feat: {response,mood} output contract + router removal, TTS piper plan

Daemon side of Decision B: parse {"response","mood"} across the 4 consumers
(replier, nudges, reminders, chat), fall back to legacy formats. Drop the
LLM router — the classifier handles routing; replier/phraser share one
llm.Client (timeout 20s->60s). llm.Client reads reasoning_content when
content is empty (thinking models).

Docs: TTS piper-student plan (OmniVoice teacher -> piper student, from
scratch, phoneme-first). CLAUDE.md training guide.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

AGENTS.md

@@ -74,7 +74,7 @@ sudo cp onnxruntime-linux-x64-1.15.1/lib/libonnxruntime.so* /usr/local/lib/
 Without the embedder block, the daemon uses `HashEmbedder` (works, but weak on
 Russian recall — you may see many "clarify" responses).
 
-## LFM model for router + phraser
+## LFM model for router + phraser (Thinking variant)
 
 The daemon uses a single resident LFM (sub-1B) for both routing (intent
 classification + slot extraction) and phrasing (nudges, reminders, reactive
@@ -90,8 +90,8 @@ make download-llm
 Or manually:
 
 ```sh
-curl -sL "https://huggingface.co/lfm/LFM2.5-1.2B-Instruct-GGUF/resolve/main/LFM2.5-1.2B-Instruct-Q4_K_M.gguf" \
-  -o models/llm/LFM2.5-1.2B-Instruct-Q4_K_M.gguf
+curl -sL "https://huggingface.co/lfm/LFM2.5-1.2B-Thinking-GGUF/resolve/main/LFM2.5-1.2B-Thinking-Q4_K_M.gguf" \
+  -o models/llm/LFM2.5-1.2B-Thinking-Q4_K_M.gguf
 ```
 
 **Configure in `deploy/mavend.json`** — the `phraser` block points at this