feat:增加用户在webui创建和配置subagent的功能 #4697
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Hey - 我发现了 3 个问题，并给出了一些整体性的反馈：
dashboard/src/main.ts里的全局window.fetch包装器在第一个参数是Request对象时会丢失method、body和其他Request属性；建议检测参数是否为Request，如果是则原样转发（只克隆/增强 headers），以避免一些隐蔽的破坏性行为。- 在
SubAgentOrchestrator.reload_from_config中，通过func_list和remove_func手动移除/添加工具绕过了FunctionToolManager的正常注册不变式；更安全的做法是暴露并使用专门的 API 来注册HandoffTool实例，从而保证它们仍然可被发现，并与其它工具保持一致。 - 在
SubAgentRoute.update_config中保存子代理配置时，目前没有对 agent 名称做校验（例如非空、唯一性、允许字符集），这可能导致transfer_to_*工具名冲突或生成非法标识符；添加基本的服务端校验会让编排逻辑更健壮。
给 AI 代理的 Prompt
Please address the comments from this code review:
## Overall Comments
- `dashboard/src/main.ts` 里的全局 `window.fetch` 包装器在第一个参数是 `Request` 对象时会丢失 `method`、`body` 和其他 `Request` 属性；建议检测参数是否为 `Request`，如果是则原样转发（只克隆/增强 headers），以避免一些隐蔽的破坏性行为。
- 在 `SubAgentOrchestrator.reload_from_config` 中，通过 `func_list` 和 `remove_func` 手动移除/添加工具绕过了 `FunctionToolManager` 的正常注册不变式；更安全的做法是暴露并使用专门的 API 来注册 `HandoffTool` 实例，从而保证它们仍然可被发现，并与其它工具保持一致。
- 在 `SubAgentRoute.update_config` 中保存子代理配置时，目前没有对 agent 名称做校验（例如非空、唯一性、允许字符集），这可能导致 `transfer_to_*` 工具名冲突或生成非法标识符；添加基本的服务端校验会让编排逻辑更健壮。
## Individual Comments
### Comment 1
<location> `astrbot/dashboard/server.py:135-136` </location>
<code_context>
r.status_code = 401
return r
- token = token.removeprefix("Bearer ")
+ # Be tolerant of different header casing / formatting.
+ token = token.strip().removeprefix("Bearer ").strip()
try:
payload = jwt.decode(token, self._jwt_secret, algorithms=["HS256"])
</code_context>
<issue_to_address>
**suggestion:** 尽管注释里说明要兼容不同的 header 大小写，但当前 JWT 提取对 `Bearer` 前缀仍然是大小写敏感的。
代码只会移除精确匹配的 "Bearer " 前缀，因此像 `authorization: bearer <token>` 或 `Authorization: BEARER <token>` 这样的 header 会失败，这与注释不符。建议在去前缀前先做归一化，例如：
```py
raw = token.strip()
if raw.lower().startswith("bearer "):
raw = raw[7:]
token = raw.strip()
```
这样与注释中宣称的“对 header 大小写/格式更宽容”是一致的，也能避免来自非标准客户端的意外认证失败。
```suggestion
# Be tolerant of different header casing / formatting.
raw = token.strip()
if raw.lower().startswith("bearer "):
raw = raw[7:]
token = raw.strip()
```
</issue_to_address>
### Comment 2
<location> `astrbot/dashboard/routes/subagent.py:93-105` </location>
<code_context>
+ UI can use this to build a multi-select list for subagent tool assignment.
+ """
+ try:
+ tool_mgr = self.core_lifecycle.provider_manager.llm_tools
+ tools_dict = []
+ for tool in tool_mgr.func_list:
+ tools_dict.append(
+ {
+ "name": tool.name,
+ "description": tool.description,
+ "parameters": tool.parameters,
+ "active": tool.active,
+ "handler_module_path": tool.handler_module_path,
+ }
+ )
</code_context>
<issue_to_address>
**suggestion (bug_risk):** available-tools 接口会暴露 handoff 工具，使得子代理可以选择 `transfer_to_*` 工具，从而创建递归路由。
由于该接口返回 `func_list` 中的所有条目，它也会暴露 `HandoffTool` 实例（即 `transfer_to_*` 工具）。这让 UI 能够把 handoff 工具分配为子代理工具，从而可能形成令人困惑或递归的委托循环。为避免这种情况，请过滤掉这些工具——例如跳过 `handler_module_path == "core.subagent_orchestrator"` 的工具，或者如果可以的话，排除 `isinstance(tool, HandoffTool)` 的工具。
```suggestion
try:
tool_mgr = self.core_lifecycle.provider_manager.llm_tools
tools_dict = []
for tool in tool_mgr.func_list:
# Skip handoff tools (e.g., transfer_to_*), which live in the subagent orchestrator.
# These should not be assignable as subagent tools to avoid recursive delegation.
if getattr(tool, "handler_module_path", None) == "core.subagent_orchestrator":
continue
tools_dict.append(
{
"name": tool.name,
"description": tool.description,
"parameters": tool.parameters,
"active": tool.active,
"handler_module_path": tool.handler_module_path,
}
)
```
</issue_to_address>
### Comment 3
<location> `astrbot/core/subagent_orchestrator.py:37` </location>
<code_context>
+ self._tool_mgr = tool_mgr
+ self._registered_handoff_names: set[str] = set()
+
+ def reload_from_config(self, provider_settings: dict[str, Any]) -> None:
+ cfg = provider_settings.get("subagent_orchestrator", {})
+ enabled = bool(cfg.get("main_enable", False))
</code_context>
<issue_to_address>
**issue (complexity):** 建议重构 orchestrator，将工具注册/移除的职责委托给 `FunctionToolManager`，并通过 `SubAgentConfig` 统一子代理配置的解析逻辑，从而让 `reload_from_config` 更加简洁、聚焦。
可以通过加强与 `FunctionToolManager` 的交互，并真正把 `SubAgentConfig` 作为标准化后的配置类型来使用，从而显著简化当前实现。
### 1) 去掉 add/remove/append 的“舞蹈”
与其这样：
```python
self._tool_mgr.add_func(
name=handoff.name,
func_args=[...],
desc=handoff.description,
handler=handoff.handler,
)
self._tool_mgr.remove_func(handoff.name)
self._tool_mgr.func_list.append(handoff)
```
不如在 `FunctionToolManager` 中增加一个接受预构造工具并且负责替换的轻量 API：
```python
# in func_tool_manager.py
class FunctionToolManager:
...
def add_tool(self, tool: FunctionTool) -> None:
"""Register a pre-constructed tool, replacing by name if it exists."""
# remove any existing tool with same name
self.func_list = [t for t in self.func_list if t.name != tool.name]
self.func_list.append(tool)
```
这样你的 orchestrator 就变成单一、清晰的注册路径：
```python
# in SubAgentOrchestrator.reload_from_config
handoff = HandoffTool(agent=agent, description=public_description or None)
handoff.provider_id = provider_id
handoff.handler_module_path = "core.subagent_orchestrator"
self._tool_mgr.add_tool(handoff)
self._registered_handoff_names.add(handoff.name)
```
既保留了原有行为，又避免了对 `func_list` 的直接操作，以及“先 `add_func` 再立刻撤销”的模式。
### 2) 尽量避免手动状态跟踪
如果可以在工具对象中编码来源信息（你已经设置了 `handler_module_path`），就可以把移除逻辑集中到 manager 里，从而去掉 `_registered_handoff_names` 这套手动跟踪：
```python
# in func_tool_manager.py
class FunctionToolManager:
...
def remove_by_module(self, module_path: str) -> None:
self.func_list = [
t for t in self.func_list
if getattr(t, "handler_module_path", None) != module_path
]
```
然后在 orchestrator 中：
```python
def reload_from_config(self, provider_settings: dict[str, Any]) -> None:
cfg = provider_settings.get("subagent_orchestrator", {})
enabled = bool(cfg.get("main_enable", False))
# clean up previously registered tools from this orchestrator
self._tool_mgr.remove_by_module("core.subagent_orchestrator")
if not enabled:
return
...
