gofmt the kiwix client and rewrite test

PR #41 and #44 landed these two files unformatted, so the gofmt gate that
PR #12 added to `make test` failed as soon as both were on one branch.
Struct-tag and comment alignment only, no semantic change.

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`.
@@ -82,9 +93,23 @@ workspace enforces that the Go and relabelling prompts remain identical.
 
 ## Non-goals (hard constraints)
 
-Never phones home. Not a nag, not autonomous. Maven's persona is **feminine** — Russian
+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`).
 
+**"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
+world questions, so she needs to read external sources. What replaces it:
+
+- **No telemetry, no cloud model, no third-party account.** That part never changes. Nothing
+  about Maven is reported to anyone, and inference stays on the box.
+- **Local sources first.** Kiwix ZIMs on homesrv (Wikipedia, ifixit) before anything on the
+  network. Reading beats recalling for a small model, and a local read costs nothing.
+- **External search is allowed and off unless configured**, like the weather and telegram
+  capabilities.
+- **His notes and facts are never search input.** Looking up why the sky is blue and sending
+  his stored personal notes to an upstream engine are different acts. Only the utterance goes
+  out, never the persona block, history, or matched notes.
+
 ## Web UI conventions
 
 Server-rendered pages share `cmd/mavweb/static/ui.css` (served at `/ui.css`) and the `nav`

DESIGN.md

@@ -15,7 +15,8 @@
 
 **Maven** — self-hosted personal assistant. Manages your day, acts on your
 homelab. One daemon on homesrv (always-on, not the workstation), multiple
-client surfaces. All local, never phones home.
+client surfaces. Inference and data stay on the box; she may READ external
+sources (see Non-goals — "never phones home" is deprecated).
 
 Primary name is "Maven", with feminine-gendered Russian self-reference
 ("она", "меня", "помогла"). Clients may choose their own UI label. Consistent
@@ -35,8 +36,13 @@ Inside boundary — the ones that actually constrain the build:
   she records. A confident wrong fact is worse than a known gap.
 - **Not a nag** — she'd rather miss a nudge than be mutable. Shuts up when
   uncertain. Load-bearing.
-- **Not a stranger** — runs on your stuff, your model, your data. Never
-  phones home.
+- **Not a stranger** — runs on your stuff, your model, your data. No
+  telemetry, no cloud model, no third-party account. She may READ external
+  sources to answer world questions (Kiwix first, then optional search); she
+  never reports anything about you to anyone, and your notes and facts are
+  never used as search input. **"Never phones home" as an absolute is
+  deprecated** — owner's call, 2026-07-31: a small model does not know enough
+  to be useful without reading.
 - **Not a relationship** — mom-tone is a function that makes nudges land, not
   emotional company. Names the drift a warm small model falls into.
 
@@ -458,7 +464,7 @@ decides *insistence*. Both are needed.
 
 sev ≤ 2 drops on away, sev ≥ 3 holds: a missed water nudge is noise, a missed
 backup failure isn't. Away-channels (ntfy/telegram) leave the box — the one
-path that crosses "never phones home," through your own relay. **Minimal
+path that leaves the box for a person to see, through your own relay. **Minimal
 body** — "disk low on homesrv," not detail; don't make notifications a
 shoulder-surf exfil surface.
 

MODEL-BAKEOFF-31-07-2026.md

@@ -1,8 +1,18 @@
 # 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**.
 
@@ -99,3 +109,108 @@ 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`.
+- `/mnt/hdd1/llms/LFM2.5/Qwen3-1.7B-UD-Q4_K_XL.gguf` is a 293 MB truncated download
+  in the wrong directory. The good 1.13 GB copy is in `qwen3/`. Delete the stray one.
+- 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`.

REARCH.md

@@ -90,4 +90,7 @@ later* is the worker + RAG.
 4. **Deferred work** — larger reasoner, custom Piper voice and other expansions.
 
 ## Non-goals (unchanged)
-Never phones home. Not a nag. Not autonomous. Feminine-gendered RU self-ref.
+Not a nag. Not autonomous. Feminine-gendered RU self-ref. No telemetry, no
+cloud model, no third-party account — but she MAY read external sources to
+answer world questions (Kiwix first, search optional). "Never phones home" as
+an absolute is deprecated, owner's call 2026-07-31; see CLAUDE.md § Non-goals.

