```

feat(agent): 添加对持久化子智能体的支持并增强委派管理

添加了持久化子智能体的完整生命周期管理功能，包括创建、更新、删除和查询API接口。
新增了子智能体的JSON-RPC通信协议支持，实现了远程调用和任务管理功能。

同时增强了委派管理器的功能：
- 添加了对本地委派、插件委派和本地回退的开关控制
- 实现了持久化子智能体任务的自动检测和本地执行保护
- 增加了对不同委派类型的权限验证机制

修改了智能体注册表以支持插件智能体的条件性包含，并更新了工具注册逻辑以支持可选工具。

BREAKING CHANGE: 委派管理器的构造函数签名已更改，添加了新的控制参数。
```

app-instance/backend/nanobot/skills/subagent-manager/SKILL.md

@@ -0,0 +1,82 @@
+---
+name: subagent-manager
+description: Create, inspect, update, and remove persistent local A2A sub-agents. Use when the user wants Boardware Genius to manage sub-agents with their own workspace under ~/.nanobot/workspace/agents/<id>_agent, their own AGENTS.json and AGENTS.md, and local A2A visibility in the agent list.
+---
+
+# Subagent Manager
+
+Use this skill when the user wants to create or manage a persistent local sub-agent.
+
+## Required Rules
+
+- Persistent sub-agents must be created and updated only through `subagentctl.py` or `/api/subagents`.
+- Treat `~/.nanobot/workspace/agents/<id>_agent/AGENTS.json` as the source of truth.
+- Do not create a sub-agent by manually editing `workspace/agents/registry.json`.
+- Do not create ad-hoc layouts such as `workspace/agents/<id>/agent.json`, `main.py`, or `README.md` as a substitute for a persistent sub-agent.
+- Do not write `protocol: "local"` registry records for persistent sub-agents. A valid persistent sub-agent is registered automatically as local A2A with `protocol: "a2a"`.
+- Prefer the bundled script over hand-editing JSON files, because the script keeps `AGENTS.json`, `AGENTS.md`, and the registry entry consistent.
+
+## Workflow
+
+1. Inspect the current sub-agents first:
+   `uv run python nanobot/skills/subagent-manager/scripts/subagentctl.py list`
+2. Create or update the sub-agent with:
+   `uv run python nanobot/skills/subagent-manager/scripts/subagentctl.py create ...`
+3. Verify the generated workspace:
+   `~/.nanobot/workspace/agents/<id>_agent/`
+4. Verify the agent registry entry exists by checking `/api/agents` or `workspace/agents/registry.json`.
+5. If the user wants custom skills, edit files under:
+   `~/.nanobot/workspace/agents/<id>_agent/skills/`
+
+## Creation Standard
+
+When the user asks for a new specialized sub-agent, always:
+
+1. Choose a stable kebab-case id.
+2. Create it with `subagentctl.py create` or `POST /api/subagents`.
+3. Confirm the generated workspace is `~/.nanobot/workspace/agents/<id>_agent/`.
+4. Confirm `AGENTS.json` exists in that directory.
+5. Confirm the unified agent list shows the same id as a managed sub-agent entry.
+
+If the user asks for "an agent for X", interpret that as a persistent sub-agent when they want a reusable local worker with its own prompt, memory, skills, or MCP setup.
+
+## Repair Standard
+
+If you find a malformed "sub-agent" created through the wrong path, repair it instead of reusing the broken layout:
+
+1. Read any existing metadata that is useful, such as id, name, description, prompt, tags, aliases, or MCP config.
+2. Recreate the agent through `subagentctl.py create` or `/api/subagents`.
+3. Verify the new canonical directory `~/.nanobot/workspace/agents/<id>_agent/AGENTS.json`.
+4. Remove the malformed directory or stale registry entry only after the canonical sub-agent exists.
+
+Malformed examples include:
+
+- `workspace/agents/<id>/agent.json`
+- registry entries with `protocol: "local"`
+- agent folders that do not contain `AGENTS.json`
+
+## Commands
+
+- Create:
+  `uv run python nanobot/skills/subagent-manager/scripts/subagentctl.py create --id research-agent --name "Research Agent" --description "Research-focused local A2A sub-agent" --system-prompt "Focus on research tasks and be concise."`
+- Show:
+  `uv run python nanobot/skills/subagent-manager/scripts/subagentctl.py show research-agent`
+- Delete:
+  `uv run python nanobot/skills/subagent-manager/scripts/subagentctl.py delete research-agent`
+- Set system prompt:
+  `uv run python nanobot/skills/subagent-manager/scripts/subagentctl.py set-system-prompt research-agent --text "New prompt"`
+- Add HTTP MCP:
+  `uv run python nanobot/skills/subagent-manager/scripts/subagentctl.py add-mcp-http research-agent --server-id docs --url http://127.0.0.1:9000/mcp`
+- Add stdio MCP:
+  `uv run python nanobot/skills/subagent-manager/scripts/subagentctl.py add-mcp-stdio research-agent --server-id localtools --command npx --arg -y --arg @modelcontextprotocol/server-filesystem`
+- Remove MCP:
+  `uv run python nanobot/skills/subagent-manager/scripts/subagentctl.py remove-mcp research-agent --server-id docs`
+
+## Notes
+
+- `AGENTS.json` is the machine-readable source of truth for the sub-agent.
+- `AGENTS.md` is regenerated from `AGENTS.json` when the script updates the sub-agent.
+- Builtin skills remain available automatically. Workspace-specific skills live under the sub-agent workspace `skills/` directory.
+- This MVP exposes the sub-agent through local A2A `message/send` only.
+- New sub-agents default to `delegation_mode="remote_a2a_only"`: they can delegate outward only to remote A2A agents, not to local fallback or plugin agents.
+- A valid persistent sub-agent should appear in both `/api/subagents` and `/api/agents`.