feat(api): ADR-030 Phase 4 自動執行機制

實作低風險操作自動執行策略：

1. auto_approve.py - 自動執行策略服務
   - AutoApprovePolicy: 評估是否可自動執行
   - 條件: LOW 風險 + 信任分數 >= 5 + Playbook 成功率 >= 95%
   - CRITICAL 永遠不自動執行
   - 完整審計追蹤

2. trust_engine.py - 新增 singleton
   - get_trust_manager(): 取得全域 TrustScoreManager

3. decision_manager.py - 整合自動執行 (Tier 3 紅區)
   - Step 5 加入 AutoApprovePolicy 判斷
   - 條件滿足時跳過 Telegram，直接執行
   - _auto_execute(): 自動執行邏輯
   - 失敗時 fallback 到人工審核

流程:
Incident → 分析 → AutoApprovePolicy 評估
  ├─ 可自動執行 → 直接執行 → 完成
  └─ 需人工審核 → Telegram 通知 → 等待批准

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

apps/api/src/services/decision_manager.py

@@ -31,6 +31,7 @@ from src.core.config import settings
 from src.core.redis_client import get_redis
 from src.models.incident import Incident
 from src.models.playbook import SymptomPattern
+from src.services.auto_approve import get_auto_approve_policy
 from src.services.openclaw import get_openclaw
 from src.services.playbook_service import get_playbook_service
 
@@ -422,15 +423,89 @@ class DecisionManager:
         # 4. 儲存最終結果
         await self._save_token(token)
 
-        # 5. Phase 6.5: 推送到 Telegram (非阻塞)
+        # 5. ADR-030 Phase 4: 自動執行判斷
         if token.state == DecisionState.READY and token.proposal_data:
-            # 使用 asyncio.create_task 非阻塞執行
+            # 評估是否可以自動執行
+            auto_policy = get_auto_approve_policy()
+            auto_decision = auto_policy.evaluate(
+                proposal_data=token.proposal_data,
+                playbook=token.proposal_data.get("_matched_playbook"),  # 如果有
+            )
+
+            if auto_decision.should_auto_approve:
+                # 自動執行 (跳過人工審核)
+                logger.info(
+                    "auto_approve_triggered",
+                    incident_id=incident.incident_id,
+                    reason=auto_decision.reason.value,
+                    detail=auto_decision.reason_detail,
+                )
+                token.state = DecisionState.EXECUTING
+                token.proposal_data["auto_approved"] = True
+                token.proposal_data["auto_approve_reason"] = auto_decision.reason_detail
+                await self._save_token(token)
+
+                # 觸發自動執行 (非阻塞)
+                asyncio.create_task(
+                    self._auto_execute(incident, token)
+                )
+            else:
+                # 需人工審核: 推送到 Telegram
+                asyncio.create_task(
+                    _push_decision_to_telegram(incident, token.proposal_data)
+                )
+
+        return token
+
+    async def _auto_execute(self, incident: Incident, token: "DecisionToken") -> None:
+        """
+        ADR-030 Phase 4: 自動執行已批准的操作
+
+        僅當 AutoApprovePolicy 判斷可自動執行時呼叫
+        """
+        try:
+            # 延遲導入避免循環依賴
+            from src.services.approval_execution import ApprovalExecutionService
+            from src.models.approval import ApprovalRequest, ApprovalStatus
+
+            # 建立虛擬 ApprovalRequest
+            approval = ApprovalRequest(
+                incident_id=incident.incident_id,
+                action=token.proposal_data.get("kubectl_command", ""),
+                status=ApprovalStatus.APPROVED,
+                risk_level=token.proposal_data.get("risk_level", "low"),
+            )
+
+            # 執行
+            executor = ApprovalExecutionService()
+            await executor.execute_approved_action(approval)
+
+            # 更新狀態
+            token.state = DecisionState.COMPLETED
+            token.proposal_data["auto_executed"] = True
+            await self._save_token(token)
+
+            logger.info(
+                "auto_execute_completed",
+                incident_id=incident.incident_id,
+                action=approval.action,
+            )
+
+        except Exception as e:
+            logger.error(
+                "auto_execute_failed",
+                incident_id=incident.incident_id,
+                error=str(e),
+            )
+            token.state = DecisionState.ERROR
+            token.error = f"Auto-execute failed: {e}"
+            await self._save_token(token)
+
+            # 失敗時 fallback 到人工審核
             asyncio.create_task(
                 _push_decision_to_telegram(incident, token.proposal_data)
             )
 
-        return token
-
     async def _dual_engine_analyze(
         self,
         incident: Incident,