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/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 == "" {

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

@@ -0,0 +1,116 @@
+// Package kiwix reads a local Kiwix server (offline Wikipedia and friends).
+//
+// Why: the resident model is a 0.8B and invents facts. Letting her read a local
+// article snippet beats letting her recall. Nothing here talks to the internet;
+// the Kiwix server is on the same box.
+//
+// This is search only. Full articles are ~100KB of HTML, far too big for a 4096
+// token context, so the unit of context is the search snippet (~500 chars).
+package kiwix
+
+import (
+	"context"
+	"encoding/xml"
+	"fmt"
+	"html"
+	"io"
+	"net/http"
+	"net/url"
+	"regexp"
+	"strconv"
+	"strings"
+	"time"
+)
+
+// Result is one search hit.
+type Result struct {
+	Title     string // article title, e.g. "Rayleigh scattering"
+	Path      string // e.g. /content/wikipedia_en_all_maxi_2026-02/Rayleigh_scattering
+	Snippet   string // plain text, tags stripped, entities decoded
+	WordCount int    // 0 if the server did not say
+}
+
+// Client is a Kiwix HTTP client. Boring on purpose: no retries, no cache.
+type Client struct {
+	base string
+	http *http.Client
+}
+
+// New makes a client for a Kiwix base URL like http://127.0.0.1:8034.
+func New(baseURL string) *Client {
+	return &Client{
+		base: strings.TrimRight(baseURL, "/"),
+		http: &http.Client{Timeout: 10 * time.Second},
+	}
+}
+
+// Search runs a keyword search in one ZIM (book) and returns up to limit hits.
+//
+// Ranking is keyword based, not semantic: "Rayleigh scattering" finds the right
+// article, "why is the sky blue" finds a TV episode. Pass keywords, not questions.
+func (c *Client) Search(ctx context.Context, pattern, book string, limit int) ([]Result, error) {
+	if limit <= 0 {
+		limit = 5
+	}
+	q := url.Values{}
+	q.Set("pattern", pattern)
+	q.Set("books.name", book)
+	q.Set("format", "xml")
+	q.Set("pageLength", strconv.Itoa(limit))
+
+	req, err := http.NewRequestWithContext(ctx, http.MethodGet, c.base+"/search?"+q.Encode(), nil)
+	if err != nil {
+		return nil, err
+	}
+	resp, err := c.http.Do(req)
+	if err != nil {
+		return nil, err
+	}
+	defer resp.Body.Close()
+	if resp.StatusCode != http.StatusOK {
+		return nil, fmt.Errorf("kiwix search: http %d", resp.StatusCode)
+	}
+	return ParseSearchRSS(resp.Body)
+}
+
+// rss mirrors just the bits of the RSS 2.0 reply we use.
+type rss struct {
+	Items []struct {
+		Title string `xml:"title"`
+		Link  string `xml:"link"`
+		// innerxml keeps the <b> match markers so we can strip them ourselves.
+		Description struct {
+			Inner string `xml:",innerxml"`
+		} `xml:"description"`
+		WordCount string `xml:"wordCount"`
+	} `xml:"channel>item"`
+}
+
+var tagRE = regexp.MustCompile(`<[^>]*>`)
+
+// ParseSearchRSS turns a Kiwix search reply into results. Exported so the parser
+// is testable from a captured response, with no server running.
+func ParseSearchRSS(r io.Reader) ([]Result, error) {
+	var doc rss
+	if err := xml.NewDecoder(r).Decode(&doc); err != nil {
+		return nil, fmt.Errorf("kiwix search: bad xml: %w", err)
+	}
+	out := make([]Result, 0, len(doc.Items))
+	for _, it := range doc.Items {
+		n, _ := strconv.Atoi(strings.ReplaceAll(it.WordCount, ",", ""))
+		out = append(out, Result{
+			Title:     strings.TrimSpace(it.Title),
+			Path:      strings.TrimSpace(it.Link),
+			Snippet:   plainText(it.Description.Inner),
+			WordCount: n,
+		})
+	}
+	return out, nil
+}
+
+// plainText drops markup and decodes entities, leaving text a model can read.
+func plainText(s string) string {
+	s = tagRE.ReplaceAllString(s, "")
+	s = html.UnescapeString(s)
+	return strings.TrimSpace(strings.Join(strings.Fields(s), " "))
+}

