修改了nanobot，往Hermes agent的风格走，进度1/3

app-instance/backend/beaver/tools/builtins/memory.py

@@ -0,0 +1,129 @@
+"""Beaver 内置 memory tool。
+
+这个文件的职责很单纯：把 `MemoryStore` 暴露成一个 agent runtime 可以调用的统一工具。
+
+设计边界：
+1. `store.py` 负责底层数据与并发安全
+2. 本文件负责工具接口、参数校验分发、JSON 响应
+3. 更高层的 engine / loader 之后再决定如何把这个工具注册进 runtime
+
+换句话说，本文件是“memory 能力的工具化外壳”，不是记忆实现本身。
+"""
+
+from __future__ import annotations
+
+import json
+from dataclasses import dataclass, field
+from typing import Any
+
+from beaver.memory.curated.store import MemoryStore
+
+MEMORY_TOOL_DESCRIPTION = (
+    "Save durable information to persistent memory that survives across sessions. "
+    "Use this proactively for user corrections, preferences, environment facts, "
+    "project conventions, and stable tool quirks. Do not store temporary task "
+    "progress or raw session logs here; use session search for historical detail."
+)
+
+MEMORY_TOOL_PARAMETERS: dict[str, Any] = {
+    "type": "object",
+    "properties": {
+        "action": {
+            "type": "string",
+            "enum": ["add", "replace", "remove"],
+            "description": "The memory operation to perform.",
+        },
+        "target": {
+            "type": "string",
+            "enum": ["memory", "user"],
+            "description": "Which curated store to update.",
+        },
+        "content": {
+            "type": "string",
+            "description": "The new entry content. Required for add and replace.",
+        },
+        "old_text": {
+            "type": "string",
+            "description": "A short unique substring identifying the entry to replace or remove.",
+        },
+    },
+    "required": ["action", "target"],
+}
+
+
+def memory_tool(
+    *,
+    action: str,
+    target: str = "memory",
+    content: str | None = None,
+    old_text: str | None = None,
+    store: MemoryStore | None = None,
+) -> str:
+    """分发 Hermes 风格的 CRUD memory API，并返回 JSON 字符串。
+
+    这里统一采用 JSON 返回，是为了兼容常见 tool-calling 场景：
+    - LLM 更容易消费结构化结果
+    - Web/API/日志层也更容易透传和记录
+    """
+
+    if store is None:
+        return json.dumps(
+            {
+                "success": False,
+                "error": "Memory store is not available for this runtime.",
+            },
+            ensure_ascii=False,
+        )
+
+    if target not in {"memory", "user"}:
+        return json.dumps(
+            {
+                "success": False,
+                "error": f"Invalid target '{target}'. Use 'memory' or 'user'.",
+            },
+            ensure_ascii=False,
+        )
+
+    if action == "add":
+        if not content:
+            result = {"success": False, "error": "content is required for add."}
+        else:
+            result = store.add(target, content)
+    elif action == "replace":
+        if not old_text:
+            result = {"success": False, "error": "old_text is required for replace."}
+        elif not content:
+            result = {"success": False, "error": "content is required for replace."}
+        else:
+            result = store.replace(target, old_text, content)
+    elif action == "remove":
+        if not old_text:
+            result = {"success": False, "error": "old_text is required for remove."}
+        else:
+            result = store.remove(target, old_text)
+    else:
+        result = {
+            "success": False,
+            "error": f"Unknown action '{action}'. Use add, replace, or remove.",
+        }
+
+    return json.dumps(result, ensure_ascii=False)
+
+
+@dataclass(slots=True)
+class MemoryTool:
+    """面向 runtime 的轻量工具封装。
+
+    这里故意保持很薄：
+    1. 不重复实现业务逻辑
+    2. 不重复维护 schema
+    3. 只做 `execute()` 到 `memory_tool()` 的桥接
+    """
+
+    store: MemoryStore
+    name: str = "memory"
+    description: str = MEMORY_TOOL_DESCRIPTION
+    parameters: dict[str, Any] = field(default_factory=lambda: dict(MEMORY_TOOL_PARAMETERS))
+
+    async def execute(self, **kwargs: Any) -> str:
+        return memory_tool(store=self.store, **kwargs)