feat: introduce unified agent runtime config and system task prompt framework

- Add structured runtime config files (AGENT_PROFILE.md, AGENT_WORKFLOW.md, AGENT_HOOKS.md, USER_PREFERENCES.md, SYSTEM_TASKS.md, CURRENT_PERSONA.md) for persona, workflow, hooks, and system tasks
- Implement agent_runtime_manager to load, validate, and render runtime config and system task prompts
- Refactor agent initialization to use runtime-managed directories for skills, jobs, memory, and activity logs
- Add AgentHooksMiddleware for structured pre/in/post hooks injection
- Replace hardcoded system task prompts with template-driven rendering from SYSTEM_TASKS.md
- Update tests to cover runtime config loading, migration, and system task prompt rendering
- Update .gitignore to exclude config/agent/

app/agent/middleware/hooks.py

@@ -0,0 +1,68 @@
+"""结构化 Agent hooks 中间件。"""
+
+from collections.abc import Awaitable, Callable
+from typing import Annotated, NotRequired, TypedDict
+
+from langchain.agents.middleware.types import (
+    AgentMiddleware,
+    AgentState,
+    ContextT,
+    ModelRequest,
+    ModelResponse,
+    PrivateStateAttr,  # noqa
+    ResponseT,
+)
+from langchain_core.runnables import RunnableConfig
+from langgraph.runtime import Runtime
+
+from app.agent.middleware.utils import append_to_system_message
+from app.agent.runtime import agent_runtime_manager
+
+
+class HooksState(AgentState):
+    """hooks 中间件状态。"""
+
+    hooks_prompt: NotRequired[Annotated[str, PrivateStateAttr]]
+
+
+class HooksStateUpdate(TypedDict):
+    """hooks 状态更新。"""
+
+    hooks_prompt: str
+
+
+class AgentHooksMiddleware(AgentMiddleware[HooksState, ContextT, ResponseT]):  # noqa
+    """在固定生命周期点注入结构化 pre/in/post hooks。"""
+
+    state_schema = HooksState
+
+    async def abefore_agent(  # noqa
+        self, state: HooksState, runtime: Runtime, config: RunnableConfig
+    ) -> HooksStateUpdate | None:
+        if "hooks_prompt" in state:
+            return None
+
+        runtime_config = agent_runtime_manager.load_runtime_config()
+        return HooksStateUpdate(hooks_prompt=runtime_config.render_hooks_prompt())
+
+    def modify_request(self, request: ModelRequest[ContextT]) -> ModelRequest[ContextT]:   # noqa
+        hooks_prompt = request.state.get("hooks_prompt", "")  # noqa
+        if not hooks_prompt:
+            return request
+
+        new_system_message = append_to_system_message(
+            request.system_message, hooks_prompt
+        )
+        return request.override(system_message=new_system_message)
+
+    async def awrap_model_call(
+        self,
+        request: ModelRequest[ContextT],
+        handler: Callable[
+            [ModelRequest[ContextT]], Awaitable[ModelResponse[ResponseT]]
+        ],
+    ) -> ModelResponse[ResponseT]:
+        return await handler(self.modify_request(request))
+
+
+__all__ = ["AgentHooksMiddleware"]

app/agent/middleware/memory.py

@@ -188,7 +188,8 @@ class MemoryMiddleware(AgentMiddleware[MemoryState, ContextT, ResponseT]):  # no
     支持多文件记忆组织：用户可以创建多个 `.md` 文件来按主题组织知识。
 
     参数：
-        memory_dir: 记忆文件目录路径。
+        memory_dir: 记忆文件目录路径。建议使用独立的 `config/agent/memory`
+            目录，避免与 persona/workflow 等根层配置混写。
     """
 
     state_schema = MemoryState
@@ -201,7 +202,7 @@ class MemoryMiddleware(AgentMiddleware[MemoryState, ContextT, ResponseT]):  # no
         """初始化记忆中间件。
 
         参数：
-            memory_dir: 记忆文件目录路径（例如，`"/config/agent"`）。
+            memory_dir: 记忆文件目录路径（例如，`"/config/agent/memory"`）。
                         该目录下所有 `.md` 文件都会被自动加载为记忆。
         """
         self.memory_dir = memory_dir