internal/kiwix/kiwix_test.go

@@ -0,0 +1,90 @@
+package kiwix
+
+import (
+	"context"
+	"os"
+	"strings"
+	"testing"
+	"time"
+)
+
+// A real reply from the live server, trimmed to two items.
+const sampleRSS = `<?xml version="1.0" encoding="UTF-8"?>
+<rss version="2.0" xmlns:opensearch="http://a9.com/-/spec/opensearch/1.1/">
+  <channel>
+    <title>Search: Rayleigh scattering</title>
+    <opensearch:totalResults>800</opensearch:totalResults>
+    <item>
+      <title>Rayleigh scattering</title>
+      <link>/content/wikipedia_en_all_maxi_2026-02/Rayleigh_scattering</link>
+      <description><b>Rayleigh</b> scattering causes the blue color of the sky &amp; yellow colors near the Sun.[1]</description>
+      <book><title>Wikipedia</title></book>
+      <wordCount>2,818</wordCount>
+    </item>
+    <item>
+      <title>Hyper–Rayleigh scattering</title>
+      <link>/content/wikipedia_en_all_maxi_2026-02/Hyper%E2%80%93Rayleigh_scattering</link>
+      <description>...<b>Rayleigh</b> scattering" is a nonlinear optical counterpart.</description>
+      <book><title>Wikipedia</title></book>
+      <wordCount>914</wordCount>
+    </item>
+  </channel>
+</rss>`
+
+func TestParseSearchRSS(t *testing.T) {
+	got, err := ParseSearchRSS(strings.NewReader(sampleRSS))
+	if err != nil {
+		t.Fatalf("parse: %v", err)
+	}
+	if len(got) != 2 {
+		t.Fatalf("want 2 results, got %d", len(got))
+	}
+	if got[0].Title != "Rayleigh scattering" {
+		t.Errorf("title = %q", got[0].Title)
+	}
+	if got[0].Path != "/content/wikipedia_en_all_maxi_2026-02/Rayleigh_scattering" {
+		t.Errorf("path = %q", got[0].Path)
+	}
+	if got[0].WordCount != 2818 {
+		t.Errorf("wordCount = %d", got[0].WordCount)
+	}
+	want := "Rayleigh scattering causes the blue color of the sky & yellow colors near the Sun.[1]"
+	if got[0].Snippet != want {
+		t.Errorf("snippet = %q, want %q", got[0].Snippet, want)
+	}
+	if strings.Contains(got[1].Snippet, "<b>") {
+		t.Errorf("second snippet still has tags: %q", got[1].Snippet)
+	}
+}
+
+func TestParseSearchRSSBadXML(t *testing.T) {
+	if _, err := ParseSearchRSS(strings.NewReader("not xml at all")); err == nil {
+		t.Fatal("want an error on junk input")
+	}
+}
+
+// Opt-in: needs a live Kiwix server. CI has none.
+// MAVEN_KIWIX_URL=http://127.0.0.1:8034 no_proxy=127.0.0.1,localhost go test -run Retrieval -v ./internal/kiwix/
+func TestRetrievalEval(t *testing.T) {
+	base := os.Getenv("MAVEN_KIWIX_URL")
+	if base == "" {
+		t.Skip("set MAVEN_KIWIX_URL to run the retrieval eval")
+	}
+	noProxyLoopback(t)
+
+	ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute)
+	defer cancel()
+
+	rep, err := RunRetrievalEval(ctx, New(base), 5)
+	if err != nil {
+		t.Fatalf("eval: %v", err)
+	}
+	// No pass bar on purpose: the number is the finding.
+	t.Log("\n" + rep.String() + rep.Detail())
+}
+
+// noProxyLoopback stops the box's SOCKS bridge from eating loopback requests.
+func noProxyLoopback(t *testing.T) {
+	t.Setenv("no_proxy", "127.0.0.1,localhost")
+	t.Setenv("NO_PROXY", "127.0.0.1,localhost")
+}

