diff --git a/other_ext/kamaz_ai.py b/other_ext/kamaz_ai.py
index 289a1a1..a00f24a 100644
--- a/other_ext/kamaz_ai.py
+++ b/other_ext/kamaz_ai.py
@@ -107,24 +107,17 @@ class KamazAI:
 			score += self.WEIGHTS['steam_identity'] * identity_score
 
 		# 2. Причина (точное совпадение)
-		try:
-			reason_score = 1.0 if report1['reasons'] == report2['reasons'] else 0.0
-			score += self.WEIGHTS['reason'] * reason_score
-		except:
-			print("Skip reason calc", report1, report2)
-			traceback.print_exc()
+		reason_score = 1.0 if report1['reasons'] == report2['reasons'] else 0.0
+		score += self.WEIGHTS['reason'] * reason_score
 
 		# 3. Права
-		try:
-			perm_score = 0.0
-			if report1['a_permition'] == report2['a_permition']:
-				perm_score += 0.5
-			if report1['r_permition'] == report2['r_permition']:
-				perm_score += 0.5
-			score += self.WEIGHTS['permissions'] * perm_score
-		except:
-			print("Skip permition calc", report1, report2)
-			traceback.print_exc()
+		perm_score = 0.0
+		if report1['a_permition'] == report2['a_permition']:
+			perm_score += 0.5
+		if report1['r_permition'] == report2['r_permition']:
+			perm_score += 0.5
+		score += self.WEIGHTS['permissions'] * perm_score
+
 
 		# 4. Числовые поля (нормированное евклидово расстояние -> сходство)
 		num_fields = ['a_kills', 'a_deads', 'a_seconds', 'r_kills', 'r_deads', 'r_seconds', 'online']
@@ -150,14 +143,18 @@ class KamazAI:
 			srv_score = 1.0 if report1['srv'] == report2['srv'] else 0.0
 			score += self.WEIGHTS['server'] * srv_score
 
-		return score
+		return [score, 
+		  {
+			  "reason_score": reason_score, 
+			  "perm_score": perm_score, 
+			  "num_similarity": num_similarity}]
 	
 	async def predict(self, new_report):
 		# Вычисляем сходство со всеми историческими заявками
 		similarities = []
 		for hist in self.historical_reports:
-			sim = await self.similarity(new_report, hist, self.numeric_stats)
-			similarities.append((hist['id'], sim))
+			s_container = await self.similarity(new_report, hist, self.numeric_stats)
+			similarities.append((hist['id'], s_container[0], s_container[1]))
 
 		# Сортируем по убыванию сходства
 		similarities.sort(key=lambda x: x[1], reverse=True)
@@ -167,7 +164,7 @@ class KamazAI:
 		# Собираем все действия, назначенные на эти заявки
 		action_counter = Counter()
 		similar_report_ids = []
-		for rid, sim in top_k:
+		for rid, sim, score_rate in top_k:
 			#print(rid, sim)
 			if sim > 0:  # можно задать порог, чтобы отсечь шум
 				similar_report_ids.append(rid)
@@ -185,7 +182,7 @@ class KamazAI:
 				})
 		else:
 			# Если ни одного похожего – предложение "inspect" по умолчанию
-			suggestions.append({'action': 'inspect', 'confidence': 1.0})
+			suggestions.append({'action': 'none', 'confidence': 1.0})
 
 		return {
 			'suggestions': suggestions,
@@ -204,7 +201,8 @@ class Extension:
 		'author_kick': "кикнуть автора репорта",
 		'mute': "замьютить игрока",
 		'unban': "разбанить игрока если тот в бане, ебанутое решение",
-		'author_inspect': 'глянуть профиль автора репорта'
+		'author_inspect': 'глянуть профиль автора репорта',
+		'none': 'ничего не делать, лучше не лезть'
 	}
 
 	def __init__(self, core):