diff --git a/freqtrade/templates/freqaiprimer.py b/freqtrade/templates/freqaiprimer.py
index ada16ba9..6bbb7d53 100644
--- a/freqtrade/templates/freqaiprimer.py
+++ b/freqtrade/templates/freqaiprimer.py
@@ -21,7 +21,7 @@ UTC_PLUS_8 = timezone(timedelta(hours=8))
 class FreqaiPrimer(IStrategy):
     # 策略参数 - 使用custom_roi替代minimal_roi字典
     loglevel = "warning"
-    minimal_roi = {}
+    minimal_roi = {}self.add_position_callback.value
     
     # 启用自定义ROI回调函数
     use_custom_roi = True
@@ -500,6 +500,8 @@ class FreqaiPrimer(IStrategy):
     def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         # ========== 新增：ML目标变量数据新鲜度监控 ==========
         # 检查FreqAI模型预测数据的新鲜度，确保使用最新的预测结果
+        # 注意：ML预测数据通常比普通量化数据滞后一个timeframe（约3分钟）
+        # 这是FreqAI的正常工作机制，不影响策略有效性
         try:
             # 获取FreqAI分析过的数据帧
             analyzed_df, _ = self.dp.get_analyzed_dataframe(metadata['pair'], self.timeframe)
@@ -1513,6 +1515,16 @@ class FreqaiPrimer(IStrategy):
                                 ema_trend_filter_1h_recent = ema_trend_filter_1h.iloc[-5:].tolist()
                                 ema_trend_filter_1h_visual = ''.join(['✅' if x else '❌' for x in ema_trend_filter_1h_recent])
                                 self.strategy_log(f"  - [{ema_trend_filter_1h_visual}]#1hEMA趋势过滤(宽松版)【用于业务逻辑】")
+                                
+                                # EMA20仰角状态可视化
+                                if 'ema20_slope_normalized' in df.columns:
+                                    # 获取最近5个EMA20斜率值
+                                    ema20_slope_values = df['ema20_slope_normalized'].iloc[-5:]
+                                    # 检查是否超过阈值
+                                    ema20_slope_threshold = self.ema20_slope_threshold.value
+                                    ema20_slope_above_threshold = ema20_slope_values > ema20_slope_threshold
+                                    ema20_slope_visual = ''.join(['✅' if x else '❌' for x in ema20_slope_above_threshold])
+                                    self.strategy_log(f"  - [{ema20_slope_visual}]#EMA20仰角>阈值(越绿越大)【用于趋势强度】")
                         
                         # ========== 诊断统计结束 ==========