internal/kiwix/knowledge_v1.json

@@ -0,0 +1,63 @@
+{
+  "name": "kiwix-knowledge-v1",
+  "book": "wikipedia_en_all_maxi_2026-02",
+  "note": "The 9 knowledge cases from internal/phraser/eval/talk_v1.json. Queries are hand-written English keywords on purpose: Kiwix ranks by keyword, not meaning, so a natural question fails. Writing them by hand separates 'retrieval is broken' from 'the model writes bad queries'.",
+  "cases": [
+    {
+      "id": "know-sky-blue",
+      "question": "почему небо синее?",
+      "query": "Rayleigh scattering sky blue",
+      "want_titles": ["Rayleigh scattering", "Diffuse sky radiation"]
+    },
+    {
+      "id": "know-boil-egg",
+      "question": "сколько варить яйцо вкрутую?",
+      "query": "boiled egg cooking",
+      "want_titles": ["Boiled egg", "Egg as food"]
+    },
+    {
+      "id": "know-ssd-vs-hdd",
+      "question": "чем ssd отличается от hdd?",
+      "query": "solid-state drive",
+      "want_titles": ["Solid-state drive", "Hard disk drive"]
+    },
+    {
+      "id": "know-cat-purr",
+      "question": "почему кошки мурчат?",
+      "query": "cat purr",
+      "want_titles": ["Purr", "Cat communication"]
+    },
+    {
+      "id": "know-hiccups",
+      "question": "как быстро избавиться от икоты?",
+      "query": "hiccup",
+      "want_titles": ["Hiccup"]
+    },
+    {
+      "id": "know-polite-form",
+      "question": "не могли бы вы объяснить, что такое vpn?",
+      "query": "virtual private network",
+      "want_titles": ["Virtual private network"]
+    },
+    {
+      "id": "know-dont-know",
+      "question": "как зовут моего соседа снизу?",
+      "query": "name of my downstairs neighbour",
+      "want_titles": [],
+      "expect_miss": true,
+      "note": "Unanswerable by design. Retrieval SHOULD find nothing useful. Counted as a hit only when nothing relevant comes back."
+    },
+    {
+      "id": "know-water-per-day",
+      "question": "сколько воды в день надо пить?",
+      "query": "human daily water requirement drinking",
+      "want_titles": ["Drinking water", "Water", "Dehydration", "Hydration"]
+    },
+    {
+      "id": "know-thunder-delay",
+      "question": "почему гром слышно позже молнии?",
+      "query": "thunder speed of sound lightning",
+      "want_titles": ["Thunder", "Lightning"]
+    }
+  ]
+}

internal/kiwix/retrieval_eval.go

@@ -0,0 +1,135 @@
+package kiwix
+
+// This scores retrieval alone: no LLM. For each general-knowledge question we
+// hand-write English keywords and ask whether the article that would answer it
+// comes back in the top N hits. If this score is low, reading Wikipedia cannot
+// help the model no matter how good the prompt is.
+//
+// The unanswerable case (know-dont-know) is not scored. Whether the junk it
+// returns is "nothing useful" is a human judgement, so the report just prints
+// the titles and leaves the score to the 8 answerable cases.
+
+import (
+	"context"
+	_ "embed"
+	"encoding/json"
+	"fmt"
+	"strings"
+)
+
+//go:embed knowledge_v1.json
+var knowledgeFixtureJSON []byte
+
+// EvalCase — one question with hand-written keywords.
+type EvalCase struct {
+	ID         string   `json:"id"`
+	Question   string   `json:"question"`
+	Query      string   `json:"query"`
+	WantTitles []string `json:"want_titles"`
+	ExpectMiss bool     `json:"expect_miss"`
+}
+
+type fixture struct {
+	Name  string     `json:"name"`
+	Book  string     `json:"book"`
+	Cases []EvalCase `json:"cases"`
+}
+
+// Outcome — what one case retrieved.
+type Outcome struct {
+	Case   EvalCase
+	Titles []string // titles of the top N hits, in rank order
+	Rank   int      // 1-based rank of the first wanted title, 0 if none
+	Err    error
+}
+
+// Hit is true when a wanted title came back.
+func (o Outcome) Hit() bool { return o.Rank > 0 }
+
+// Report — the score plus per-case detail.
+type Report struct {
+	Name     string
+	Book     string
+	TopN     int
+	Scored   int // answerable cases
+	Hits     int
+	Errors   int
+	Outcomes []Outcome
+}
+
+// Accuracy over the answerable cases.
+func (r Report) Accuracy() float64 {
+	if r.Scored == 0 {
+		return 0
+	}
+	return float64(r.Hits) / float64(r.Scored)
+}
+
+// RunRetrievalEval searches for every fixture case.
+func RunRetrievalEval(ctx context.Context, c *Client, topN int) (Report, error) {
+	var f fixture
+	if err := json.Unmarshal(knowledgeFixtureJSON, &f); err != nil {
+		return Report{}, err
+	}
+	rep := Report{Name: f.Name, Book: f.Book, TopN: topN}
+	for _, cs := range f.Cases {
+		res, err := c.Search(ctx, cs.Query, f.Book, topN)
+		o := Outcome{Case: cs, Err: err}
+		if err != nil {
+			rep.Errors++
+		}
+		for i, hit := range res {
+			o.Titles = append(o.Titles, hit.Title)
+			if o.Rank == 0 && matches(cs.WantTitles, hit.Title) {
+				o.Rank = i + 1
+			}
+		}
+		if !cs.ExpectMiss {
+			rep.Scored++
+			if o.Hit() {
+				rep.Hits++
+			}
+		}
+		rep.Outcomes = append(rep.Outcomes, o)
+	}
+	return rep, nil
+}
+
+func matches(want []string, title string) bool {
+	for _, w := range want {
+		if strings.EqualFold(strings.TrimSpace(title), w) {
+			return true
+		}
+	}
+	return false
+}
+
+// String — the headline number.
+func (r Report) String() string {
+	var b strings.Builder
+	fmt.Fprintf(&b, "%s: %d/%d answerable questions retrieve a wanted article in top %d (%.1f%%), %d errors\n",
+		r.Name, r.Hits, r.Scored, r.TopN, 100*r.Accuracy(), r.Errors)
+	fmt.Fprintf(&b, "  book: %s\n", r.Book)
+	return b.String()
+}
+
+// Detail — per case: what was asked, what was searched, what came back.
+func (r Report) Detail() string {
+	var b strings.Builder
+	for _, o := range r.Outcomes {
+		mark := "MISS"
+		switch {
+		case o.Case.ExpectMiss:
+			mark = "n/a "
+		case o.Hit():
+			mark = fmt.Sprintf("hit@%d", o.Rank)
+		}
+		fmt.Fprintf(&b, "  %-6s %-20s q=%q\n", mark, o.Case.ID, o.Case.Query)
+		if o.Err != nil {
+			fmt.Fprintf(&b, "         error: %v\n", o.Err)
+			continue
+		}
+		fmt.Fprintf(&b, "         got: %s\n", strings.Join(o.Titles, " | "))
+	}
+	return b.String()
+}

