feat: plan agent v2, global chat mode, and user-mode v2 flag sync

- Add runtime/plan_agent_v2 package and shims; gateway/direct_loop/WS wiring

- Admin chat: interaction mode and specialist only in user menu; session API stores memory_mode and execution_mode only

- POST /admin/api/chat/user-mode mirrors plan_agent_version to AIA_EXPERT_PLAN_AGENT_V2_ENABLED (v2 to 1, v1 to 0)

- Composer cleanup (hidden mode select, no reasoning toggle in meta bar); tests and _local/system.env.example

Co-authored-by: Cursor <cursoragent@cursor.com>

runtime/plan_agent_v2/gateway_adapter.py

@@ -0,0 +1,54 @@
+from __future__ import annotations
+
+from dataclasses import dataclass
+from typing import Any
+
+from .adapter import PlanAgentV2Decision, evaluate_for_expert_mode
+from .switch import should_route_to_v2
+from oclaw.runtime.types import StandardMessage
+
+
+@dataclass(frozen=True)
+class GatewayPlanV2AdapterOutput:
+    used_v2: bool
+    decision: PlanAgentV2Decision | None
+
+
+def evaluate_gateway_expert_turn_shadow(
+    *,
+    store: Any,
+    msg: StandardMessage,
+    lang: str,
+    interaction_mode: str,
+    requested_specialist: str,
+    execution_mode: str = "",
+    base_system_prompt: str,
+    force_flag: bool = False,
+    trace_id: str | None = None,
+    parent_span_id: str | None = None,
+) -> GatewayPlanV2AdapterOutput:
+    if not should_route_to_v2(store=store, interaction_mode=interaction_mode, force_flag=force_flag):
+        return GatewayPlanV2AdapterOutput(used_v2=False, decision=None)
+    meta = msg.metadata if isinstance(msg.metadata, dict) else {}
+    if "plan_agent_version" in meta:
+        if str(meta.get("plan_agent_version") or "").strip().lower() != "v2":
+            return GatewayPlanV2AdapterOutput(used_v2=False, decision=None)
+    eff_mode = str(execution_mode or "").strip().lower()
+    if eff_mode not in {"agent", "plan"}:
+        eff_mode = "plan" if force_flag else "agent"
+    dec = evaluate_for_expert_mode(
+        store=store,
+        session_id=str(msg.session_id or ""),
+        lang=lang,
+        requested_specialist=requested_specialist,
+        user_text=str(msg.text or ""),
+        execution_mode=eff_mode,
+        base_system_prompt=base_system_prompt,
+        trace_id=trace_id,
+        parent_span_id=parent_span_id,
+    )
+    return GatewayPlanV2AdapterOutput(used_v2=True, decision=dec)
+
+
+__all__ = ["GatewayPlanV2AdapterOutput", "evaluate_gateway_expert_turn_shadow"]
+