perf(brain): switch voice brain to Sonnet 5 with an always-on brevity rule

Sonnet 5 reaches first token ~0.4s sooner than Sonnet 4.5 but answers the
same voice prompt more verbosely (measured 46-54 vs ~28 output tokens),
which erased the win in total turn time. Add a cached, persona-independent
brevity system block that pulls output back to ~30 tokens, so the faster
first token becomes a faster, lower-variance whole reply.

Measured (16-round interleaved A/B, production-shaped call):
  sonnet-4-5      TTFT 1.26s  total 2.02s (tail 3.26s)  out 29
  sonnet-5+brev   TTFT 0.85s  total 1.70s (tail 2.28s)  out 30

- ClaudeBrain: default model claude-sonnet-5 + BREVITY block (cached with
  the persona prefix so a dashboard persona edit can't drop it).
- Defaults aligned: config.Settings.anthropic_model and the voice-server
  WSAI_BRAIN_MODEL default -> claude-sonnet-5.
- Dashboard: add claude-sonnet-5 to LLM_OPTIONS + JS label; fix stale
  restart hint.
- tests/latency_ab.py: reproducible model-latency A/B harness (reads
  CLAUDE_CREDENTIALS_PATH; makes live API calls, so not a pytest test).

Streaming TTS was intentionally not added: this bot answers in one sentence,
where sentence-level streaming has no overlap to exploit, and it would
require rearchitecting both the Python endpoint and the node playback.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

wsai/__main__.py

@@ -142,7 +142,7 @@ def _run_voice_server(host: str, port: int) -> None:
     if os.environ.get("WSAI_BRAIN", "claude").lower() not in ("none", "echo"):
         try:
             from .backends.claude import ClaudeBrain
-            model = os.environ.get("WSAI_BRAIN_MODEL", "claude-sonnet-4-5")
+            model = os.environ.get("WSAI_BRAIN_MODEL", "claude-sonnet-5")
             brain = ClaudeBrain(model=model)
             brain_name = "claude"
         except Exception as exc:  # noqa: BLE001