diff --git a/src/chat/planner_actions/planner.py b/src/chat/planner_actions/planner.py
index da02e845..ca907406 100644
--- a/src/chat/planner_actions/planner.py
+++ b/src/chat/planner_actions/planner.py
@@ -4,6 +4,7 @@ import traceback
 import random
 import re
 from typing import Dict, Optional, Tuple, List, TYPE_CHECKING, Union
+from collections import OrderedDict
 from rich.traceback import install
 from datetime import datetime
 from json_repair import repair_json
@@ -110,6 +111,10 @@ class ActionPlanner:
         self.last_obs_time_mark = 0.0
 
         self.plan_log: List[Tuple[str, float, Union[List[ActionPlannerInfo], str]]] = []
+        
+        # 黑话缓存：使用 OrderedDict 实现 LRU，最多缓存10个
+        self.unknown_words_cache: OrderedDict[str, None] = OrderedDict()
+        self.unknown_words_cache_limit = 10
 
     def find_message_by_id(
         self, message_id: str, message_id_list: List[Tuple[str, "DatabaseMessages"]]
@@ -299,6 +304,136 @@ class ActionPlanner:
             logger.warning(f"{self.log_prefix}检测消息发送者失败，缺少必要字段")
             return False
 
+    def _update_unknown_words_cache(self, new_words: List[str]) -> None:
+        """
+        更新黑话缓存，将新的黑话加入缓存
+        
+        Args:
+            new_words: 新提取的黑话列表
+        """
+        for word in new_words:
+            if not isinstance(word, str):
+                continue
+            word = word.strip()
+            if not word:
+                continue
+            
+            # 如果已存在，移到末尾（LRU）
+            if word in self.unknown_words_cache:
+                self.unknown_words_cache.move_to_end(word)
+            else:
+                # 添加新词
+                self.unknown_words_cache[word] = None
+                # 如果超过限制，移除最老的
+                if len(self.unknown_words_cache) > self.unknown_words_cache_limit:
+                    self.unknown_words_cache.popitem(last=False)
+                    logger.debug(f"{self.log_prefix}黑话缓存已满，移除最老的黑话")
+
+    def _merge_unknown_words_with_cache(self, new_words: Optional[List[str]]) -> List[str]:
+        """
+        合并新提取的黑话和缓存中的黑话
+        
+        Args:
+            new_words: 新提取的黑话列表（可能为None）
+            
+        Returns:
+            合并后的黑话列表（去重）
+        """
+        # 清理新提取的黑话
+        cleaned_new_words: List[str] = []
+        if new_words:
+            for word in new_words:
+                if isinstance(word, str):
+                    word = word.strip()
+                    if word:
+                        cleaned_new_words.append(word)
+        
+        # 获取缓存中的黑话列表
+        cached_words = list(self.unknown_words_cache.keys())
+        
+        # 合并并去重（保留顺序：新提取的在前，缓存的在后）
+        merged_words: List[str] = []
+        seen = set()
+        
+        # 先添加新提取的
+        for word in cleaned_new_words:
+            if word not in seen:
+                merged_words.append(word)
+                seen.add(word)
+        
+        # 再添加缓存的（如果不在新提取的列表中）
+        for word in cached_words:
+            if word not in seen:
+                merged_words.append(word)
+                seen.add(word)
+        
+        return merged_words
+
+    def _process_unknown_words_cache(
+        self, actions: List[ActionPlannerInfo]
+    ) -> None:
+        """
+        处理黑话缓存逻辑：
+        1. 检查是否有 reply action 提取了 unknown_words
+        2. 如果没有提取，移除最老的1个
+        3. 如果缓存数量大于5，移除最老的2个
+        4. 对于每个 reply action，合并缓存和新提取的黑话
+        5. 更新缓存
+        
+        Args:
+            actions: 解析后的动作列表
+        """
+        # 先检查缓存数量，如果大于5，移除最老的2个
+        if len(self.unknown_words_cache) > 5:
+            # 移除最老的2个
+            removed_count = 0
+            for _ in range(2):
+                if len(self.unknown_words_cache) > 0:
+                    self.unknown_words_cache.popitem(last=False)
+                    removed_count += 1
+            if removed_count > 0:
+                logger.debug(f"{self.log_prefix}缓存数量大于5，移除最老的{removed_count}个缓存")
+        
+        # 检查是否有 reply action 提取了 unknown_words
+        has_extracted_unknown_words = False
+        for action in actions:
+            if action.action_type == "reply":
+                action_data = action.action_data or {}
+                unknown_words = action_data.get("unknown_words")
+                if unknown_words and isinstance(unknown_words, list) and len(unknown_words) > 0:
+                    has_extracted_unknown_words = True
+                    break
+        
+        # 如果当前 plan 的 reply 没有提取，移除最老的1个
+        if not has_extracted_unknown_words:
+            if len(self.unknown_words_cache) > 0:
+                self.unknown_words_cache.popitem(last=False)
+                logger.debug(f"{self.log_prefix}当前 plan 的 reply 没有提取黑话，移除最老的1个缓存")
+        
+        # 对于每个 reply action，合并缓存和新提取的黑话
+        for action in actions:
+            if action.action_type == "reply":
+                action_data = action.action_data or {}
+                new_words = action_data.get("unknown_words")
+                
+                # 合并新提取的和缓存的黑话列表
+                merged_words = self._merge_unknown_words_with_cache(new_words)
+                
+                # 更新 action_data
+                if merged_words:
+                    action_data["unknown_words"] = merged_words
+                    logger.debug(
+                        f"{self.log_prefix}合并黑话：新提取 {len(new_words) if new_words else 0} 个，"
+                        f"缓存 {len(self.unknown_words_cache)} 个，合并后 {len(merged_words)} 个"
+                    )
+                else:
+                    # 如果没有合并后的黑话，移除 unknown_words 字段
+                    action_data.pop("unknown_words", None)
+                
+                # 更新缓存（将新提取的黑话加入缓存）
+                if new_words:
+                    self._update_unknown_words_cache(new_words)
+
     async def plan(
         self,
         available_actions: Dict[str, ActionInfo],
@@ -722,6 +857,9 @@ class ActionPlanner:
             random.shuffle(shuffled)
             actions = list({a.action_type: a for a in shuffled}.values())
 
+        # 处理黑话缓存逻辑
+        self._process_unknown_words_cache(actions)
+
         logger.debug(f"{self.log_prefix}规划器选择了{len(actions)}个动作: {' '.join([a.action_type for a in actions])}")
 
         return extracted_reasoning, actions, llm_content, llm_reasoning, llm_duration_ms