feat: add active memory tools (StoreMemoryTool, SearchMemoryTool) (#3197)

- Implement StoreMemoryTool for explicit memory storage during agent reasoning
- Implement SearchMemoryTool for on-demand memory retrieval during conversations
- Integrate tools into agent creation flow (create_agent_info.py)
- Register tools in nexent_agent.py and tools/__init__.py
- Add MEMORY_OPERATION tool sign for proper categorization
- Fix memory_core.py cache key to include event loop ID (prevents cross-loop conflicts)
- Add comprehensive test coverage for both tools
- Add procedural memory verification documentation

Tools follow existing patterns: lazy imports, observer integration, error handling,
and respect user memory preferences (agent_share_option, disabled_agent_ids).

Co-authored-by: Dallas98 <40557804+Dallas98@users.noreply.github.com>

Author: JasonW404

.gitignore

@@ -61,4 +61,7 @@ data/
 sdk/benchmark/.env
 /docker/.env.bak
 
-.venv
+.venv
+
+.pytest-tmp
+doc/mermaid

backend/agents/create_agent_info.py

@@ -1,4 +1,5 @@
-import threading
+import json
+import threading
 import logging
 from typing import List, Optional
 from urllib.parse import urljoin
@@ -383,6 +384,77 @@ async def create_agent_config(
             # Bubble up to streaming layer so it can emit <MEM_FAILED> and fall back
             raise Exception(f"Failed to retrieve memory list: {e}")
 
+    # Append active memory tools if memory is enabled
+    if memory_context.user_config.memory_switch and memory_context.memory_config:
+        try:
+            memory_metadata = {
+                "memory_config": memory_context.memory_config,
+                "memory_user_config": memory_context.user_config,
+                "tenant_id": memory_context.tenant_id,
+                "user_id": memory_context.user_id,
+                "agent_id": memory_context.agent_id,
+            }
+
+            store_tool_config = ToolConfig(
+                class_name="StoreMemoryTool",
+                name="store_memory",
+                description=(
+                    "Save important information to long-term memory for future recall. "
+                    "Use this when the user shares personal preferences, facts about themselves, "
+                    "project context, or instructions that should persist across conversations. "
+                    "Do NOT store transient information like temporary calculations, information "
+                    "already in the knowledge base, or data the user explicitly says to forget."
+                ),
+                inputs=json.dumps({
+                    "content": {
+                        "type": "string",
+                        "description": "The information to remember",
+                        "description_zh": "需要记住的信息"
+                    }
+                }, ensure_ascii=False),
+                output_type="string",
+                params={},
+                source="local",
+                usage=None,
+                metadata=memory_metadata,
+            )
+            tool_list.append(store_tool_config)
+
+            search_tool_config = ToolConfig(
+                class_name="SearchMemoryTool",
+                name="search_memory",
+                description=(
+                    "Search long-term memory for relevant information from previous interactions. "
+                    "Use this when you need context about the user's preferences, past decisions, "
+                    "or previously discussed topics that aren't in the current conversation. "
+                    "The system already provides some memory context automatically -- use this tool "
+                    "when you need to search for specific information not already available."
+                ),
+                inputs=json.dumps({
+                    "query": {
+                        "type": "string",
+                        "description": "Natural language query describing what to search for",
+                        "description_zh": "描述要搜索内容的自然语言查询"
+                    },
+                    "top_k": {
+                        "type": "integer",
+                        "description": "Maximum number of results to return",
+                        "description_zh": "返回结果的最大数量",
+                        "default": 5,
+                        "nullable": True
+                    }
+                }, ensure_ascii=False),
+                output_type="string",
+                params={},
+                source="local",
+                usage=None,
+                metadata=memory_metadata,
+            )
+            tool_list.append(search_tool_config)
+            logger.debug("Active memory tools appended to agent tool list")
+        except Exception as e:
+            logger.warning(f"Failed to append active memory tools: {e}")
+
     # Build knowledge base summary
     knowledge_base_summary = ""
     try: