feat(mcp-phase4a): NemoClaw second opinion — 信心 < 0.7 觸發 deepseek-r1:14b 複審

- _nemoclaw_second_opinion(): 呼叫 Ollama 188 deepseek-r1:14b 做獨立推理
  - 解析 <think>...</think> CoT 格式，只取正文
  - 30s timeout，失敗靜默降級
  - 輸出截斷 300 字
- _dual_engine_analyze(): LLM 信心 < 0.7 時非同步觸發 second opinion
  - 結果附加到 proposal_data["advisory_note"]
- _push_decision_to_telegram(): advisory_note 以 NemoClaw bot 身分追加訊息
  - 格式: "NemoClaw 第二意見 (信心=0.xx)"

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

apps/api/src/services/decision_manager.py

@@ -240,6 +240,17 @@ async def _push_decision_to_telegram(
         # 非同步執行，不阻塞主流程
         asyncio.create_task(_send_log_summary(incident))
 
+        # MCP Phase 4a: NemoClaw second opinion (2026-04-11 Claude Sonnet 4.6)
+        # 若 proposal_data 有 advisory_note，用 NemoClaw bot 身分追加一條訊息
+        _advisory_note = proposal_data.get("advisory_note", "")
+        if _advisory_note:
+            asyncio.create_task(
+                gateway.send_as_nemotron(
+                    f"🤔 <b>NemoClaw 第二意見</b> (信心={confidence:.2f})\n"
+                    f"<i>{_advisory_note}</i>"
+                )
+            )
+
         # 🔴 發送成功後設置去重 key (TTL 10 分鐘)
         await redis.setex(dedup_key, 600, "1")
 
@@ -259,6 +270,62 @@ async def _push_decision_to_telegram(
         )
 
 
+async def _nemoclaw_second_opinion(incident: "Incident", primary_result: dict) -> str | None:
+    """
+    MCP Phase 4a: NemoClaw second opinion — 信心 < 0.7 時觸發
+    ============================================================
+    用 deepseek-r1:14b (Ollama 188) 對同一份資料做獨立推理，
+    輸出純文字 advisory_note，不執行任何操作。
+
+    2026-04-11 Claude Sonnet 4.6 Asia/Taipei
+    """
+    try:
+        from src.core.config import settings
+        import httpx as _httpx
+
+        ollama_url = getattr(settings, "OLLAMA_URL", "http://192.168.0.188:11434")
+        model = "deepseek-r1:14b"
+
+        signals_summary = ""
+        if incident.signals:
+            lbl = incident.signals[0].labels
+            signals_summary = (
+                f"alertname={lbl.get('alertname','?')} "
+                f"severity={lbl.get('severity','?')} "
+                f"instance={lbl.get('instance','?')}"
+            )
+
+        prompt = (
+            f"你是資深 SRE，請對以下告警做獨立分析並提出建議。\n"
+            f"告警摘要: {signals_summary}\n"
+            f"受影響服務: {', '.join(incident.affected_services or [])}\n"
+            f"主 AI 已提出: {primary_result.get('action','?')} "
+            f"(信心={primary_result.get('confidence',0):.2f})\n"
+            f"主 AI 根因: {primary_result.get('reasoning','')[:200]}\n\n"
+            f"請用繁體中文，100 字以內，給出你的獨立判斷與建議（若同意主 AI 則說明原因）。"
+        )
+
+        async with _httpx.AsyncClient(timeout=30.0) as client:
+            resp = await client.post(
+                f"{ollama_url}/api/generate",
+                json={"model": model, "prompt": prompt, "stream": False},
+            )
+            resp.raise_for_status()
+            data = resp.json()
+
+        advisory = data.get("response", "").strip()
+        # 截取 <think>...</think> 後的正文（deepseek-r1 CoT 格式）
+        if "</think>" in advisory:
+            advisory = advisory.split("</think>", 1)[-1].strip()
+
+        return advisory[:300] if advisory else None
+
+    except Exception as e:
+        import structlog as _sl
+        _sl.get_logger(__name__).debug("nemoclaw_second_opinion_error", error=str(e))
+        return None
+
+
 async def _fetch_metrics_snapshot(incident: Incident) -> dict:
     """
     ADR-071-I: 從 Prometheus 抓取與此 incident 相關的指標快照
@@ -993,10 +1060,25 @@ class DecisionManager:
                     provider=provider,
                     kb_rag=bool(kb_context),
                 )
-                return {
-                    **llm_result,
-                    "source": f"llm_{provider}",
-                }
+                result = {**llm_result, "source": f"llm_{provider}"}
+
+                # MCP Phase 4a: 信心 < 0.7 → NemoClaw second opinion (2026-04-11 Claude Sonnet 4.6)
+                _conf = float(result.get("confidence", 1.0))
+                if _conf < 0.7:
+                    try:
+                        _advisory = await _nemoclaw_second_opinion(incident, result)
+                        if _advisory:
+                            result["advisory_note"] = _advisory
+                            logger.info(
+                                "nemoclaw_second_opinion_added",
+                                incident_id=incident.incident_id,
+                                confidence=_conf,
+                            )
+                    except Exception as _soe:
+                        logger.warning("nemoclaw_second_opinion_failed",
+                                       incident_id=incident.incident_id, error=str(_soe))
+
+                return result
 
         except Exception as e:
             logger.warning(