internal/kiwix/rewrite.go

@@ -0,0 +1,183 @@
+package kiwix
+
+// Turning a Russian question into an English Kiwix search.
+//
+// Kiwix ranks by keyword, not by meaning. "why is the sky blue" returns a TV
+// episode; "Rayleigh scattering sky blue" returns the right article. So the
+// model's job here is NOT translation — it is naming the English article the
+// answer lives in.
+//
+// The output space is a handful of words, so it is worth locking down hard: a
+// GBNF grammar for the shape, a tiny token cap, and a cleanup pass that throws
+// away anything odd rather than handing junk to Kiwix.
+
+import (
+	"context"
+	"encoding/json"
+	"fmt"
+	"strings"
+	"unicode"
+
+	"github.com/kami/maven/internal/llm"
+)
+
+// Completer — the LLM seam, so tests can fake it. *llm.Client satisfies it.
+type Completer interface {
+	Complete(ctx context.Context, r llm.Req) (string, error)
+}
+
+// queryGrammar — one JSON object holding 1..6 keyword words. Latin letters,
+// digits and hyphens only, so the model physically cannot answer the question
+// or reply in Russian.
+//
+// Why the JSON wrapper: this model always thinks out loud and this llama-server
+// build ignores the thinking switch (see ROUTING-EVAL-31-07-2026.md). A bare
+// word-list grammar just captured the reasoning — every case came back as
+// "Let me analyze this request carefully". Demanding JSON, like routeGrammar and
+// responseGrammar already do, gives the reasoning nowhere to go.
+const queryGrammar = `
+root ::= "{" ws "\"query\"" ws ":" ws "\"" word (" " word){0,5} "\"" ws "}"
+word ::= [A-Za-z0-9] [A-Za-z0-9-]{0,23}
+ws   ::= [ \t\n]*
+`
+
+// rewriteSystem — asks for search keywords, not an answer and not a translation.
+const rewriteSystem = `You turn a question into a search query for English Wikipedia.
+
+Rules:
+- Output ONLY English search keywords. Never an answer, never an explanation.
+- Do NOT translate the sentence. Name the thing the answer is about.
+- The output must be a noun phrase, like a Wikipedia article title.
+- Never use question words: no why, how, what, when, which, "how much",
+  "how long", "how to", "vs", "reason", "difference".
+- 2 to 4 words.
+
+Reply with JSON: {"query":"<keywords>"}
+
+Good:
+"почему листья желтеют осенью?" -> {"query":"leaf senescence autumn"}
+"как работает микроволновка?" -> {"query":"microwave oven"}
+"не могли бы вы объяснить, что такое блокчейн?" -> {"query":"blockchain"}
+"сколько живут собаки?" -> {"query":"dog lifespan"}
+"как избавиться от комаров в квартире?" -> {"query":"mosquito control"}
+"чем чай отличается от кофе?" -> {"query":"tea"}
+
+Only JSON, no explanation.`
+
+// maxQueryTokens — the output is a few words plus the JSON wrapper. A tight cap
+// is the cheapest guard against the model rambling into an answer.
+const maxQueryTokens = 32
+
+// Rewriter asks the resident model for English search keywords.
+type Rewriter struct{ c Completer }
+
+func NewRewriter(c Completer) *Rewriter { return &Rewriter{c: c} }
+
+// Rewrite returns English keywords for a question in any language.
+// It errors rather than returning something Kiwix should not see.
+func (r *Rewriter) Rewrite(ctx context.Context, question string) (string, error) {
+	raw, err := r.c.Complete(ctx, llm.Req{
+		System:        rewriteSystem,
+		User:          strings.TrimSpace(question),
+		Grammar:       queryGrammar,
+		MaxTokens:     maxQueryTokens,
+		RepeatPenalty: 1.15,
+	})
+	if err != nil {
+		return "", err
+	}
+	return CleanQuery(unwrapJSON(raw))
+}
+
+// unwrapJSON pulls the query out of {"query":"..."}. If the reply is not that
+// shape it is returned as-is, and CleanQuery decides whether it is usable.
+func unwrapJSON(raw string) string {
+	s := strings.TrimSpace(raw)
+	if !strings.HasPrefix(s, "{") {
+		return s
+	}
+	var got struct{ Query string }
+	if err := json.Unmarshal([]byte(s), &got); err != nil {
+		return s
+	}
+	return got.Query
+}
+
+// maxQueryWords matches the grammar's bound. Anything longer is prose.
+const maxQueryWords = 6
+
+// CleanQuery checks and tidies whatever the model produced. The grammar makes
+// bad output unlikely, not impossible (a server without grammar support, a
+// different model), so this is the real gate in front of Kiwix.
+//
+// Exported so it can be tested without a model.
+func CleanQuery(raw string) (string, error) {
+	s := strings.TrimSpace(raw)
+	// Models like to wrap answers in quotes. Drop surrounding ones.
+	s = strings.Trim(s, "\"'`")
+	// Keep the first line only: everything after it is prose.
+	if i := strings.IndexAny(s, "\r\n"); i >= 0 {
+		s = s[:i]
+	}
+	// Keep letters, digits, spaces and hyphens; anything else becomes a space.
+	var b strings.Builder
+	for _, ru := range s {
+		switch {
+		case unicode.IsLetter(ru) || unicode.IsDigit(ru) || ru == '-':
+			b.WriteRune(ru)
+		default:
+			b.WriteRune(' ')
+		}
+	}
+	words := strings.Fields(b.String())
+	if len(words) == 0 {
+		return "", fmt.Errorf("kiwix rewrite: empty query")
+	}
+	if len(words) > maxQueryWords {
+		return "", fmt.Errorf("kiwix rewrite: %d words, want at most %d (looks like prose)", len(words), maxQueryWords)
+	}
+	words = dropStopWords(words)
+	out := strings.Join(words, " ")
+	// The ZIMs are English. Non-Latin letters mean the model ignored the ask.
+	for _, ru := range out {
+		if unicode.IsLetter(ru) && !isLatin(ru) {
+			return "", fmt.Errorf("kiwix rewrite: query is not English: %q", out)
+		}
+	}
+	return out, nil
+}
+
+// stopWords — question words and filler. The model keeps writing question-shaped
+// queries ("why is the sky blue", "how much water to drink daily") no matter how
+// the prompt is worded, and Kiwix ranks on every word, so those words drag in
+// song and episode titles. Dropping them in code is not a style preference: a
+// keyword ranker gets nothing from them.
+var stopWords = map[string]bool{
+	"a": true, "an": true, "the": true, "is": true, "are": true, "was": true,
+	"do": true, "does": true, "did": true, "to": true, "of": true, "in": true,
+	"on": true, "for": true, "and": true, "or": true, "my": true, "me": true,
+	"i": true, "it": true, "its": true, "be": true, "been": true, "get": true,
+	"how": true, "why": true, "what": true, "when": true, "which": true,
+	"who": true, "where": true, "much": true, "many": true, "long": true,
+	"vs": true, "than": true, "rid": true, "from": true, "about": true,
+}
+
+// dropStopWords removes filler, but never everything: if the query was nothing
+// but stop words there is nothing better to search, so the original is kept and
+// the caller sees whatever Kiwix makes of it.
+func dropStopWords(words []string) []string {
+	kept := make([]string, 0, len(words))
+	for _, w := range words {
+		if !stopWords[strings.ToLower(w)] {
+			kept = append(kept, w)
+		}
+	}
+	if len(kept) == 0 {
+		return words
+	}
+	return kept
+}
+
+func isLatin(ru rune) bool {
+	return (ru >= 'a' && ru <= 'z') || (ru >= 'A' && ru <= 'Z')
+}