self._tool_mgr.add_tool(handoff)
```
如果采用这种方式，就可以完全删除 `_registered_handoff_names`。
### 3) 使用 `SubAgentConfig` 简化解析逻辑
当前的 `reload_from_config` 混合了配置解析和编排逻辑。你已经有 `SubAgentConfig`，如果用它来承载标准化后的配置，方法会更短、更易读。
示例重构：
```python
@dataclass(frozen=True)
class SubAgentConfig:
name: str
instructions: str
public_description: str
tools: list[str]
provider_id: str | None = None
enabled: bool = True
```
解析辅助函数：
```python
def _parse_agent_config(self, item: dict[str, Any]) -> SubAgentConfig | None:
if not isinstance(item, dict):
return None
if not item.get("enabled", True):
return None
name = str(item.get("name", "")).strip()
if not name:
return None
instructions = str(item.get("system_prompt", "")).strip()
public_description = str(item.get("public_description", "")).strip()
provider_id = item.get("provider_id")
if provider_id is not None:
provider_id = str(provider_id).strip() or None
tools = item.get("tools", [])
if not isinstance(tools, list):
tools = []
tools = [str(t).strip() for t in tools if str(t).strip()]
return SubAgentConfig(
name=name,
instructions=instructions,
public_description=public_description,
tools=tools,
provider_id=provider_id,
enabled=True,
)
```
然后 `reload_from_config` 就可以聚焦在编排本身：
```python
def reload_from_config(self, provider_settings: dict[str, Any]) -> None:
cfg = provider_settings.get("subagent_orchestrator", {})
enabled = bool(cfg.get("main_enable", False))
self._tool_mgr.remove_by_module("core.subagent_orchestrator")
if not enabled:
return
agents = cfg.get("agents", [])
if not isinstance(agents, list):
logger.warning("subagent_orchestrator.agents must be a list")
return
for item in agents:
cfg_item = self._parse_agent_config(item)
if cfg_item is None:
continue
agent = Agent[AstrAgentContext](
name=cfg_item.name,
instructions=cfg_item.instructions,
tools=cfg_item.tools,
)
handoff = HandoffTool(
agent=agent,
description=cfg_item.public_description or None,
)
handoff.provider_id = cfg_item.provider_id
handoff.handler_module_path = "core.subagent_orchestrator"
self._tool_mgr.add_tool(handoff)
logger.info(f"Registered subagent handoff tool: {handoff.name}")
```
这样可以让 `SubAgentConfig` 成为真正的抽象（而不是闲置代码），在保持行为不变的前提下，降低 `reload_from_config` 的认知负担。
</issue_to_address>帮我变得更有用！请在每条评论上点 👍 或 👎，我会根据你的反馈改进评审质量。
Original comment in English
Hey - I've found 3 issues, and left some high level feedback:
- The global
window.fetchwrapper indashboard/src/main.tslosesmethod,body, and otherRequestproperties when the first argument is aRequestobject; consider detectingRequestand forwarding it unchanged (only cloning/augmenting headers) to avoid subtle breakage. - In
SubAgentOrchestrator.reload_from_config, manually removing/adding tools viafunc_listandremove_funcbypassesFunctionToolManager's normal registration invariants; it would be safer to expose and use a dedicated API for registeringHandoffToolinstances so they remain discoverable and consistent with other tools. - When saving subagent config in
SubAgentRoute.update_config, there is currently no validation of agent names (e.g., non-empty, uniqueness, allowed characters), which could lead to conflictingtransfer_to_*tool names or invalid identifiers; adding basic server-side validation would make the orchestration more robust.
Prompt for AI Agents
Please address the comments from this code review:
## Overall Comments
- The global `window.fetch` wrapper in `dashboard/src/main.ts` loses `method`, `body`, and other `Request` properties when the first argument is a `Request` object; consider detecting `Request` and forwarding it unchanged (only cloning/augmenting headers) to avoid subtle breakage.
- In `SubAgentOrchestrator.reload_from_config`, manually removing/adding tools via `func_list` and `remove_func` bypasses `FunctionToolManager`'s normal registration invariants; it would be safer to expose and use a dedicated API for registering `HandoffTool` instances so they remain discoverable and consistent with other tools.
- When saving subagent config in `SubAgentRoute.update_config`, there is currently no validation of agent names (e.g., non-empty, uniqueness, allowed characters), which could lead to conflicting `transfer_to_*` tool names or invalid identifiers; adding basic server-side validation would make the orchestration more robust.
## Individual Comments
### Comment 1
<location> `astrbot/dashboard/server.py:135-136` </location>
<code_context>
r.status_code = 401
return r
- token = token.removeprefix("Bearer ")
+ # Be tolerant of different header casing / formatting.
+ token = token.strip().removeprefix("Bearer ").strip()
try:
payload = jwt.decode(token, self._jwt_secret, algorithms=["HS256"])
</code_context>
<issue_to_address>
**suggestion:** JWT extraction is still case-sensitive for the 'Bearer' prefix despite the comment about header casing.
The code only removes an exact "Bearer " prefix, so headers like `authorization: bearer <token>` or `Authorization: BEARER <token>` will fail despite the comment. Consider normalizing before stripping, e.g.:
```py
raw = token.strip()
if raw.lower().startswith("bearer "):
raw = raw[7:]
token = raw.strip()
```
This matches the stated tolerance for header casing/formatting and avoids unexpected auth failures from non-standard clients.
```suggestion
# Be tolerant of different header casing / formatting.
raw = token.strip()
if raw.lower().startswith("bearer "):
raw = raw[7:]
token = raw.strip()
```
</issue_to_address>
### Comment 2
<location> `astrbot/dashboard/routes/subagent.py:93-105` </location>
<code_context>
+ UI can use this to build a multi-select list for subagent tool assignment.
+ """
+ try:
+ tool_mgr = self.core_lifecycle.provider_manager.llm_tools
+ tools_dict = []
+ for tool in tool_mgr.func_list:
+ tools_dict.append(
+ {
+ "name": tool.name,
+ "description": tool.description,
+ "parameters": tool.parameters,
+ "active": tool.active,
+ "handler_module_path": tool.handler_module_path,
+ }
+ )
</code_context>
<issue_to_address>
**suggestion (bug_risk):** available-tools endpoint exposes handoff tools, allowing subagents to select transfer_to_* tools and create recursive routing.
Because this endpoint returns all entries in `func_list`, it also exposes `HandoffTool` instances (the `transfer_to_*` tools). That lets the UI assign handoff tools as subagent tools, enabling confusing or recursive delegation loops. To avoid this, filter these out—for example, skip tools with `handler_module_path == "core.subagent_orchestrator"` or, if possible, exclude `isinstance(tool, HandoffTool)`.
```suggestion
try:
tool_mgr = self.core_lifecycle.provider_manager.llm_tools
tools_dict = []
for tool in tool_mgr.func_list:
# Skip handoff tools (e.g., transfer_to_*), which live in the subagent orchestrator.
# These should not be assignable as subagent tools to avoid recursive delegation.
if getattr(tool, "handler_module_path", None) == "core.subagent_orchestrator":
continue
tools_dict.append(
{
"name": tool.name,
"description": tool.description,
"parameters": tool.parameters,
"active": tool.active,
"handler_module_path": tool.handler_module_path,
}
)
```
</issue_to_address>
### Comment 3
<location> `astrbot/core/subagent_orchestrator.py:37` </location>
<code_context>
+ self._tool_mgr = tool_mgr
+ self._registered_handoff_names: set[str] = set()
+
+ def reload_from_config(self, provider_settings: dict[str, Any]) -> None:
+ cfg = provider_settings.get("subagent_orchestrator", {})
+ enabled = bool(cfg.get("main_enable", False))
</code_context>
<issue_to_address>
**issue (complexity):** Consider refactoring the orchestrator to delegate tool registration/removal to `FunctionToolManager` and normalize subagent parsing through `SubAgentConfig` for a cleaner, more focused `reload_from_config`.
You can simplify this substantially by tightening the interaction with `FunctionToolManager` and actually using `SubAgentConfig` as your normalized config type.
### 1) Remove the add/remove/append dance
Instead of:
```python
self._tool_mgr.add_func(
name=handoff.name,
func_args=[...],
desc=handoff.description,
handler=handoff.handler,
)
self._tool_mgr.remove_func(handoff.name)
self._tool_mgr.func_list.append(handoff)
```
add a small API to `FunctionToolManager` that accepts a pre‑built tool and handles replacement:
```python
# in func_tool_manager.py
class FunctionToolManager:
...
def add_tool(self, tool: FunctionTool) -> None:
"""Register a pre-constructed tool, replacing by name if it exists."""
# remove any existing tool with same name
self.func_list = [t for t in self.func_list if t.name != tool.name]
self.func_list.append(tool)
```
Then your orchestrator becomes a single, clear registration path:
```python
# in SubAgentOrchestrator.reload_from_config
handoff = HandoffTool(agent=agent, description=public_description or None)
handoff.provider_id = provider_id
handoff.handler_module_path = "core.subagent_orchestrator"
self._tool_mgr.add_tool(handoff)
self._registered_handoff_names.add(handoff.name)
```
This keeps all behavior but avoids reaching into `func_list` and calling `add_func` only to immediately undo it.
