройди утренний список.",
+        "Начни {what} со списка.",
+        "{what}. Осталось пройти чеклист.",
+        "Утренний список ещё не пройден: {what}.",
+        "{what}: первый пункт списка за тобой.",
+        "{what} идёт, а список стоит.",
+        "{what}: не забудь про утренние дела.",
+        "По утреннему чеклисту ещё есть дела: {what}.",
+        "{what} — утренний список дел ещё ждёт."
+      ]
+    },
+    "default": {
+      "mood": "neutral",
+      "variants": [
+        "Напоминаю: есть дело.",
+        "Пора вернуться к отложенному делу.",
+        "Одно дело ждёт тебя.",
+        "Напоминаю про дело из списка.",
+        "В списке осталось дело.",
+        "Дело всё ещё не сделано."
+      ]
+    }
+  }
+}