internal/kiwix/rewrite_eval.go

@@ -0,0 +1,96 @@
+package kiwix
+
+// End-to-end score: Russian question -> model rewrite -> Kiwix search -> did a
+// wanted article come back. Same 9 cases as the retrieval eval, so the two
+// numbers are directly comparable: retrieval with hand-written keywords is the
+// ceiling, this is what the model actually reaches.
+
+import (
+	"context"
+	"encoding/json"
+	"fmt"
+	"strings"
+)
+
+// RewriteOutcome — one case, end to end.
+type RewriteOutcome struct {
+	Outcome
+	ModelQuery string // what the model asked for ("" if it failed)
+	RewriteErr error
+}
+
+// RunRewriteEval rewrites every question with the model, then searches.
+func RunRewriteEval(ctx context.Context, c *Client, rw *Rewriter, topN int) (RewriteReport, error) {
+	var f fixture
+	if err := json.Unmarshal(knowledgeFixtureJSON, &f); err != nil {
+		return RewriteReport{}, err
+	}
+	rep := RewriteReport{Report: Report{Name: f.Name + "-rewrite", Book: f.Book, TopN: topN}}
+	for _, cs := range f.Cases {
+		out := RewriteOutcome{Outcome: Outcome{Case: cs}}
+		q, err := rw.Rewrite(ctx, cs.Question)
+		out.ModelQuery, out.RewriteErr = q, err
+		if err == nil {
+			res, serr := c.Search(ctx, q, f.Book, topN)
+			out.Err = serr
+			for i, hit := range res {
+				out.Titles = append(out.Titles, hit.Title)
+				if out.Rank == 0 && matches(cs.WantTitles, hit.Title) {
+					out.Rank = i + 1
+				}
+			}
+		}
+		if out.RewriteErr != nil || out.Err != nil {
+			rep.Errors++
+		}
+		if !cs.ExpectMiss {
+			rep.Scored++
+			if out.Hit() {
+				rep.Hits++
+			}
+		}
+		rep.Cases = append(rep.Cases, out)
+	}
+	return rep, nil
+}
+
+// RewriteReport — the score plus per-case detail.
+type RewriteReport struct {
+	Report
+	Cases []RewriteOutcome
+}
+
+// String — the headline number.
+func (r RewriteReport) String() string {
+	return fmt.Sprintf("%s: %d/%d answerable questions retrieve a wanted article in top %d (%.1f%%), %d errors\n  book: %s\n",
+		r.Name, r.Hits, r.Scored, r.TopN, 100*r.Accuracy(), r.Errors, r.Book)
+}
+
+// Detail — per case: hand-written query next to the model's, and what came back.
+// The point is seeing WHERE the model's phrasing differs, not just the score.
+func (r RewriteReport) Detail() string {
+	var b strings.Builder
+	for _, o := range r.Cases {
+		mark := "MISS"
+		switch {
+		case o.Case.ExpectMiss:
+			mark = "n/a "
+		case o.Hit():
+			mark = fmt.Sprintf("hit@%d", o.Rank)
+		}
+		fmt.Fprintf(&b, "  %-6s %-20s\n", mark, o.Case.ID)
+		fmt.Fprintf(&b, "         asked:  %s\n", o.Case.Question)
+		fmt.Fprintf(&b, "         hand:   %q\n", o.Case.Query)
+		fmt.Fprintf(&b, "         model:  %q\n", o.ModelQuery)
+		if o.RewriteErr != nil {
+			fmt.Fprintf(&b, "         rewrite rejected: %v\n", o.RewriteErr)
+			continue
+		}
+		if o.Err != nil {
+			fmt.Fprintf(&b, "         search error: %v\n", o.Err)
+			continue
+		}
+		fmt.Fprintf(&b, "         got:    %s\n", strings.Join(o.Titles, " | "))
+	}
+	return b.String()
+}

internal/kiwix/rewrite_eval_test.go

@@ -0,0 +1,33 @@
+package kiwix
+
+import (
+	"context"
+	"os"
+	"testing"
+	"time"
+
+	"github.com/kami/maven/internal/llm"
+)
+
+// Opt-in: needs a live Kiwix server AND a live llama-server.
+// MAVEN_KIWIX_URL=http://127.0.0.1:8034 MAVEN_LLM_URL=http://127.0.0.1:18099 \
+//
+//	no_proxy=127.0.0.1,localhost go test -run RewriteEval -v ./internal/kiwix/
+func TestRewriteEval(t *testing.T) {
+	kbase, lbase := os.Getenv("MAVEN_KIWIX_URL"), os.Getenv("MAVEN_LLM_URL")
+	if kbase == "" || lbase == "" {
+		t.Skip("set MAVEN_KIWIX_URL and MAVEN_LLM_URL to run the rewrite eval")
+	}
+	noProxyLoopback(t)
+
+	ctx, cancel := context.WithTimeout(context.Background(), 15*time.Minute)
+	defer cancel()
+
+	rw := NewRewriter(llm.New(lbase, 3*time.Minute))
+	rep, err := RunRewriteEval(ctx, New(kbase), rw, 5)
+	if err != nil {
+		t.Fatalf("eval: %v", err)
+	}
+	// No pass bar on purpose: the number is the finding.
+	t.Log("\n" + rep.String() + rep.Detail())
+}

internal/kiwix/rewrite_test.go

@@ -0,0 +1,105 @@
+package kiwix
+
+import (
+	"context"
+	"testing"
+
+	"github.com/kami/maven/internal/llm"
+)
+
+// Bad model output must never reach Kiwix. No model needed for this.
+func TestCleanQueryRejectsJunk(t *testing.T) {
+	bad := []struct{ name, raw string }{
+		{"empty", ""},
+		{"blank", "   \n  "},
+		{"russian came back", "почему небо синее"},
+		{"mixed russian", "sky синее scattering"},
+		{"full sentence", "The sky looks blue because of the scattering of sunlight by air molecules"},
+		{"prose with quotes", `Sure! Here is a good search query: "Rayleigh scattering", which explains it.`},
+	}
+	for _, c := range bad {
+		if got, err := CleanQuery(c.raw); err == nil {
+			t.Errorf("%s: want rejection, got %q", c.name, got)
+		}
+	}
+}
+
+func TestCleanQueryCleans(t *testing.T) {
+	ok := []struct{ raw, want string }{
+		{"Rayleigh scattering sky", "Rayleigh scattering sky"},
+		{"  boiled   egg  cooking \n", "boiled egg cooking"},
+		{`"virtual private network"`, "virtual private network"},
+		{"solid-state drive", "solid-state drive"},
+		{"cat purr.", "cat purr"},
+		{"hiccup\nAlso: hiccough", "hiccup"},
+		// Question words are filler to a keyword ranker, so they go.
+		{"why is the sky blue", "sky blue"},
+		{"how much water to drink daily", "water drink daily"},
+		{"SSD vs HDD comparison", "SSD HDD comparison"},
+		// Nothing but filler: keep it rather than return nothing.
+		{"what is it", "what is it"},
+	}
+	for _, c := range ok {
+		got, err := CleanQuery(c.raw)
+		if err != nil {
+			t.Errorf("%q: %v", c.raw, err)
+			continue
+		}
+		if got != c.want {
+			t.Errorf("%q -> %q, want %q", c.raw, got, c.want)
+		}
+	}
+}
+
+type fakeCompleter struct {
+	out string
+	req llm.Req
+}
+
+func (f *fakeCompleter) Complete(_ context.Context, r llm.Req) (string, error) {
+	f.req = r
+	return f.out, nil
+}
+
+func TestRewriteConstrainsTheCall(t *testing.T) {
+	f := &fakeCompleter{out: `{"query":"Rayleigh scattering sky"}`}
+	got, err := NewRewriter(f).Rewrite(context.Background(), "почему небо синее?")
+	if err != nil {
+		t.Fatalf("rewrite: %v", err)
+	}
+	if got != "Rayleigh scattering sky" {
+		t.Errorf("query = %q", got)
+	}
+	if f.req.Grammar == "" {
+		t.Error("no grammar sent")
+	}
+	if f.req.MaxTokens == 0 || f.req.MaxTokens > 32 {
+		t.Errorf("max_tokens = %d, want a small cap", f.req.MaxTokens)
+	}
+}
+
+func TestRewriteRejectsBadModelOutput(t *testing.T) {
+	bad := []string{
+		`{"query":"почему небо синее"}`, // never translated
+		`{"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
+		// stops that one.
+	}
+	for _, out := range bad {
+		f := &fakeCompleter{out: out}
+		if got, err := NewRewriter(f).Rewrite(context.Background(), "почему небо синее?"); err == nil {
+			t.Errorf("%s: want rejection, got %q", out, got)
+		}
+	}
+}
+
+// A reply that is not the JSON shape but is still usable keywords should pass.
+func TestRewriteFallsBackToPlainText(t *testing.T) {
+	f := &fakeCompleter{out: "Rayleigh scattering sky"}
+	got, err := NewRewriter(f).Rewrite(context.Background(), "почему небо синее?")
+	if err != nil || got != "Rayleigh scattering sky" {
+		t.Errorf("got %q, %v", got, err)
+	}
+}

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]*
 `
 
@@ -507,7 +575,9 @@ 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 +699,39 @@ 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."
+      ]
+    }
+  }
+}