perf: conversational fast-path (skip enrichment) + shorter silence wait

Greetings/small-talk routed no data tool yet still ran the episodic memory
enrichment (LLM keyword extract + diary/graph search, ~1s) every turn. Skip it
when the router picked no external-data tool — the always-injected warm profile
still personalises the reply. Also drop the voice silence-detection wait
800ms -> 600ms for snappier turn-taking. Warm "안녕" now lands well under the
3-4s target.

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

docker-compose.yml

@@ -77,6 +77,7 @@ services:
       PLANNER_ENABLED: ${PLANNER_ENABLED:-0}
       # Lock STT to Korean (skip Whisper auto-detect).
       STT_LANGUAGE: ${STT_LANGUAGE:-ko}
+      VOICE_SILENCE_MS: ${VOICE_SILENCE_MS:-600}
       BRIDGE_URL: http://127.0.0.1:8765
     depends_on:
       - ollama

src/jarvis/reply/engine.py

@@ -1027,6 +1027,19 @@ def run_reply_engine(db: "Database", cfg, tts: Optional[Any],
                 "planning",
             )
 
+    # Conversational fast-path signal: did the router pick any tool that needs
+    # EXTERNAL DATA? Captured BEFORE the screen-share unions below add browser
+    # tools to every turn. When nothing data-bearing was routed (greetings,
+    # small talk, behavioural instructions), the episodic memory enrichment
+    # (LLM keyword extract + diary/graph search) is pure latency — the warm
+    # profile already carries the user's identity/interests in the prompt. Used
+    # at the needs_memory gate to skip enrichment for those turns.
+    _DATA_TOOLS = {
+        "webSearch", "getWeather", "fetchWebPage", "fetchMeals", "logMeal",
+        "deleteMeal", "localFiles", "controlBrowser", "browseAndPlay", "screenshot",
+    }
+    _router_wants_data = any(t in routed_tools for t in _DATA_TOOLS)
+
     # In screen-share mode, always offer setBroadcast. "Turn the broadcast
     # on/off" is language-agnostic intent the embedding/keyword router won't
     # reliably surface for a non-English utterance (e.g. "방송 꺼줘"), so the
@@ -1118,6 +1131,15 @@ def run_reply_engine(db: "Database", cfg, tts: Optional[Any],
                 needs_memory = False
         except Exception as exc:  # noqa: BLE001
             debug_log(f"recall gate failed (fail-open): {exc}", "memory")
+
+    # Conversational fast-path: when the router routed NO external-data tool,
+    # this is a greeting / small-talk / behavioural-instruction turn. Skip the
+    # episodic enrichment (LLM keyword extract + diary/graph vector search) —
+    # the always-injected warm profile still personalises the reply, and this
+    # shaves ~1s off the most common (and latency-sensitive) voice turns.
+    if needs_memory and not plan_demands_memory and not _router_wants_data:
+        debug_log("fast-path: no data tool routed — skipping episodic enrichment", "memory")
+        needs_memory = False
     # Topic hint from the directive (if any) — passed to the memory
     # extractor so keyword selection is anchored on what the planner
     # actually wanted to look up, instead of re-deriving from the raw