### 2) Avoid manual tracking where possible
If you can encode the origin in the tools (you already set `handler_module_path`), you can centralize removal in the manager and drop the `_registered_handoff_names` set:
```python
# in func_tool_manager.py
class FunctionToolManager:
...
def remove_by_module(self, module_path: str) -> None:
self.func_list = [
t for t in self.func_list
if getattr(t, "handler_module_path", None) != module_path
]
```
Then in the orchestrator:
```python
def reload_from_config(self, provider_settings: dict[str, Any]) -> None:
cfg = provider_settings.get("subagent_orchestrator", {})
enabled = bool(cfg.get("main_enable", False))
# clean up previously registered tools from this orchestrator
self._tool_mgr.remove_by_module("core.subagent_orchestrator")
if not enabled:
return
...
self._tool_mgr.add_tool(handoff)
```
If you adopt this, you can remove `_registered_handoff_names` completely.
### 3) Use `SubAgentConfig` to simplify parsing
Right now `reload_from_config` mixes config parsing with orchestration. You already have `SubAgentConfig`; using it makes the method shorter and easier to read.
Example refactor:
```python
@dataclass(frozen=True)
class SubAgentConfig:
name: str
instructions: str
public_description: str
tools: list[str]
provider_id: str | None = None
enabled: bool = True
```
Parsing helper:
```python
def _parse_agent_config(self, item: dict[str, Any]) -> SubAgentConfig | None:
if not isinstance(item, dict):
return None
if not item.get("enabled", True):
return None
name = str(item.get("name", "")).strip()
if not name:
return None
instructions = str(item.get("system_prompt", "")).strip()
public_description = str(item.get("public_description", "")).strip()
provider_id = item.get("provider_id")
if provider_id is not None:
provider_id = str(provider_id).strip() or None
tools = item.get("tools", [])
if not isinstance(tools, list):
tools = []
tools = [str(t).strip() for t in tools if str(t).strip()]
return SubAgentConfig(
name=name,
instructions=instructions,
public_description=public_description,
tools=tools,
provider_id=provider_id,
enabled=True,
)
```
Then `reload_from_config` focuses on orchestration:
```python
def reload_from_config(self, provider_settings: dict[str, Any]) -> None:
cfg = provider_settings.get("subagent_orchestrator", {})
enabled = bool(cfg.get("main_enable", False))
self._tool_mgr.remove_by_module("core.subagent_orchestrator")
if not enabled:
return
agents = cfg.get("agents", [])
if not isinstance(agents, list):
logger.warning("subagent_orchestrator.agents must be a list")
return
for item in agents:
cfg_item = self._parse_agent_config(item)
if cfg_item is None:
continue
agent = Agent[AstrAgentContext](
name=cfg_item.name,
instructions=cfg_item.instructions,
tools=cfg_item.tools,
)
handoff = HandoffTool(
agent=agent,
description=cfg_item.public_description or None,
)
handoff.provider_id = cfg_item.provider_id
handoff.handler_module_path = "core.subagent_orchestrator"
self._tool_mgr.add_tool(handoff)
logger.info(f"Registered subagent handoff tool: {handoff.name}")
```
This makes `SubAgentConfig` a real abstraction (not dead code), keeps behavior intact, and reduces the cognitive load in `reload_from_config`.
</issue_to_address>Help me be more useful! Please click 👍 or 👎 on each comment and I'll use the feedback to improve your reviews.
astrbot/dashboard/server.py
Outdated
Comment on lines
135
to
136
| # Be tolerant of different header casing / formatting. | ||
| token = token.strip().removeprefix("Bearer ").strip() |
Contributor
There was a problem hiding this comment.
suggestion: 尽管注释里说明要兼容不同的 header 大小写，但当前 JWT 提取对 Bearer 前缀仍然是大小写敏感的。
代码只会移除精确匹配的 "Bearer " 前缀，因此像 authorization: bearer <token> 或 Authorization: BEARER <token> 这样的 header 会失败，这与注释不符。建议在去前缀前先做归一化，例如：
raw = token.strip()
if raw.lower().startswith("bearer "):
raw = raw[7:]
token = raw.strip()这样与注释中宣称的“对 header 大小写/格式更宽容”是一致的，也能避免来自非标准客户端的意外认证失败。
Suggested change
| # Be tolerant of different header casing / formatting. | |
| token = token.strip().removeprefix("Bearer ").strip() | |
| # Be tolerant of different header casing / formatting. | |
| raw = token.strip() | |
| if raw.lower().startswith("bearer "): | |
| raw = raw[7:] | |
| token = raw.strip() |
Original comment in English
suggestion: JWT extraction is still case-sensitive for the 'Bearer' prefix despite the comment about header casing.
The code only removes an exact "Bearer " prefix, so headers like authorization: bearer <token> or Authorization: BEARER <token> will fail despite the comment. Consider normalizing before stripping, e.g.:
raw = token.strip()
if raw.lower().startswith("bearer "):
raw = raw[7:]
token = raw.strip()This matches the stated tolerance for header casing/formatting and avoids unexpected auth failures from non-standard clients.
Suggested change
| # Be tolerant of different header casing / formatting. | |
| token = token.strip().removeprefix("Bearer ").strip() | |
| # Be tolerant of different header casing / formatting. | |
| raw = token.strip() | |
| if raw.lower().startswith("bearer "): | |
| raw = raw[7:] | |
| token = raw.strip() |
dosubot
bot
added
area:core
Soulter
reviewed
Jan 26, 2026
astrbot/dashboard/server.py
Outdated
| return r | ||
| token = token.removeprefix("Bearer ") | ||
| # Be tolerant of different header casing / formatting. | ||
| token = token.strip().removeprefix("Bearer ").strip() |
| name=f"transfer_to_{agent.name}", | ||
| parameters=parameters or self.default_parameters(), | ||
| description=agent.instructions or self.default_description(agent.name), | ||
| description=description, |
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这里直接这样改吧：
- 新增可为None的关键字参数，"tool_description"，然后这里就 tool_description or self.default_description(agent.name)
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| @dataclass(frozen=True) | ||
| class SubAgentConfig: |
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感觉相关逻辑可以直接放到 tool_manager 里面，用一个方法代替。
Soulter
reviewed
Jan 26, 2026
astrbot/core/config/default.py
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| }, | ||
| # SubAgent orchestrator mode: the main LLM only delegates tasks to subagents | ||
| # (via transfer_to_{agent} tools). Domain tools are mounted on subagents. | ||
| "subagent_orchestrator": { |
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Motivations / 动机
目前框架采取将所有tool全部挂载在主llm上，主llm既负责与用户对话，又要负责组织和调用大量工具。若tool数量多，容易导致prompt长度爆炸以及llm调用失误等情况。
若用户可以创建subagent，每个subagent负责挂载一定的工具，主llm只需负责聊天以及向subagent委派任务即可，具体工具由subagent负责调用。这样可以极大得减少主llm的prompt长度以及执行任务时的出错概率。
Modifications / 改动点
1.在webui上增加subagent编排，用户可在页面上创建subagent，指定该subagent使用的工具，subagent的systemprompt以及在主llm处subagent的描述，以及自定义subagent使用的模型
2.支持开关subagent功能，开启时，主 LLM 仅负责对话与委派，只会看到 transfer_to_* 这类委派工具；需要调用工具时，会把任务交给对应 SubAgent 执行。SubAgent 负责真正的工具调用与结果整理，并把结论回传给主 LLM。关闭时则像原来一样把全部工具挂载到主llm上。
3.注册的subagent会自动成为一个名为transfer_to_(subagent名称)的tool，复用框架原有handleoff功能，主llm调用transfer_to_(agent名称)即将任务委派给指定subagent。
Screenshots or Test Results / 运行截图或测试结果
Checklist / 检查清单
requirements.txt和pyproject.toml文件相应位置。/ I have ensured that no new dependencies are introduced, OR if new dependencies are introduced, they have been added to the appropriate locations inrequirements.txtandpyproject.toml.Summary by Sourcery
引入一种可配置的子代理（subagent）编排模式，在该模式下主 LLM 通过动态交接（handoff）工具进行委派，而不是直接挂载所有工具。
New Features:
transfer_to_*交接工具，支持可选的按子代理级别的 provider 覆盖。Enhancements:
fetch的仪表盘请求自动包含Authorization头。Build:
monaco-editor添加为仪表盘依赖，以在 UI 中提供更强大的编辑器能力。Original summary in English
Summary by Sourcery
Introduce a configurable subagent orchestration mode where the main LLM delegates via dynamic handoff tools instead of mounting all tools directly.
New Features:
Enhancements:
Build: