feat: sub-agent design and skills

README.md

@@ -0,0 +1,92 @@
+# Reson Agent
+
+可扩展、可学习的 Agent 框架。
+
+## 快速开始
+
+### 1. 安装依赖
+
+```bash
+pip install -r requirements.txt
+```
+
+### 2. 配置环境变量
+
+```bash
+cp .env.example .env
+# 编辑 .env，添加你的 API 密钥
+```
+
+### 3. 创建 Skills
+
+在 `skills/` 目录下创建 `.md` 文件：
+
+```markdown
+---
+name: browser-use
+description: 浏览器自动化工具使用指南
+category: web-automation
+---
+
+## When to use
+- 需要访问网页、填写表单
+
+## Guidelines
+- 先运行 `browser-use state` 查看可点击元素
+- 使用元素索引进行交互
+```
+
+### 4. 运行 Agent
+
+```python
+from agent import AgentRunner
+from agent.llm.providers.gemini import create_gemini_llm_call
+import os
+
+runner = AgentRunner(
+    llm_call=create_gemini_llm_call(os.getenv("GEMINI_API_KEY"))
+)
+
+async for event in runner.run(
+    task="从网站提取数据",
+    tools=["skill", "list_skills", "bash"],
+    model="gemini-2.0-flash-exp"
+):
+    if event.type == "conclusion":
+        print(event.data["content"])
+```
+
+## 功能特性
+
+- 📚 **Skills 管理**: 使用 Markdown 文件定义领域知识
+- 🔧 **按需加载**: Agent 通过 `skill` 工具按需加载 skills
+- 🛠️ **工具系统**: 装饰器风格的工具定义和自动注册
+- 📊 **执行追踪**: 完整的 Trace 和 Step 记录
+
+## 项目结构
+
+```
+.
+├── agent/                  # 核心框架
+│   ├── runner.py          # Agent 执行引擎
+│   ├── models/            # 数据模型
+│   ├── storage/           # 存储接口和实现
+│   │   └── skill_loader.py  # Skills 加载器
+│   ├── tools/             # 工具系统
+│   └── llm/               # LLM 提供者
+├── tools/                  # 工具实现
+│   └── skill.py           # Skill 工具
+├── skills/                 # Skills 库
+│   └── browser-use.md
+└── examples/               # 示例代码
+```
+
+## 文档
+
+- [完整文档](docs/README.md) - 系统架构和设计
+- [Skills 指南](docs/skills.md) - Skills 使用指南
+- [工具系统](docs/tools.md) - 工具系统文档
+
+## License
+
+MIT

agent/__init__.py

@@ -3,6 +3,7 @@ Reson Agent - 可扩展、可学习的 Agent 框架
 
 核心导出：
 - AgentRunner: Agent 执行引擎
+- AgentConfig: Agent 配置
 - AgentEvent: Agent 事件
 - Trace, Step: 执行追踪
 - Experience, Skill: 记忆模型
@@ -10,7 +11,7 @@ Reson Agent - 可扩展、可学习的 Agent 框架
 - TraceStore, MemoryStore: 存储接口
 """
 
-from agent.runner import AgentRunner
+from agent.runner import AgentRunner, AgentConfig
 from agent.events import AgentEvent
 from agent.models.trace import Trace, Step, StepType
 from agent.models.memory import Experience, Skill
@@ -22,6 +23,7 @@ __version__ = "0.1.0"
 __all__ = [
     # Runner
     "AgentRunner",
+    "AgentConfig",
     # Events
     "AgentEvent",
     # Models

agent/runner.py

@@ -17,6 +17,7 @@ from agent.events import AgentEvent
 from agent.models.trace import Trace, Step
 from agent.models.memory import Experience, Skill
 from agent.storage.protocols import TraceStore, MemoryStore, StateStore
+from agent.storage.skill_loader import load_skills_from_dir
 from agent.tools import ToolRegistry, get_tool_registry
 
 logger = logging.getLogger(__name__)
@@ -239,16 +240,12 @@ class AgentRunner:
         })
 
         try:
-            # 加载记忆
-            skills_text = ""
+            # 加载记忆（仅 Experience）
             experiences_text = ""
 
             if enable_memory and self.memory_store:
                 scope = f"agent:{agent_type}"
-                skills = await self.memory_store.search_skills(scope, task)
                 experiences = await self.memory_store.search_experiences(scope, task)
-
-                skills_text = self._format_skills(skills)
                 experiences_text = self._format_experiences(experiences)
 
                 # 记录 memory_read Step
@@ -258,16 +255,13 @@ class AgentRunner:
                         step_type="memory_read",
                         sequence=0,
                         data={
-                            "skills_count": len(skills),
                             "experiences_count": len(experiences),
-                            "skills": [s.to_dict() for s in skills],
                             "experiences": [e.to_dict() for e in experiences],
                         }
                     )
                     await self.trace_store.add_step(mem_step)
 
                 yield AgentEvent("memory_loaded", {
-                    "skills_count": len(skills),
                     "experiences_count": len(experiences)
                 })
 
@@ -278,8 +272,6 @@ class AgentRunner:
             if system_prompt:
                 # 注入记忆到 system prompt
                 full_system = system_prompt
-                if skills_text:
-                    full_system += f"\n\n## 相关技能\n{skills_text}"
                 if experiences_text:
                     full_system += f"\n\n## 相关经验\n{experiences_text}"
 

agent/storage/skill_loader.py

@@ -0,0 +1,356 @@
+"""
+Skill Loader - 从 Markdown 文件加载 Skills
+
+支持两种格式：
+
+格式1 - YAML Frontmatter（推荐）：
+---
+name: skill-name
+description: Skill description
+category: category-name
+scope: agent:*
+parent: parent-id
+---
+
+## When to use
+- Use case 1
+- Use case 2
+
+## Guidelines
+- Guideline 1
+- Guideline 2
+
+格式2 - 行内元数据（向后兼容）：
+# Skill Name
+
+> category: web-automation
+> scope: agent:*
+
+## Description
+...
+
+## Guidelines
+...
+"""
+
+import os
+import re
+from pathlib import Path
+from typing import List, Dict, Optional
+import logging
+
+from agent.models.memory import Skill
+
+logger = logging.getLogger(__name__)
+
+
+class SkillLoader:
+    """从 Markdown 文件加载 Skills"""
+
+    def __init__(self, skills_dir: str):
+        """
+        初始化 SkillLoader
+
+        Args:
+            skills_dir: skills 目录路径
+        """
+        self.skills_dir = Path(skills_dir)
+        if not self.skills_dir.exists():
+            logger.warning(f"Skills 目录不存在: {skills_dir}")
+
+    def load_all(self) -> List[Skill]:
+        """
+        加载目录下所有 .md 文件
+
+        Returns:
+            Skill 列表
+        """
+        if not self.skills_dir.exists():
+            return []
+
+        skills = []
+        for md_file in self.skills_dir.glob("*.md"):
+            try:
+                skill = self.load_file(md_file)
+                if skill:
+                    skills.append(skill)
+                    logger.info(f"成功加载 skill: {skill.name} from {md_file.name}")
+            except Exception as e:
+                logger.error(f"加载 skill 失败 {md_file}: {e}")
+
+        return skills
+
+    def load_file(self, file_path: Path) -> Optional[Skill]:
+        """
+        从单个 Markdown 文件加载 Skill
+
+        Args:
+            file_path: Markdown 文件路径
+
+        Returns:
+            Skill 对象，解析失败返回 None
+        """
+        if not file_path.exists():
+            logger.warning(f"文件不存在: {file_path}")
+            return None
+
+        with open(file_path, "r", encoding="utf-8") as f:
+            content = f.read()
+
+        return self.parse_markdown(content, file_path.stem)
+
+    def parse_markdown(self, content: str, filename: str) -> Optional[Skill]:
+        """
+        解析 Markdown 内容为 Skill
+
+        支持两种格式：
+
+        格式1 - YAML Frontmatter（推荐）：
+        ---
+        name: skill-name
+        description: Skill description
+        category: category-name
+        scope: agent:*
+        ---
+
+        ## When to use
+        - Use case 1
+
+        ## Guidelines
+        - Guideline 1
+
+        格式2 - 行内元数据（向后兼容）：
+        # Skill Name
+
+        > category: web-automation
+        > scope: agent:*
+
+        ## Description
+        描述内容...
+
+        ## Guidelines
+        - 指导原则1
+
+        Args:
+            content: Markdown 内容
+            filename: 文件名（不含扩展名）
+
+        Returns:
+            Skill 对象
+        """
+        # 检测格式：是否有 YAML frontmatter
+        if content.strip().startswith("---"):
+            return self._parse_frontmatter_format(content, filename)
+        else:
+            return self._parse_inline_format(content, filename)
+
+    def _parse_frontmatter_format(self, content: str, filename: str) -> Optional[Skill]:
+        """
+        解析 YAML frontmatter 格式
+
+        ---
+        name: skill-name
+        description: Skill description
+        category: category-name
+        scope: agent:*
+        parent: parent-id
+        ---
+
+        ## When to use
+        ...
+
+        ## Guidelines
+        ...
+        """
+        lines = content.split("\n")
+
+        # 提取 YAML frontmatter
+        if not lines[0].strip() == "---":
+            logger.warning("格式错误：缺少开始的 ---")
+            return None
+
+        frontmatter = {}
+        i = 1
+        while i < len(lines):
+            line = lines[i].strip()
+            if line == "---":
+                break
+            if ":" in line:
+                key, value = line.split(":", 1)
+                frontmatter[key.strip()] = value.strip()
+            i += 1
+
+        # 提取元数据
+        name = frontmatter.get("name") or self._filename_to_title(filename)
+        description = frontmatter.get("description", "")
+        category = frontmatter.get("category", "general")
+        scope = frontmatter.get("scope", "agent:*")
+        parent_id = frontmatter.get("parent")
+
+        # 提取章节内容（从 frontmatter 之后开始）
+        remaining_content = "\n".join(lines[i+1:])
+        remaining_lines = remaining_content.split("\n")
+
+        # 提取 "When to use" 章节（可选）
+        when_to_use = self._extract_list_items(remaining_lines, "When to use")
+        if when_to_use:
+            # 将 "When to use" 添加到描述中
+            description += "\n\n适用场景：\n" + "\n".join(f"- {item}" for item in when_to_use)
+
+        # 提取 Guidelines
+        guidelines = self._extract_list_items(remaining_lines, "Guidelines")
+
+        # 创建 Skill
+        return Skill.create(
+            scope=scope,
+            name=name,
+            description=description.strip(),
+            category=category,
+            guidelines=guidelines,
+            parent_id=parent_id,
+        )
+
+    def _parse_inline_format(self, content: str, filename: str) -> Optional[Skill]:
+        """
+        解析行内元数据格式（向后兼容）
+
+        # Skill Name
+
+        > category: web-automation
+        > scope: agent:*
+
+        ## Description
+        ...
+
+        ## Guidelines
+        ...
+        """
+        lines = content.split("\n")
+
+        # 提取标题作为 name
+        name = self._extract_title(lines) or self._filename_to_title(filename)
+
+        # 提取元数据
+        metadata = self._extract_metadata(lines)
+        category = metadata.get("category", "general")
+        scope = metadata.get("scope", "agent:*")
+        parent_id = metadata.get("parent")
+
+        # 提取描述
+        description = self._extract_section(lines, "Description") or ""
+
+        # 提取指导原则
+        guidelines = self._extract_list_items(lines, "Guidelines")
+
+        # 创建 Skill
+        return Skill.create(
+            scope=scope,
+            name=name,
+            description=description.strip(),
+            category=category,
+            guidelines=guidelines,
+            parent_id=parent_id,
+        )
+
+    def _extract_title(self, lines: List[str]) -> Optional[str]:
+        """提取 # 标题"""
+        for line in lines:
+            line = line.strip()
+            if line.startswith("# "):
+                return line[2:].strip()
+        return None
+
+    def _filename_to_title(self, filename: str) -> str:
+        """将文件名转换为标题（kebab-case -> Title Case）"""
+        return " ".join(word.capitalize() for word in filename.split("-"))
+
+    def _extract_metadata(self, lines: List[str]) -> Dict[str, str]:
+        """
+        提取元数据块（> key: value）
+
+        Example:
+            > category: web-automation
+            > scope: agent:*
+        """
+        metadata = {}
+        for line in lines:
+            line = line.strip()
+            if line.startswith(">"):
+                # 去掉 > 符号
+                content = line[1:].strip()
+                # 分割 key: value
+                if ":" in content:
+                    key, value = content.split(":", 1)
+                    metadata[key.strip()] = value.strip()
+        return metadata
+
+    def _extract_section(self, lines: List[str], section_name: str) -> Optional[str]:
+        """
+        提取指定章节的内容
+
+        Args:
+            lines: 文件行列表
+            section_name: 章节名称（如 "Description"）
+
+        Returns:
+            章节内容（纯文本）
+        """
+        in_section = False
+        section_lines = []
+
+        for line in lines:
+            stripped = line.strip()
+
+            # 遇到目标章节
+            if stripped.startswith("## ") and section_name.lower() in stripped.lower():
+                in_section = True
+                continue
+
+            # 遇到下一个章节，结束
+            if in_section and stripped.startswith("##"):
+                break
+
+            # 收集章节内容
+            if in_section:
+                section_lines.append(line)
+
+        return "\n".join(section_lines).strip() if section_lines else None
+
+    def _extract_list_items(self, lines: List[str], section_name: str) -> List[str]:
+        """
+        提取指定章节的列表项
+
+        Args:
+            lines: 文件行列表
+            section_name: 章节名称（如 "Guidelines"）
+
+        Returns:
+            列表项数组
+        """
+        section_content = self._extract_section(lines, section_name)
+        if not section_content:
+            return []
+
+        items = []
+        for line in section_content.split("\n"):
+            line = line.strip()
+            # 匹配列表项（- item 或 * item）
+            if line.startswith("- ") or line.startswith("* "):
+                items.append(line[2:].strip())
+
+        return items
+
+
+# 便捷函数
+def load_skills_from_dir(skills_dir: str) -> List[Skill]:
+    """
+    从目录加载所有 Skills
+
+    Args:
+        skills_dir: skills 目录路径
+
+    Returns:
+        Skill 列表
+    """
+    loader = SkillLoader(skills_dir)
+    return loader.load_all()

docs/README.md

@@ -21,13 +21,15 @@
 
 **单次调用是 Agent 的特例**：
 
-| 特性 | 单次调用 | Agent 模式 |
-|------|---------|-----------|
-| 循环次数 | 1 | N (可配置) |
-| 工具调用 | 可选 | 常用 |
-| 状态管理 | 无 | 有 (Trace) |
-| 记忆检索 | 无 | 有 (Experience/Skill) |
-| 执行图 | 1 个节点 | N 个节点的 DAG |
+| 特性 | 单次调用 | Agent 模式 | Sub-Agent 模式 |
+|------|---------|-----------|--------------|
+| 循环次数 | 1 | N (可配置) | N (可配置，受限) |
+| 工具调用 | 可选 | 常用 | 受限工具集 |
+| 状态管理 | 无 | 有 (Trace) | 有 (独立 Trace + 父子关系) |
+| 记忆检索 | 无 | 有 (Experience/Skill) | 有 (继承主 Agent) |
+| 执行图 | 1 个节点 | N 个节点的 DAG | 嵌套 DAG（多个 Trace） |
+| 触发方式 | 直接调用 | 直接调用 | 通过 Task 工具 |
+| 权限范围 | 完整 | 完整 | 受限（可配置） |
 
 ---
 
@@ -209,6 +211,26 @@ Trace
 
 详细的模块文档请参阅：
 
+### [Sub-Agent 机制](./sub-agents.md)
+- Sub-Agent 架构和类型定义
+- Task Tool 实现
+- 权限隔离和层级管理
+- 内置 Sub-Agent（explore、general、analyst）
+- 自定义 Sub-Agent 配置
+
+**核心特性**：
+```python
+from agent.tools.builtin import task_tool
+
+# 主 Agent 通过 Task 工具启动 Sub-Agent
+result = await task_tool(
+    subagent_type="explore",
+    description="查找数据库配置",
+    prompt="在项目中查找所有数据库配置文件和连接代码",
+    ctx=tool_context
+)
+```
+
 ### [工具系统](./tools.md)
 - 工具定义和注册
 - 双层记忆管理
@@ -237,12 +259,11 @@ async def my_tool(arg: str, ctx: ToolContext) -> ToolResult:
 **存储**：Markdown 文件
 
 ```
-~/.reson/skills/           # 全局
-├── error-handling/SKILL.md
-└── data-processing/SKILL.md
-
-./project/.reson/skills/   # 项目级
-└── api-integration/SKILL.md
+./skills/                   # 项目级 skills 目录
+├── browser-use.md
+├── web-scraping.md
+├── api-integration.md
+└── error-handling.md
 ```
 
 **格式**：
@@ -265,7 +286,20 @@ description: Error handling best practices
 
 **加载**：通过 `skill` 工具动态加载
 
-**实现**：`agent/storage/skill_fs.py:SkillLoader`
+Agent 在需要时调用 `skill` 工具：
+```python
+# Agent 运行时
+await tools.execute("skill", {"skill_name": "browser-use"})
+```
+
+工具会读取文件并返回内容，注入到对话历史中。
+
+**实现**：
+- `agent/storage/skill_loader.py:SkillLoader` - Markdown 解析器
+- `tools/skill.py:load_skill()` - skill 工具实现
+- `tools/skill.py:list_skills()` - 列出可用 skills
+
+**详细文档**：参考 [`docs/skills.md`](./skills.md)
 
 ### Experiences（经验库）
 
@@ -408,7 +442,14 @@ agent/
 - [ ] 高级工具集成：Browser-Use、Search
 - [ ] 单次执行的监控与分析：Trace/Step 数据模型与文件系统存储、初步的执行历史可视化
 
-### Phase 2：反思能力
+### Phase 2：Sub-Agent 机制
+- [ ] Agent 定义系统：AgentDefinition、AgentRegistry
+- [ ] Trace 层级关系：parent_trace_id 支持
+- [ ] Task Tool：启动和管理 Sub-Agent
+- [ ] 内置 Sub-Agent：general、explore
+- [ ] 权限控制：工具过滤、路径限制
+
+### Phase 3：反思能力
 - [ ] Experience：feedback、归纳反思
 - [ ] 批量执行的监控与分析
 
@@ -421,6 +462,8 @@ agent/
 |------|------|------|------|
 | **Trace** | 一次任务执行 | 文件系统（JSON） | `models/trace.py` |
 | **Step** | 执行步骤 | 文件系统（JSON） | `models/trace.py` |
+| **Sub-Agent** | 专门化的子代理 | 独立 Trace | `tools/builtin/task.py` |
+| **AgentDefinition** | Agent 类型定义 | 配置文件/代码 | `models/agent.py` |
 | **Skill** | 能力描述（Markdown） | 文件系统 | `storage/skill_fs.py` |
 | **Experience** | 经验规则（条件+规则） | 数据库 + 向量 | `storage/experience_pg.py` |
 | **Tool** | 可调用的函数 | 内存（注册表） | `tools/registry.py` |

docs/skills.md

@@ -0,0 +1,120 @@
+# Skills 使用指南
+
+Skills 是 Agent 的领域知识库，存储在 Markdown 文件中。Agent 通过 `skill` 工具按需加载。
+
+## Skill 文件格式
+
+```markdown
+---
+name: browser-use
+description: 浏览器自动化工具使用指南
+category: web-automation
+scope: agent:*
+---
+
+## When to use
+- 需要访问网页、填写表单
+- 需要截图或提取网页内容
+
+## Guidelines
+- 先运行 `browser-use state` 查看可点击元素
+- 使用元素索引进行交互：`browser-use click 5`
+- 每次操作后验证结果
+```
+
+**Frontmatter 字段**：
+- `name`: Skill 名称（必填）
+- `description`: 简短描述（必填）
+- `category`: 分类（可选，默认 general）
+- `scope`: 作用域（可选，默认 agent:*）
+
+**章节**：
+- `## When to use`: 适用场景列表
+- `## Guidelines`: 指导原则列表
+
+## 使用方法
+
+### 1. 创建 skills 目录
+
+```bash
+mkdir skills
+```
+
+### 2. 添加 skill 文件
+
+创建 `skills/browser-use.md` 文件，按照上述格式编写。
+
+### 3. Agent 调用
+
+Agent 在运行时可以调用 skill 工具：
+
+```python
+from agent import AgentRunner
+from agent.llm.providers.gemini import create_gemini_llm_call
+import os
+
+runner = AgentRunner(
+    llm_call=create_gemini_llm_call(os.getenv("GEMINI_API_KEY"))
+)
+
+async for event in runner.run(
+    task="帮我从网站提取数据",
+    tools=["skill", "list_skills", "bash"],
+    model="gemini-2.0-flash-exp"
+):
+    if event.type == "conclusion":
+        print(event.data["content"])
+```
+
+**Agent 工作流**：
+1. Agent 接收任务
+2. Agent 调用 `list_skills()` 查看可用 skills
+3. Agent 调用 `skill(skill_name="browser-use")` 加载需要的 skill
+4. Skill 内容注入到对话历史
+5. Agent 根据 skill 指导完成任务
+
+### 4. 手动测试
+
+```python
+from tools.skill import list_skills, skill
+
+# 列出所有 skills
+result = await list_skills()
+print(result.output)
+
+# 加载特定 skill
+result = await skill(skill_name="browser-use")
+print(result.output)
+```
+
+## Skill 工具
+
+### `skill` 工具
+
+加载指定的 skill 文档。
+
+**参数**：
+- `skill_name` (str): Skill 名称，如 "browser-use"
+
+**返回**：Skill 的完整内容（Markdown 格式）
+
+### `list_skills` 工具
+
+列出所有可用的 skills，按 category 分组。
+
+**返回**：Skills 列表，包含名称、ID 和简短描述
+
+## 环境变量
+
+可以设置默认 skills 目录：
+
+```bash
+# .env
+SKILLS_DIR=./skills
+```
+
+## 参考
+
+- 示例: `examples/skills_example.py`
+- Skill 文件: `skills/` 目录
+- 工具实现: `tools/skill.py`

docs/sub-agents-quickref.md

@@ -0,0 +1,274 @@
+# Sub-Agent 快速参考
+
+## 什么是 Sub-Agent？
+
+Sub-Agent 是在独立 Trace 中运行的专门化 Agent，用于处理特定类型的子任务。
+
+## 核心概念
+
+- **主 Agent (Primary)**: 直接接收用户请求，可以启动 Sub-Agent
+- **Sub-Agent**: 由主 Agent 通过 Task 工具启动，处理特定子任务
+- **Task Tool**: 启动 Sub-Agent 的工具
+- **Trace 层级**: Sub-Agent 运行在独立的 Trace 中，通过 parent_trace_id 关联
+
+## 内置 Sub-Agent
+
+| 名称 | 用途 | 允许工具 | 典型场景 |
+|------|------|---------|---------|
+| `general` | 通用多步骤任务 | 所有工具（除 task） | 数据收集、复杂分析 |
+| `explore` | 代码探索 | read, search, list | 查找代码、理解结构 |
+| `analyst` | 深度分析 | read, search, web | 技术栈分析、报告 |
+
+## 快速开始
+
+### 1. 主 Agent 调用 Sub-Agent
+
+```python
+from agent import AgentRunner, AgentConfig
+
+# 主 Agent 会自动知道如何使用 Sub-Agent
+runner = AgentRunner(llm_call=your_llm, config=AgentConfig())
+
+async for event in runner.run(
+    task="使用 explore sub-agent 分析这个项目的架构"
+):
+    # 处理事件
+    pass
+```
+
+### 2. 定义自定义 Sub-Agent
+
+```python
+from agent.models.agent import AgentDefinition
+from agent.agent_registry import get_agent_registry
+
+# 定义
+custom_agent = AgentDefinition(
+    name="code-reviewer",
+    description="代码审查专家",
+    mode="subagent",
+    allowed_tools=["read_file", "search_code"],
+    system_prompt="你是代码审查专家...",
+)
+
+# 注册
+get_agent_registry().register(custom_agent)
+```
+
+### 3. 配置文件方式
+
+创建 `sub_agents.json`:
+
+```json
+{
+  "agents": {
+    "my-agent": {
+      "description": "我的自定义 Agent",
+      "mode": "subagent",
+      "allowed_tools": ["read_file", "search_code"],
+      "system_prompt": "..."
+    }
+  }
+}
+```
+
+加载配置:
+
+```python
+get_agent_registry().load_from_config("sub_agents.json")
+```
+
+## Agent 模式
+
+- `primary`: 主 Agent，可以被用户直接调用，可以启动 Sub-Agent
+- `subagent`: Sub-Agent，只能被其他 Agent 通过 Task 工具调用
+- `all`: 两者皆可
+
+## 权限控制
+
+### 工具级别
+
+```python
+AgentDefinition(
+    allowed_tools=["read_file", "search_code"],  # 白名单
+    denied_tools=["write_file", "execute_bash"], # 黑名单
+)
+```
+
+### 路径级别
+
+```python
+AgentDefinition(
+    permissions={
+        "paths": {
+            "/etc": "deny",
+            "~/.ssh": "deny",
+            "/tmp": "allow",
+        }
+    }
+)
+```
+
+### 防止递归
+
+```python
+AgentDefinition(
+    can_spawn_subagent=False,  # 默认为 False
+    denied_tools=["task"],     # 显式禁止 Task 工具
+)
+```
+
+## 事件监控
+
+```python
+async for event in runner.run(task="..."):
+    if event.type == "tool_call" and event.data["tool"] == "task":
+        # Sub-Agent 启动
+        print(f"启动: {event.data['args']['subagent_type']}")
+
+    elif event.type == "tool_result" and event.data["tool"] == "task":
+        # Sub-Agent 完成
+        metadata = event.data["metadata"]
+        print(f"完成: {metadata['sub_trace_id']}")
+```
+
+## Trace 查询
+
+```python
+from agent.storage import TraceStore
+
+# 获取主 Trace
+main_trace = await trace_store.get_trace(trace_id)
+
+# 查询所有子 Trace
+sub_traces = await trace_store.query_traces(
+    parent_trace_id=trace_id
+)
+
+# 获取 Sub-Agent 的详细步骤
+for sub_trace in sub_traces:
+    steps = await trace_store.get_steps(sub_trace.trace_id)
+    print(f"{sub_trace.agent_type}: {len(steps)} steps")
+```
+
+## 最佳实践
+
+### 1. 合理选择 Sub-Agent
+
+- 只读任务 → `explore`
+- 多步骤复杂任务 → `general`
+- 专业领域分析 → 自定义 Sub-Agent
+
+### 2. 限制权限
+
+```python
+# ✅ 好的实践：最小权限原则
+AgentDefinition(
+    allowed_tools=["read_file", "search_code"],  # 只给必要的工具
+    can_spawn_subagent=False,                    # 禁止嵌套
+)
+
+# ❌ 避免：过于宽松的权限
+AgentDefinition(
+    allowed_tools=None,  # 所有工具都可用
+    can_spawn_subagent=True,  # 允许无限嵌套
+)
+```
+
+### 3. 设置合理的迭代次数
+
+```python
+AgentDefinition(
+    max_iterations=15,  # 探索型任务：10-20 次
+    # max_iterations=30,  # 复杂分析任务：20-40 次
+)
+```
+
+### 4. 优化 System Prompt
+
+```python
+system_prompt = """你是 XXX 专家。
+
+专注于：
+1. [核心职责 1]
+2. [核心职责 2]
+
+注意事项：
+- [限制条件 1]
+- [限制条件 2]
+
+输出格式：
+[期望的输出格式]
+"""
+```
+
+### 5. 监控成本
+
+```python
+# 在 Trace 中追踪每个 Sub-Agent 的成本
+trace = await trace_store.get_trace(trace_id)
+print(f"总成本: ${trace.total_cost:.4f}")
+print(f"Token 消耗: {trace.total_tokens}")
+
+# 查看子 Trace 的成本
+for sub_trace in await trace_store.query_traces(parent_trace_id=trace_id):
+    print(f"  {sub_trace.agent_type}: ${sub_trace.total_cost:.4f}")
+```
+
+## 常见问题
+
+### Q: Sub-Agent 可以启动其他 Sub-Agent 吗？
+
+A: 默认不可以。可以通过设置 `can_spawn_subagent=True` 允许，但要注意：
+- 设置最大嵌套深度（建议 2-3 层）
+- 监控成本和性能
+- 避免无限递归
+
+### Q: 如何限制 Sub-Agent 的执行时间？
+
+A: 可以通过以下方式：
+```python
+AgentDefinition(
+    max_iterations=10,  # 限制迭代次数
+    permissions={
+        "limits": {
+            "timeout_seconds": 120  # 2 分钟超时
+        }
+    }
+)
+```
+
+### Q: Sub-Agent 可以访问主 Agent 的上下文吗？
+
+A: 可以通过 Task Tool 传递必要的上下文：
+```python
+# 主 Agent
+prompt = f"""
+分析用户 {user_id} 的项目 {project_id}。
+
+项目路径: {project_path}
+关注点: {focus_areas}
+"""
+
+task_tool(
+    subagent_type="explore",
+    description="分析项目",
+    prompt=prompt,  # 完整的上下文信息
+    ctx=ctx
+)
+```
+
+### Q: 如何调试 Sub-Agent 的行为？
+
+A:
+1. 查看 Trace 和 Steps
+2. 启用详细日志
+3. 检查工具调用历史
+4. 使用可视化工具分析调用链
+
+## 相关文档
+
+- [完整设计文档](../docs/sub-agents.md)
+- [使用示例](../examples/subagent_example.py)
+- [配置示例](../sub_agents.json.example)
+- [架构文档](../docs/README.md)

docs/sub-agents.md

@@ -0,0 +1,697 @@
+# Sub-Agent 机制设计
+
+> **可执行规格书**：本文档定义 Sub-Agent 架构。代码修改必须同步更新此文档。
+>
+> 📖 **快速开始**：查看 [快速参考指南](./sub-agents-quickref.md) 了解常用操作
+
+---
+
+## 概述
+
+**Sub-Agent** 是在独立 Trace 中运行的专门化 Agent，用于处理复杂的子任务。
+
+### 核心特性
+
+- **任务隔离**：每个 Sub-Agent 在独立的 Trace 中运行，有完整的执行记录
+- **权限控制**：Sub-Agent 有独立的权限配置，限制其行为范围
+- **层级关系**：通过 `parent_trace_id` 建立父子关系，支持多层嵌套
+- **专门化**：不同类型的 Sub-Agent 专注于特定领域（如代码探索、研究分析）
+- **防止递归**：默认禁止 Sub-Agent 再启动其他 Sub-Agent，避免无限嵌套
+
+### 与主 Agent 的区别
+
+| 特性 | 主 Agent (Primary) | Sub-Agent |
+|------|-------------------|-----------|
+| 触发方式 | 用户直接调用 | 主 Agent 通过 Task 工具调用 |
+| 运行环境 | 独立 Trace | 独立 Trace（有父 Trace） |
+| 权限范围 | 完整权限 | 受限权限（可配置） |
+| 工具访问 | 所有工具 | 受限工具集 |
+| 可见性 | 用户可见 | 主 Agent 可见，用户可选可见 |
+
+---
+
+## 架构设计
+
+### 1. Agent 类型定义
+
+```python
+# agent/models/agent.py
+
+@dataclass
+class AgentDefinition:
+    """Agent 定义"""
+    name: str
+    description: Optional[str] = None
+    mode: Literal["primary", "subagent", "all"] = "all"
+
+    # 权限配置
+    permissions: Dict[str, Any] = field(default_factory=dict)
+
+    # 工具限制
+    allowed_tools: Optional[List[str]] = None
+    denied_tools: Optional[List[str]] = None
+
+    # 模型配置
+    model: Optional[str] = None
+    temperature: Optional[float] = None
+    max_iterations: Optional[int] = None
+
+    # 自定义 System Prompt
+    system_prompt: Optional[str] = None
+
+    # 是否可以调用其他 Sub-Agent
+    can_spawn_subagent: bool = False
+```
+
+**实现位置**：`agent/models/agent.py:AgentDefinition`
+
+### 2. Trace 层级关系
+
+```python
+# agent/models/trace.py (扩展现有模型)
+
+@dataclass
+class Trace:
+    trace_id: str
+    mode: Literal["call", "agent"]
+
+    # 新增：Sub-Agent 支持
+    parent_trace_id: Optional[str] = None  # 父 Trace ID
+    agent_definition: Optional[str] = None  # Agent 类型名称
+    spawned_by_tool: Optional[str] = None   # 启动此 Sub-Agent 的工具调用 ID
+
+    # 原有字段...
+    task: Optional[str] = None
+    agent_type: Optional[str] = None
+    status: Literal["running", "completed", "failed"] = "running"
+    # ...
+```
+
+**实现位置**：`agent/models/trace.py:Trace`（扩展现有类）
+
+### 3. Task Tool 实现
+
+Task Tool 是启动 Sub-Agent 的核心工具：
+
+```python
+# agent/tools/builtin/task.py
+
+@tool(
+    name="task",
+    description="启动sub-agent处理复杂的子任务",
+    requires_confirmation=False
+)
+async def task_tool(
+    subagent_type: str,  # Sub-Agent 类型
+    description: str,     # 任务简短描述（3-5词）
+    prompt: str,          # 详细任务描述
+    ctx: ToolContext
+) -> ToolResult:
+    """
+    启动一个 Sub-Agent 执行子任务
+
+    Args:
+        subagent_type: Sub-Agent 类型（如 "explore", "general"）
+        description: 任务简短描述
+        prompt: 完整的任务描述
+        ctx: 工具上下文
+
+    Returns:
+        Sub-Agent 的执行结果
+    """
+    # 1. 验证 Sub-Agent 类型
+    agent_def = await get_agent_definition(subagent_type)
+    if not agent_def or agent_def.mode == "primary":
+        raise ValueError(f"Invalid subagent type: {subagent_type}")
+
+    # 2. 检查权限
+    if not ctx.current_agent.can_spawn_subagent:
+        raise PermissionError("Current agent cannot spawn sub-agents")
+
+    # 3. 创建子 Trace
+    sub_trace = Trace.create(
+        mode="agent",
+        parent_trace_id=ctx.trace_id,
+        agent_definition=subagent_type,
+        spawned_by_tool=ctx.step_id,
+        task=prompt,
+        agent_type=subagent_type,
+        context={
+            "parent_task": ctx.trace.task,
+            "description": description,
+        }
+    )
+    sub_trace_id = await ctx.trace_store.create_trace(sub_trace)
+
+    # 4. 配置 Sub-Agent Runner
+    sub_config = AgentConfig(
+        agent_type=subagent_type,
+        max_iterations=agent_def.max_iterations or 10,
+        # 继承父 Agent 的某些配置
+        skills_dir=ctx.runner.config.skills_dir,
+    )
+
+    sub_runner = AgentRunner(
+        trace_store=ctx.trace_store,
+        memory_store=ctx.memory_store,
+        state_store=ctx.state_store,
+        tool_registry=_build_restricted_registry(agent_def),
+        llm_call=ctx.runner.llm_call,
+        config=sub_config,
+    )
+
+    # 5. 运行 Sub-Agent（收集所有事件）
+    events = []
+    async for event in sub_runner.run(
+        task=prompt,
+        model=agent_def.model or ctx.model,
+        trace_id=sub_trace_id,
+    ):
+        events.append(event)
+        # 可选：将事件转发给父 Agent
+
+    # 6. 提取结果
+    conclusion_events = [e for e in events if e.type == "conclusion"]
+    final_result = conclusion_events[-1].data["content"] if conclusion_events else ""
+
+    # 7. 生成摘要
+    tool_summary = _summarize_tool_calls(events)
+
+    output = f"{final_result}\n\n<task_metadata>\n"
+    output += f"sub_trace_id: {sub_trace_id}\n"
+    output += f"total_steps: {len(events)}\n"
+    output += f"tool_calls: {tool_summary}\n"
+    output += "</task_metadata>"
+
+    return ToolResult(
+        title=description,
+        output=output,
+        metadata={
+            "sub_trace_id": sub_trace_id,
+            "subagent_type": subagent_type,
+            "tool_summary": tool_summary,
+        }
+    )
+
+
+def _build_restricted_registry(agent_def: AgentDefinition) -> ToolRegistry:
+    """根据 Agent 定义构建受限的工具注册表"""
+    registry = ToolRegistry()
+    global_registry = get_tool_registry()
+
+    for tool_name, tool_def in global_registry.tools.items():
+        # 检查是否在允许列表中
+        if agent_def.allowed_tools and tool_name not in agent_def.allowed_tools:
+            continue
+
+        # 检查是否在拒绝列表中
+        if agent_def.denied_tools and tool_name in agent_def.denied_tools:
+            continue
+
+        registry.register_tool(tool_def)
+
+    # 默认禁止 task 工具（防止递归）
+    if not agent_def.can_spawn_subagent:
+        registry.tools.pop("task", None)
+
+    return registry
+
+
+def _summarize_tool_calls(events: List[AgentEvent]) -> str:
+    """总结工具调用情况"""
+    tool_calls = [e for e in events if e.type == "tool_call"]
+    summary = {}
+    for event in tool_calls:
+        tool = event.data.get("tool", "unknown")
+        summary[tool] = summary.get(tool, 0) + 1
+
+    return ", ".join(f"{tool}×{count}" for tool, count in summary.items())
+```
+
+**实现位置**：`agent/tools/builtin/task.py:task_tool`
+
+---
+
+## 内置 Sub-Agent 类型
+
+### 1. general - 通用型
+
+**用途**：执行复杂的多步骤任务和研究分析
+
+```python
+GENERAL_AGENT = AgentDefinition(
+    name="general",
+    description="通用型 Sub-Agent，用于执行复杂的多步骤任务和研究分析",
+    mode="subagent",
+    allowed_tools=None,  # 允许所有工具
+    denied_tools=["task"],  # 禁止启动其他 Sub-Agent
+    max_iterations=20,
+)
+```
+
+**典型使用场景**：
+- 多步骤的数据收集和分析
+- 复杂的文件处理任务
+- 需要多个工具协同的任务
+
+### 2. explore - 探索型
+
+**用途**：快速探索代码库，查找文件和代码
+
+```python
+EXPLORE_AGENT = AgentDefinition(
+    name="explore",
+    description="探索型 Sub-Agent，专门用于快速探索代码库、查找文件和搜索代码",
+    mode="subagent",
+    allowed_tools=[
+        "read_file",
+        "list_files",
+        "search_code",
+        "search_files",
+    ],
+    denied_tools=[
+        "write_file",
+        "edit_file",
+        "execute_bash",
+        "task",
+    ],
+    max_iterations=15,
+    system_prompt="""你是一个代码探索专家。专注于：
+1. 快速定位相关文件和代码
+2. 理解代码结构和依赖关系
+3. 总结关键信息
+
+注意：
+- 你只能读取和搜索，不能编辑或执行代码
+- 优先使用搜索工具，而不是逐个读取文件
+- 提供清晰的文件路径和行号引用
+""",
+)
+```
+
+**典型使用场景**：
+- "找出所有使用了 Redis 的代码"
+- "分析 API 路由的实现方式"
+- "查找配置文件的加载逻辑"
+
+### 3. analyst - 分析型
+
+**用途**：深度分析和报告生成
+
+```python
+ANALYST_AGENT = AgentDefinition(
+    name="analyst",
+    description="分析型 Sub-Agent，专注于深度分析和报告生成",
+    mode="subagent",
+    allowed_tools=[
+        "read_file",
+        "list_files",
+        "search_code",
+        "web_search",
+        "fetch_url",
+    ],
+    denied_tools=["task", "write_file", "edit_file"],
+    max_iterations=25,
+    temperature=0.3,  # 更精确的分析
+)
+```
+
+**典型使用场景**：
+- 技术栈分析
+- 性能瓶颈分析
+- 安全审计报告
+
+---
+
+## Agent 配置系统
+
+### 配置文件格式
+
+```json
+{
+  "agents": {
+    "custom-reviewer": {
+      "description": "代码审查专家",
+      "mode": "subagent",
+      "allowed_tools": ["read_file", "search_code", "list_files"],
+      "denied_tools": ["write_file", "edit_file", "execute_bash"],
+      "max_iterations": 10,
+      "temperature": 0.2,
+      "system_prompt": "你是一个代码审查专家...",
+      "can_spawn_subagent": false
+    },
+    "my-primary": {
+      "description": "自定义主 Agent",
+      "mode": "primary",
+      "can_spawn_subagent": true
+    }
+  },
+  "default_agent": "my-primary"
+}
+```
+
+### 加载和管理
+
+```python
+# agent/agent_registry.py
+
+class AgentRegistry:
+    """Agent 注册表"""
+
+    def __init__(self):
+        self.agents: Dict[str, AgentDefinition] = {}
+        self._load_builtin_agents()
+
+    def _load_builtin_agents(self):
+        """加载内置 Agent"""
+        self.register(GENERAL_AGENT)
+        self.register(EXPLORE_AGENT)
+        self.register(ANALYST_AGENT)
+
+    def load_from_config(self, config_path: str):
+        """从配置文件加载自定义 Agent"""
+        import json
+        with open(config_path) as f:
+            config = json.load(f)
+
+        for name, cfg in config.get("agents", {}).items():
+            agent_def = AgentDefinition(
+                name=name,
+                **cfg
+            )
+            self.register(agent_def)
+
+    def register(self, agent: AgentDefinition):
+        """注册 Agent"""
+        self.agents[agent.name] = agent
+
+    def get(self, name: str) -> Optional[AgentDefinition]:
+        """获取 Agent 定义"""
+        return self.agents.get(name)
+
+    def list_subagents(self) -> List[AgentDefinition]:
+        """列出所有可用的 Sub-Agent"""
+        return [
+            agent for agent in self.agents.values()
+            if agent.mode in ("subagent", "all")
+        ]
+
+
+# 全局注册表
+_agent_registry = AgentRegistry()
+
+def get_agent_registry() -> AgentRegistry:
+    """获取全局 Agent 注册表"""
+    return _agent_registry
+
+async def get_agent_definition(name: str) -> Optional[AgentDefinition]:
+    """获取 Agent 定义"""
+    return _agent_registry.get(name)
+```
+
+**实现位置**：`agent/agent_registry.py:AgentRegistry`
+
+---
+
+## 权限控制
+
+### 权限模型
+
+每个 Agent 可以定义细粒度的权限：
+
+```python
+PERMISSIONS_EXAMPLE = {
+    # 工具级别权限
+    "tools": {
+        "write_file": "deny",
+        "read_file": "allow",
+        "execute_bash": "deny",
+    },
+
+    # 路径级别权限
+    "paths": {
+        "/etc": "deny",
+        "/tmp": "allow",
+        "~/.ssh": "deny",
+    },
+
+    # 网络级别权限
+    "network": {
+        "allowed_domains": ["*.example.com", "api.github.com"],
+        "blocked_domains": ["*.evil.com"],
+    },
+
+    # 资源限制
+    "limits": {
+        "max_file_size": 10_000_000,  # 10MB
+        "max_iterations": 15,
+        "timeout_seconds": 300,
+    }
+}
+```
+
+### 权限检查流程
+
+```python
+# agent/permission.py
+
+class PermissionChecker:
+    """权限检查器"""
+
+    def __init__(self, agent_def: AgentDefinition):
+        self.agent_def = agent_def
+        self.permissions = agent_def.permissions
+
+    def check_tool_access(self, tool_name: str) -> bool:
+        """检查工具访问权限"""
+        # 检查拒绝列表
+        if self.agent_def.denied_tools and tool_name in self.agent_def.denied_tools:
+            return False
+
+        # 检查允许列表
+        if self.agent_def.allowed_tools and tool_name not in self.agent_def.allowed_tools:
+            return False
+
+        # 检查工具权限配置
+        tool_perms = self.permissions.get("tools", {})
+        if tool_perms.get(tool_name) == "deny":
+            return False
+
+        return True
+
+    def check_path_access(self, path: str, mode: str = "read") -> bool:
+        """检查路径访问权限"""
+        path_perms = self.permissions.get("paths", {})
+
+        for pattern, action in path_perms.items():
+            if self._match_path(path, pattern):
+                return action == "allow"
+
+        # 默认允许读取，拒绝写入
+        return mode == "read"
+
+    def _match_path(self, path: str, pattern: str) -> bool:
+        """路径匹配（支持通配符）"""
+        import fnmatch
+        return fnmatch.fnmatch(path, pattern)
+```
+
+**实现位置**：`agent/permission.py:PermissionChecker`
+
+---
+
+## 使用示例
+
+### 1. 主 Agent 调用 Sub-Agent
+
+```python
+# 主 Agent 的 System Prompt 中会包含 Task 工具说明
+system_prompt = """
+你是一个智能助手。当遇到复杂任务时，可以使用 task 工具启动专门的 Sub-Agent。
+
+可用的 Sub-Agent：
+- explore: 探索代码库，查找文件和代码
+- general: 执行复杂的多步骤任务
+- analyst: 深度分析和报告生成
+
+示例：
+用户："这个项目用了哪些数据库？"
+你：使用 task(subagent_type="explore", description="查找数据库使用", prompt="...")
+"""
+
+# 主 Agent 执行时
+async for event in runner.run(task="分析这个项目的架构"):
+    if event.type == "tool_call" and event.data["tool"] == "task":
+        # Sub-Agent 被启动
+        print(f"启动 Sub-Agent: {event.data['args']['subagent_type']}")
+```
+
+### 2. 自定义 Sub-Agent
+
+```python
+from agent import AgentRunner, AgentConfig
+from agent.agent_registry import get_agent_registry
+from agent.models.agent import AgentDefinition
+
+# 1. 定义自定义 Sub-Agent
+custom_agent = AgentDefinition(
+    name="security-scanner",
+    description="安全扫描专家",
+    mode="subagent",
+    allowed_tools=["read_file", "search_code", "list_files"],
+    system_prompt="""你是一个安全扫描专家。专注于：
+1. 查找常见安全漏洞（SQL注入、XSS、CSRF等）
+2. 检查敏感信息泄露（密钥、密码等）
+3. 分析依赖项的安全问题
+
+输出格式：
+- 漏洞类型
+- 影响范围
+- 修复建议
+""",
+    max_iterations=20,
+)
+
+# 2. 注册到全局注册表
+get_agent_registry().register(custom_agent)
+
+# 3. 主 Agent 可以调用它
+# 在 System Prompt 中会自动列出这个新的 Sub-Agent
+```
+
+### 3. 监控 Sub-Agent 执行
+
+```python
+from agent.storage import TraceStore
+
+async def analyze_subagent_performance(trace_id: str, trace_store: TraceStore):
+    """分析 Sub-Agent 性能"""
+    trace = await trace_store.get_trace(trace_id)
+    steps = await trace_store.get_steps(trace_id)
+
+    # 找出所有 Sub-Agent 调用
+    subagent_calls = []
+    for step in steps:
+        if step.step_type == "tool_call" and step.data.get("tool") == "task":
+            sub_trace_id = step.data.get("result", {}).get("metadata", {}).get("sub_trace_id")
+            if sub_trace_id:
+                sub_trace = await trace_store.get_trace(sub_trace_id)
+                subagent_calls.append({
+                    "type": sub_trace.agent_type,
+                    "task": sub_trace.task,
+                    "steps": sub_trace.total_steps,
+                    "tokens": sub_trace.total_tokens,
+                    "cost": sub_trace.total_cost,
+                })
+
+    # 生成报告
+    print(f"主任务: {trace.task}")
+    print(f"Sub-Agent 调用次数: {len(subagent_calls)}")
+    for i, call in enumerate(subagent_calls, 1):
+        print(f"\n{i}. {call['type']}")
+        print(f"   任务: {call['task'][:50]}...")
+        print(f"   步骤: {call['steps']}, Token: {call['tokens']}, 成本: ${call['cost']:.4f}")
+```
+
+---
+
+## 实现计划
+
+### Phase 1: 基础架构（MVP）
+
+- [ ] **AgentDefinition 模型** (`agent/models/agent.py`)
+  - 定义 Agent 类型、权限、配置
+
+- [ ] **Trace 扩展** (`agent/models/trace.py`)
+  - 添加 `parent_trace_id`、`agent_definition` 等字段
+
+- [ ] **AgentRegistry** (`agent/agent_registry.py`)
+  - Agent 注册和管理
+  - 加载内置和自定义 Agent
+
+- [ ] **Task Tool** (`agent/tools/builtin/task.py`)
+  - 实现 Sub-Agent 启动逻辑
+  - Trace 层级管理
+  - 结果聚合
+
+- [ ] **内置 Sub-Agent** (`agent/builtin_agents.py`)
+  - `general`: 通用型
+  - `explore`: 探索型
+
+### Phase 2: 权限控制
+
+- [ ] **PermissionChecker** (`agent/permission.py`)
+  - 工具级别权限检查
+  - 路径级别权限检查
+  - 资源限制检查
+
+- [ ] **受限 ToolRegistry** (`agent/tools/builtin/task.py`)
+  - 根据 Agent 定义过滤工具
+
+### Phase 3: 高级特性
+
+- [ ] **配置系统**
+  - JSON 配置文件支持
+  - 动态加载自定义 Agent
+
+- [ ] **监控和分析**
+  - Sub-Agent 性能统计
+  - 调用链可视化
+
+- [ ] **递归控制**
+  - 嵌套深度限制
+  - 循环检测
+
+---
+
+## 集成点
+
+### 与现有系统的集成
+
+1. **AgentRunner** (`agent/runner.py`)
+   - 扩展 `run()` 方法支持 `agent_definition` 参数
+   - 根据 Agent 定义配置工具和权限
+
+2. **ToolRegistry** (`agent/tools/registry.py`)
+   - 添加 Task 工具到全局注册表
+   - 支持工具过滤和权限检查
+
+3. **TraceStore** (`agent/storage/protocols.py`)
+   - 支持根据 `parent_trace_id` 查询子 Trace
+   - 添加层级查询方法
+
+4. **Events** (`agent/events.py`)
+   - 添加 Sub-Agent 相关事件类型
+   - `subagent_started`、`subagent_completed`
+
+---
+
+## 注意事项
+
+1. **防止无限递归**
+   - 默认禁止 Sub-Agent 调用 Task 工具
+   - 设置最大嵌套深度（建议 3 层）
+
+2. **性能考虑**
+   - Sub-Agent 增加了额外的 LLM 调用开销
+   - 合理设置 `max_iterations` 限制
+
+3. **成本控制**
+   - 跟踪每个 Sub-Agent 的 token 消耗
+   - 在父 Trace 中聚合成本统计
+
+4. **错误处理**
+   - Sub-Agent 失败不应导致主任务完全失败
+   - 提供降级策略（如超时、重试）
+
+5. **可观测性**
+   - 完整记录 Sub-Agent 的执行过程
+   - 支持调用链追踪和分析
+
+---
+
+## 参考资料
+
+- OpenCode 实现：`/Users/sunlit/Code/opencode/packages/opencode/src/tool/task.ts`
+- OpenCode Agent 定义：`/Users/sunlit/Code/opencode/packages/opencode/src/agent/agent.ts`
+- 当前项目架构：`docs/README.md`

examples/README_gemini_agent.md

@@ -1,165 +0,0 @@
-# Gemini Agent 测试成功 ✅
-
-## 问题诊断与修复
-
-### 🔍 发现的问题
-
-1. **消息历史丢失**
-   - **问题**：tool 消息缺少 `name` 字段
-   - **位置**：`agent/runner.py:417`
-   - **修复**：添加 `name: tool_name` 字段到 tool 消息
-
-2. **架构设计不当**
-   - **问题**：模型封装放在 example 中，应该在基础模块
-   - **修复**：创建 `agent/llm/providers/gemini.py` 模块
-
-3. **SDK 兼容性问题**
-   - **问题**：`google-generativeai` SDK 对参数格式要求严格，与 OpenAI JSON Schema 不兼容
-   - **修复**：使用 HTTP REST API（`httpx`）代替 SDK
-
-### ✅ 最终方案
-
-#### 1. HTTP API Provider（推荐）
-
-**文件**：`agent/llm/providers/gemini.py`
-
-**特性**：
-- 使用 `httpx` 直接调用 Gemini REST API
-- 完全控制消息格式转换
-- 正确处理：
-  - `systemInstruction`
-  - `functionCall` / `functionResponse`
-  - 连续 user 消息合并（Gemini 要求严格的 user/model 交替）
-
-**关键实现**：
-
-```python
-def _convert_messages_to_gemini(messages):
-    """OpenAI -> Gemini 格式转换"""
-    # 1. system -> systemInstruction
-    # 2. assistant + tool_calls -> model + functionCall
-    # 3. tool -> user + functionResponse
-    # 4. 合并连续的 user 消息
-    ...
-
-def _convert_tools_to_gemini(tools):
-    """工具定义转换，清理不支持的字段（default）"""
-    ...
-```
-
-#### 2. 使用方式
-
-```python
-from agent.llm.providers.gemini import create_gemini_llm_call
-from agent.runner import AgentRunner
-
-# 创建 LLM 调用函数
-gemini_llm_call = create_gemini_llm_call()
-
-# 创建 Agent
-runner = AgentRunner(
-    tool_registry=registry,
-    llm_call=gemini_llm_call
-)
-
-# 运行
-async for event in runner.run(
-    task="你的任务",
-    model="gemini-2.5-pro",
-    tools=["tool1", "tool2"],
-    system_prompt="系统提示"
-):
-    # 处理事件
-    ...
-```
-
-## 测试结果
-
-**任务**："北京今天的天气怎么样？顺便帮我计算一下 15 * 8 等于多少。"
-
-**执行流程**：
-```
-1. [Gemini HTTP] Converted 1 messages: ['user']
-   → 调用工具: get_current_weather, calculate
-
-2. [Gemini HTTP] Converted 3 messages: ['user', 'model', 'user']
-   → 生成答案: "北京今天天气晴朗，15摄氏度。15 * 8 的计算结果是 120。"
-
-✓ Trace 完成
-  总 Tokens: 643
-```
-
-**结果**：✅ 完美运行，没有重复调用，正确结束
-
-## 架构对比
-
-### ❌ 之前（错误）
-
-```
-examples/
-└── gemini_basic_agent.py  # 包含所有逻辑
-    ├── 工具定义
-    ├── Gemini SDK 调用
-    └── Agent 运行
-```
-
-**问题**：
-- 模型封装混在示例中
-- 使用 SDK 导致兼容性问题
-- 消息历史处理有bug
-
-### ✅ 现在（正确）
-
-```
-agent/
-├── llm/
-│   └── providers/
-│       └── gemini.py          # HTTP API 封装
-├── tools/
-│   └── registry.py            # 工具注册
-└── runner.py                  # Agent 运行器
-
-examples/
-└── gemini_basic_agent.py      # 简洁的示例代码
-    ├── 工具定义
-    └── 使用 agent.llm.providers
-```
-
-**优势**：
-- 清晰的模块分层
-- 易于扩展（添加其他 provider）
-- HTTP API 完全控制格式
-
-## 依赖
-
-```bash
-pip install httpx python-dotenv
-
-# 如果有代理
-pip install 'httpx[socks]'
-```
-
-## 环境变量
-
-```bash
-# .env
-GEMINI_API_KEY=your_api_key_here
-```
-
-## 参考
-
-- Resonote 实现：`/Users/sunlit/Code/Resonote/llm/providers/gemini.py`
-- Gemini REST API 文档：https://ai.google.dev/api/rest
-
-## 下一步
-
-可以扩展支持更多 LLM provider：
-- OpenAI（已有 SDK）
-- Claude（Anthropic API）
-- DeepSeek
-- 本地模型（Ollama）
-
-每个 provider 只需实现相同的接口：
-```python
-async def llm_call(messages, model, tools, **kwargs) -> Dict
-```

examples/feature_extract/input_1/feature.md

@@ -0,0 +1,5 @@
+  {
+    "核心视觉特征": "整体构图",
+    "具体表现": "画面采用中心构图与引导线构图相结合，林间小路从画面底部中央向远方延伸，形成视觉引导线，将观众视线引向远处的骑行者和光束。画面下方约1/2的垂直高度（约350像素）有水坑倒影，宽度覆盖整个画面（1200像素），形成对称构图，增强了画面的平衡感和层次感。画面左右两侧高大的树木形成自然的拱形通道，将主体框选在其中。",
+    "评分": 0.652
+  }

examples/feature_extract/input_1/feature_extract.prompt

@@ -0,0 +1,27 @@
+---
+model: gemini-2.5-flash
+temperature: 0.3
+---
+
+$system$
+# 角色
+你是一位计算机视觉专家，也是一位才华横溢的社媒博主、内容创作者。
+
+# 任务
+分析一个优质内容的指定特征适合如何表示，并完成该特征的提取。
+提取的特征将用于在生成类似内容时作为参考内容（所以要保留重要信息），也会和其他内容的同一维度的特征放在一起聚类发现规律（所以特征表示要尽量精简、不要过于具体），或用于模型训练。
+
+# 工具
+- 你可以加载browser-use的skill，并根据skill中的指引操作浏览器，来做调研或检索
+- 可以使用 task 工具启动专门的 Sub-Agent。
+
+可用的 Sub-Agent：
+- tool_builder: 编写代码来创建指定工具，并配置好工具所需环境、对外提供API
+- tool_deployer: 完成指定的开源代码工具的环境配置与部署，对外提供API
+
+$user$
+# 指定的特征：
+%text%
+
+# 结果保存路径
+/Users/sunlit/Code/Agent/examples/feature_extract/output_1/

examples/subagent_example.py

@@ -0,0 +1,229 @@
+"""
+Sub-Agent 使用示例
+
+演示如何使用 Sub-Agent 机制处理复杂任务。
+"""
+
+import asyncio
+import os
+from agent import AgentRunner, AgentConfig
+from agent.llm.providers.gemini import create_gemini_llm_call
+from agent.agent_registry import get_agent_registry
+from agent.models.agent import AgentDefinition
+
+
+async def example_basic_subagent():
+    """示例 1: 使用内置 Sub-Agent"""
+    print("=== 示例 1: 使用内置 Sub-Agent ===\n")
+
+    # 配置主 Agent
+    config = AgentConfig(
+        agent_type="primary",
+        max_iterations=20,
+        skills_dir="./skills",
+    )
+
+    runner = AgentRunner(
+        llm_call=create_gemini_llm_call(os.getenv("GEMINI_API_KEY")),
+        config=config,
+    )
+
+    # 主 Agent 会自动知道如何使用 Task 工具启动 Sub-Agent
+    task = """
+    分析这个 Python 项目的架构：
+    1. 找出所有主要的模块和它们的职责
+    2. 识别核心的数据流
+    3. 列出使用的外部依赖
+
+    请使用 explore sub-agent 来探索代码库。
+    """
+
+    async for event in runner.run(task=task, model="gemini-2.0-flash-exp"):
+        if event.type == "tool_call" and event.data.get("tool") == "task":
+            print(f"🚀 启动 Sub-Agent: {event.data['args']['subagent_type']}")
+            print(f"   任务: {event.data['args']['description']}")
+
+        elif event.type == "tool_result" and event.data.get("tool") == "task":
+            metadata = event.data.get("metadata", {})
+            print(f"✅ Sub-Agent 完成")
+            print(f"   Sub-Trace ID: {metadata.get('sub_trace_id')}")
+            print(f"   工具调用: {metadata.get('tool_summary')}")
+
+        elif event.type == "conclusion":
+            print(f"\n📋 最终结果:\n{event.data['content']}")
+
+
+async def example_custom_subagent():
+    """示例 2: 定义和使用自定义 Sub-Agent"""
+    print("\n=== 示例 2: 自定义 Sub-Agent ===\n")
+
+    # 1. 定义自定义 Sub-Agent
+    security_scanner = AgentDefinition(
+        name="security-scanner",
+        description="安全扫描专家，查找常见漏洞和安全问题",
+        mode="subagent",
+        allowed_tools=[
+            "read_file",
+            "search_code",
+            "list_files",
+        ],
+        denied_tools=[
+            "write_file",
+            "edit_file",
+            "execute_bash",
+        ],
+        system_prompt="""你是一个安全扫描专家。专注于：
+
+1. 查找常见安全漏洞：
+   - SQL 注入
+   - XSS 攻击
+   - CSRF 漏洞
+   - 不安全的序列化
+   - 路径遍历
+
+2. 检查敏感信息泄露：
+   - 硬编码的密钥和密码
+   - API token
+   - 数据库凭据
+
+3. 依赖项安全：
+   - 过时的依赖
+   - 已知漏洞的包
+
+输出格式：
+- **漏洞类型**: [类型名称]
+- **严重程度**: [高/中/低]
+- **位置**: [文件路径:行号]
+- **描述**: [详细说明]
+- **修复建议**: [如何修复]
+""",
+        max_iterations=25,
+        temperature=0.2,  # 更精确的分析
+    )
+
+    # 2. 注册到全局注册表
+    get_agent_registry().register(security_scanner)
+    print(f"✓ 注册自定义 Sub-Agent: {security_scanner.name}")
+
+    # 3. 使用自定义 Sub-Agent
+    config = AgentConfig(
+        agent_type="primary",
+        max_iterations=20,
+    )
+
+    runner = AgentRunner(
+        llm_call=create_gemini_llm_call(os.getenv("GEMINI_API_KEY")),
+        config=config,
+    )
+
+    task = """
+    对这个项目进行安全审计，使用 security-scanner sub-agent。
+    重点关注：
+    1. 认证和授权相关代码
+    2. 数据库交互代码
+    3. 用户输入处理
+    """
+
+    async for event in runner.run(task=task, model="gemini-2.0-flash-exp"):
+        if event.type == "tool_call" and event.data.get("tool") == "task":
+            print(f"🔍 启动安全扫描...")
+
+        elif event.type == "conclusion":
+            print(f"\n🔒 安全审计报告:\n{event.data['content']}")
+
+
+async def example_multiple_subagents():
+    """示例 3: 并行使用多个 Sub-Agent"""
+    print("\n=== 示例 3: 并行使用多个 Sub-Agent ===\n")
+
+    config = AgentConfig(
+        agent_type="primary",
+        max_iterations=30,
+    )
+
+    runner = AgentRunner(
+        llm_call=create_gemini_llm_call(os.getenv("GEMINI_API_KEY")),
+        config=config,
+    )
+
+    task = """
+    完整分析这个项目：
+
+    1. 使用 explore sub-agent 探索代码结构
+    2. 使用 analyst sub-agent 分析技术栈和依赖
+    3. 综合两个分析结果，给出项目概览
+
+    可以并行启动多个 sub-agent 来加快速度。
+    """
+
+    subagent_results = {}
+
+    async for event in runner.run(task=task, model="gemini-2.0-flash-exp"):
+        if event.type == "tool_call" and event.data.get("tool") == "task":
+            agent_type = event.data['args']['subagent_type']
+            print(f"🔄 启动 Sub-Agent: {agent_type}")
+
+        elif event.type == "tool_result" and event.data.get("tool") == "task":
+            metadata = event.data.get("metadata", {})
+            agent_type = metadata.get("subagent_type")
+            subagent_results[agent_type] = {
+                "sub_trace_id": metadata.get("sub_trace_id"),
+                "summary": metadata.get("tool_summary"),
+            }
+            print(f"✅ {agent_type} 完成: {metadata.get('tool_summary')}")
+
+        elif event.type == "conclusion":
+            print(f"\n📊 综合分析报告:\n{event.data['content']}")
+            print(f"\n📈 Sub-Agent 使用统计:")
+            for agent_type, result in subagent_results.items():
+                print(f"  - {agent_type}: {result['summary']}")
+
+
+async def example_subagent_config_file():
+    """示例 4: 从配置文件加载 Sub-Agent"""
+    print("\n=== 示例 4: 配置文件方式 ===\n")
+
+    # 1. 从配置文件加载
+    # 假设有 sub_agents.json:
+    # {
+    #   "agents": {
+    #     "code-reviewer": {
+    #       "description": "代码审查专家",
+    #       "mode": "subagent",
+    #       "allowed_tools": ["read_file", "search_code"],
+    #       "system_prompt": "你是代码审查专家..."
+    #     }
+    #   }
+    # }
+
+    registry = get_agent_registry()
+
+    # 如果配置文件存在
+    config_path = "sub_agents.json"
+    if os.path.exists(config_path):
+        registry.load_from_config(config_path)
+        print(f"✓ 从 {config_path} 加载 Agent 配置")
+
+    # 2. 列出所有可用的 Sub-Agent
+    print("\n可用的 Sub-Agent:")
+    for agent in registry.list_subagents():
+        print(f"  - {agent.name}: {agent.description}")
+
+
+async def main():
+    """运行所有示例"""
+    # 示例 1: 基本使用
+    await example_basic_subagent()
+
+    # 示例 2: 自定义 Sub-Agent
+    await example_custom_subagent()
+
+    # 示例 3: 并行使用多个 Sub-Agent
+    await example_multiple_subagents()
+
+    # 示例 4: 配置文件方式
+    await example_subagent_config_file()
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

examples/test_skill.py

@@ -0,0 +1,36 @@
+"""
+Skills 使用示例
+
+演示如何测试 skill 工具
+"""
+
+import asyncio
+from tools.skill import list_skills, skill
+
+
+async def main():
+    """测试 skill 工具"""
+
+    # 1. 列出所有 skills
+    print("=" * 60)
+    print("测试 list_skills")
+    print("=" * 60)
+
+    result = await list_skills()
+    print(f"Title: {result.title}")
+    print(f"Output:\n{result.output}")
+    print()
+
+    # 2. 加载特定 skill
+    print("=" * 60)
+    print("测试 skill")
+    print("=" * 60)
+
+    result = await skill(skill_name="browser-use")
+    print(f"Title: {result.title}")
+    print(f"Output:\n{result.output[:500]}...")
+    print()
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

skills/browser-use.md

@@ -0,0 +1,218 @@
+---
+name: browser-use
+description: Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, or extract information from web pages.
+allowed-tools: Bash(browser-use:*)
+---
+
+# Browser Automation with browser-use CLI
+
+The `browser-use` command provides fast, persistent browser automation. It maintains browser sessions across commands, enabling complex multi-step workflows.
+
+## Quick Start
+
+```bash
+browser-use open https://example.com           # Navigate to URL
+browser-use state                              # Get page elements with indices
+browser-use click 5                            # Click element by index
+browser-use type "Hello World"                 # Type text
+browser-use screenshot                         # Take screenshot
+browser-use close                              # Close browser
+```
+
+## Core Workflow
+
+1. **Navigate**: `browser-use open <url>` - Opens URL (starts browser if needed)
+2. **Inspect**: `browser-use state` - Returns clickable elements with indices
+3. **Interact**: Use indices from state to interact (`browser-use click 5`, `browser-use input 3 "text"`)
+4. **Verify**: `browser-use state` or `browser-use screenshot` to confirm actions
+5. **Repeat**: Browser stays open between commands
+
+## Browser Modes
+
+```bash
+browser-use --browser chromium open <url>      # Default: headless Chromium
+browser-use --browser chromium --headed open <url>  # Visible Chromium window
+browser-use --browser real open <url>          # User's Chrome with login sessions
+browser-use --browser remote open <url>        # Cloud browser (requires API key)
+```
+
+- **chromium**: Fast, isolated, headless by default
+- **real**: Uses your Chrome with cookies, extensions, logged-in sessions
+- **remote**: Cloud-hosted browser with proxy support (requires BROWSER_USE_API_KEY)
+
+## Commands
+
+### Navigation
+```bash
+browser-use open <url>                    # Navigate to URL
+browser-use back                          # Go back in history
+browser-use scroll down                   # Scroll down
+browser-use scroll up                     # Scroll up
+```
+
+### Page State
+```bash
+browser-use state                         # Get URL, title, and clickable elements
+browser-use screenshot                    # Take screenshot (outputs base64)
+browser-use screenshot path.png           # Save screenshot to file
+browser-use screenshot --full path.png    # Full page screenshot
+```
+
+### Interactions (use indices from `browser-use state`)
+```bash
+browser-use click <index>                 # Click element
+browser-use type "text"                   # Type text into focused element
+browser-use input <index> "text"          # Click element, then type text
+browser-use keys "Enter"                  # Send keyboard keys
+browser-use keys "Control+a"              # Send key combination
+browser-use select <index> "option"       # Select dropdown option
+```
+
+### Tab Management
+```bash
+browser-use switch <tab>                  # Switch to tab by index
+browser-use close-tab                     # Close current tab
+browser-use close-tab <tab>               # Close specific tab
+```
+
+### JavaScript & Data
+```bash
+browser-use eval "document.title"         # Execute JavaScript, return result
+browser-use extract "all product prices"  # Extract data using LLM (requires API key)
+```
+
+### Python Execution (Persistent Session)
+```bash
+browser-use python "x = 42"               # Set variable
+browser-use python "print(x)"             # Access variable (outputs: 42)
+browser-use python "print(browser.url)"   # Access browser object
+browser-use python --vars                 # Show defined variables
+browser-use python --reset                # Clear Python namespace
+browser-use python --file script.py       # Execute Python file
+```
+
+The Python session maintains state across commands. The `browser` object provides:
+- `browser.url` - Current page URL
+- `browser.title` - Page title
+- `browser.goto(url)` - Navigate
+- `browser.click(index)` - Click element
+- `browser.type(text)` - Type text
+- `browser.screenshot(path)` - Take screenshot
+- `browser.scroll()` - Scroll page
+- `browser.html` - Get page HTML
+
+### Agent Tasks (Requires API Key)
+```bash
+browser-use run "Fill the contact form with test data"    # Run AI agent
+browser-use run "Extract all product prices" --max-steps 50
+```
+
+Agent tasks use an LLM to autonomously complete complex browser tasks. Requires `BROWSER_USE_API_KEY` or configured LLM API key (OPENAI_API_KEY, ANTHROPIC_API_KEY, etc).
+
+### Session Management
+```bash
+browser-use sessions                      # List active sessions
+browser-use close                         # Close current session
+browser-use close --all                   # Close all sessions
+```
+
+### Server Control
+```bash
+browser-use server status                 # Check if server is running
+browser-use server stop                   # Stop server
+browser-use server logs                   # View server logs
+```
+
+## Global Options
+
+| Option | Description |
+|--------|-------------|
+| `--session NAME` | Use named session (default: "default") |
+| `--browser MODE` | Browser mode: chromium, real, remote |
+| `--headed` | Show browser window (chromium mode) |
+| `--profile NAME` | Chrome profile (real mode only) |
+| `--json` | Output as JSON |
+| `--api-key KEY` | Override API key |
+
+**Session behavior**: All commands without `--session` use the same "default" session. The browser stays open and is reused across commands. Use `--session NAME` to run multiple browsers in parallel.
+
+## Examples
+
+### Form Submission
+```bash
+browser-use open https://example.com/contact
+browser-use state
+# Shows: [0] input "Name", [1] input "Email", [2] textarea "Message", [3] button "Submit"
+browser-use input 0 "John Doe"
+browser-use input 1 "john@example.com"
+browser-use input 2 "Hello, this is a test message."
+browser-use click 3
+browser-use state  # Verify success
+```
+
+### Multi-Session Workflows
+```bash
+browser-use --session work open https://work.example.com
+browser-use --session personal open https://personal.example.com
+browser-use --session work state    # Check work session
+browser-use --session personal state  # Check personal session
+browser-use close --all             # Close both sessions
+```
+
+### Data Extraction with Python
+```bash
+browser-use open https://example.com/products
+browser-use python "
+products = []
+for i in range(20):
+    browser.scroll('down')
+browser.screenshot('products.png')
+"
+browser-use python "print(f'Captured {len(products)} products')"
+```
+
+### Using Real Browser (Logged-In Sessions)
+```bash
+browser-use --browser real open https://gmail.com
+# Uses your actual Chrome with existing login sessions
+browser-use state  # Already logged in!
+```
+
+## Tips
+
+1. **Always run `browser-use state` first** to see available elements and their indices
+2. **Use `--headed` for debugging** to see what the browser is doing
+3. **Sessions persist** - the browser stays open between commands
+4. **Use `--json` for parsing** output programmatically
+5. **Python variables persist** across `browser-use python` commands within a session
+6. **Real browser mode** preserves your login sessions and extensions
+
+## Troubleshooting
+
+**Browser won't start?**
+```bash
+browser-use server stop               # Stop any stuck server
+browser-use --headed open <url>       # Try with visible window
+```
+
+**Element not found?**
+```bash
+browser-use state                     # Check current elements
+browser-use scroll down               # Element might be below fold
+browser-use state                     # Check again
+```
+
+**Session issues?**
+```bash
+browser-use sessions                  # Check active sessions
+browser-use close --all               # Clean slate
+browser-use open <url>                # Fresh start
+```
+
+## Cleanup
+
+**Always close the browser when done.** Run this after completing browser automation:
+
+```bash
+browser-use close
+```

sub_agents.json

@@ -0,0 +1,137 @@
+{
+  "agents": {
+    "code-reviewer": {
+      "description": "代码审查专家，专注于代码质量和最佳实践",
+      "mode": "subagent",
+      "allowed_tools": [
+        "read_file",
+        "search_code",
+        "list_files"
+      ],
+      "denied_tools": [
+        "write_file",
+        "edit_file",
+        "execute_bash",
+        "task"
+      ],
+      "max_iterations": 15,
+      "temperature": 0.2,
+      "system_prompt": "你是一个代码审查专家。专注于：\n\n1. 代码质量\n   - 可读性和可维护性\n   - 命名规范\n   - 注释质量\n\n2. 最佳实践\n   - 设计模式的正确使用\n   - SOLID 原则\n   - DRY 原则\n\n3. 潜在问题\n   - 性能问题\n   - 内存泄漏\n   - 边界条件\n\n输出格式：\n- **文件**: [路径]\n- **问题**: [描述]\n- **严重程度**: [高/中/低]\n- **建议**: [改进建议]\n- **示例**: [可选的代码示例]",
+      "can_spawn_subagent": false
+    },
+
+    "security-scanner": {
+      "description": "安全扫描专家，查找安全漏洞和敏感信息泄露",
+      "mode": "subagent",
+      "allowed_tools": [
+        "read_file",
+        "search_code",
+        "list_files"
+      ],
+      "denied_tools": [
+        "write_file",
+        "edit_file",
+        "execute_bash",
+        "task"
+      ],
+      "max_iterations": 20,
+      "temperature": 0.1,
+      "system_prompt": "你是一个安全扫描专家。专注于：\n\n1. 常见漏洞\n   - SQL 注入\n   - XSS 攻击\n   - CSRF 漏洞\n   - 不安全的反序列化\n\n2. 敏感信息\n   - 硬编码的密钥\n   - API tokens\n   - 数据库凭据\n\n3. 配置安全\n   - 不安全的默认配置\n   - 过于宽松的权限\n\n输出格式：\n- **漏洞类型**: [类型]\n- **位置**: [文件:行号]\n- **严重程度**: [高/中/低]\n- **描述**: [详细说明]\n- **修复建议**: [如何修复]",
+      "can_spawn_subagent": false,
+      "permissions": {
+        "paths": {
+          "/etc": "deny",
+          "~/.ssh": "deny",
+          "/tmp": "allow"
+        }
+      }
+    },
+
+    "doc-writer": {
+      "description": "文档编写专家，生成和改进项目文档",
+      "mode": "subagent",
+      "allowed_tools": [
+        "read_file",
+        "search_code",
+        "list_files",
+        "write_file"
+      ],
+      "denied_tools": [
+        "execute_bash",
+        "task"
+      ],
+      "max_iterations": 15,
+      "temperature": 0.5,
+      "system_prompt": "你是一个文档编写专家。专注于：\n\n1. 文档结构\n   - 清晰的层次\n   - 合理的章节划分\n   - 完整的目录\n\n2. 内容质量\n   - 准确性\n   - 示例代码\n   - 使用场景\n\n3. 文档类型\n   - README\n   - API 文档\n   - 教程\n   - 架构设计文档\n\n输出格式：使用 Markdown",
+      "can_spawn_subagent": false
+    },
+
+    "performance-analyzer": {
+      "description": "性能分析专家，识别性能瓶颈和优化机会",
+      "mode": "subagent",
+      "allowed_tools": [
+        "read_file",
+        "search_code",
+        "list_files",
+        "execute_bash"
+      ],
+      "denied_tools": [
+        "write_file",
+        "edit_file",
+        "task"
+      ],
+      "max_iterations": 25,
+      "temperature": 0.2,
+      "system_prompt": "你是一个性能分析专家。专注于：\n\n1. 性能问题识别\n   - N+1 查询\n   - 不必要的计算\n   - 内存泄漏\n   - 阻塞操作\n\n2. 优化建议\n   - 缓存策略\n   - 数据库索引\n   - 并发处理\n   - 批量操作\n\n3. 基准测试\n   - 关键路径分析\n   - 性能指标\n\n输出格式：\n- **问题**: [描述]\n- **位置**: [文件:函数]\n- **影响**: [响应时间/内存/CPU]\n- **优化建议**: [具体方案]\n- **预期收益**: [性能提升估算]",
+      "can_spawn_subagent": false
+    },
+
+    "test-writer": {
+      "description": "测试编写专家，生成单元测试和集成测试",
+      "mode": "subagent",
+      "allowed_tools": [
+        "read_file",
+        "search_code",
+        "list_files",
+        "write_file"
+      ],
+      "denied_tools": [
+        "execute_bash",
+        "task"
+      ],
+      "max_iterations": 20,
+      "temperature": 0.3,
+      "system_prompt": "你是一个测试编写专家。专注于：\n\n1. 测试覆盖\n   - 核心功能\n   - 边界条件\n   - 错误处理\n\n2. 测试质量\n   - 可读性\n   - 独立性\n   - 可维护性\n\n3. 测试类型\n   - 单元测试\n   - 集成测试\n   - 端到端测试\n\n遵循 AAA 模式：Arrange, Act, Assert",
+      "can_spawn_subagent": false
+    },
+
+    "my-primary-agent": {
+      "description": "自定义主 Agent，具有完整权限",
+      "mode": "primary",
+      "can_spawn_subagent": true,
+      "max_iterations": 30,
+      "temperature": 0.7
+    }
+  },
+
+  "default_agent": "my-primary-agent",
+
+  "permissions": {
+    "global": {
+      "tools": {
+        "execute_bash": "ask",
+        "write_file": "ask"
+      },
+      "paths": {
+        "/etc": "deny",
+        "~/.ssh": "deny",
+        "/tmp": "allow"
+      },
+      "network": {
+        "blocked_domains": [
+          "*.evil.com"
+        ]
+      }
+    }
+  }
+}

tools/browser-use/.python-version

@@ -0,0 +1 @@
+3.11

tools/browser-use/main.py

@@ -0,0 +1,6 @@
+def main():
+    print("Hello from browser-use!")
+
+
+if __name__ == "__main__":
+    main()

tools/browser-use/pyproject.toml

@@ -0,0 +1,9 @@
+[project]
+name = "browser-use-tool"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.11"
+dependencies = [
+    "browser-use>=0.1.0",
+]

tools/browser-use/uv.lock

@@ -0,0 +1,3264 @@
+version = 1
+revision = 3
+requires-python = ">=3.11"
+resolution-markers = [
+    "python_full_version >= '3.14'",
+    "python_full_version == '3.13.*'",
+    "python_full_version < '3.13'",
+]
+
+[[package]]
+name = "aiodns"
+version = "4.0.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "pycares" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/10/da/97235e953109936bfeda62c1f9f1a7c5652d4dc49f2b5911f9ae1043afa9/aiodns-4.0.0.tar.gz", hash = "sha256:17be26a936ba788c849ba5fd20e0ba69d8c46e6273e846eb5430eae2630ce5b1", size = 26204, upload-time = "2026-01-10T22:33:27.211Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/d0/60/14ac40c03e8a26216e4f2642497b776e52f9e3214e4fd537628829bbb082/aiodns-4.0.0-py3-none-any.whl", hash = "sha256:a188a75fb8b2b7862ac8f84811a231402fb74f5b4e6f10766dc8a4544b0cf989", size = 11334, upload-time = "2026-01-10T22:33:25.65Z" },
+]
+
+[[package]]
+name = "aiohappyeyeballs"
+version = "2.6.1"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/26/30/f84a107a9c4331c14b2b586036f40965c128aa4fee4dda5d3d51cb14ad54/aiohappyeyeballs-2.6.1.tar.gz", hash = "sha256:c3f9d0113123803ccadfdf3f0faa505bc78e6a72d1cc4806cbd719826e943558", size = 22760, upload-time = "2025-03-12T01:42:48.764Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/0f/15/5bf3b99495fb160b63f95972b81750f18f7f4e02ad051373b669d17d44f2/aiohappyeyeballs-2.6.1-py3-none-any.whl", hash = "sha256:f349ba8f4b75cb25c99c5c2d84e997e485204d2902a9597802b0371f09331fb8", size = 15265, upload-time = "2025-03-12T01:42:47.083Z" },
+]
+
+[[package]]
+name = "aiohttp"
+version = "3.13.3"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "aiohappyeyeballs" },
+    { name = "aiosignal" },
+    { name = "attrs" },
+    { name = "frozenlist" },
+    { name = "multidict" },
+    { name = "propcache" },
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+]

tools/skill.py

@@ -0,0 +1,190 @@
+"""
+Skill 工具 - 按需加载 Skill 文件
+
+Agent 可以调用此工具来加载特定的 skill 文档
+"""
+
+import os
+from pathlib import Path
+from typing import Optional
+
+from agent.tools import tool, ToolResult
+from agent.storage.skill_loader import SkillLoader
+
+# 默认 skills 目录
+DEFAULT_SKILLS_DIR = os.getenv("SKILLS_DIR", "./skills")
+
+
+@tool(
+    description="加载指定的 skill 文档。Skills 提供领域知识和最佳实践指导。"
+)
+async def skill(
+    skill_name: str,
+    skills_dir: Optional[str] = None,
+    uid: str = ""
+) -> ToolResult:
+    """
+    加载指定的 skill 文档
+
+    Args:
+        skill_name: Skill 名称（如 "browser-use", "error-handling"）
+        skills_dir: Skills 目录路径（可选，默认使用环境变量或 ./skills）
+        uid: 用户 ID（自动注入）
+
+    Returns:
+        ToolResult: 包含 skill 的详细内容
+    """
+    # 确定 skills 目录
+    skills_path = Path(skills_dir or DEFAULT_SKILLS_DIR)
+
+    if not skills_path.exists():
+        return ToolResult(
+            title="Skills 目录不存在",
+            output=f"找不到 skills 目录: {skills_path}",
+            error=f"Directory not found: {skills_path}"
+        )
+
+    # 查找文件（支持 skill-name.md 或 skill_name.md）
+    skill_file = None
+    for ext in [".md"]:
+        for name_format in [skill_name, skill_name.replace("-", "_"), skill_name.replace("_", "-")]:
+            candidate = skills_path / f"{name_format}{ext}"
+            if candidate.exists():
+                skill_file = candidate
+                break
+        if skill_file:
+            break
+
+    if not skill_file:
+        # 列出可用的 skills
+        available_skills = [f.stem for f in skills_path.glob("*.md")]
+        return ToolResult(
+            title=f"Skill '{skill_name}' 未找到",
+            output=f"可用的 skills: {', '.join(available_skills)}",
+            error=f"Skill not found: {skill_name}"
+        )
+
+    # 加载 skill
+    try:
+        loader = SkillLoader(str(skills_path))
+        skill_obj = loader.load_file(skill_file)
+
+        if not skill_obj:
+            return ToolResult(
+                title="加载失败",
+                output=f"无法解析 skill 文件: {skill_file.name}",
+                error="Failed to parse skill file"
+            )
+
+        # 格式化输出
+        output = f"# {skill_obj.name}\n\n"
+        output += f"**Category**: {skill_obj.category}\n\n"
+
+        if skill_obj.description:
+            output += f"## Description\n\n{skill_obj.description}\n\n"
+
+        if skill_obj.guidelines:
+            output += f"## Guidelines\n\n"
+            for i, guideline in enumerate(skill_obj.guidelines, 1):
+                output += f"{i}. {guideline}\n"
+            output += "\n"
+
+        return ToolResult(
+            title=f"Skill: {skill_obj.name}",
+            output=output,
+            long_term_memory=f"已加载 skill: {skill_obj.name} ({skill_obj.category})",
+            include_output_only_once=True,  # skill 内容只展示一次
+            metadata={
+                "skill_name": skill_obj.name,
+                "category": skill_obj.category,
+                "scope": skill_obj.scope,
+                "guidelines_count": len(skill_obj.guidelines)
+            }
+        )
+
+    except Exception as e:
+        return ToolResult(
+            title="加载错误",
+            output=f"加载 skill 时出错: {str(e)}",
+            error=str(e)
+        )
+
+
+@tool(
+    description="列出所有可用的 skills"
+)
+async def list_skills(
+    skills_dir: Optional[str] = None,
+    uid: str = ""
+) -> ToolResult:
+    """
+    列出所有可用的 skills
+
+    Args:
+        skills_dir: Skills 目录路径（可选）
+        uid: 用户 ID（自动注入）
+
+    Returns:
+        ToolResult: 包含所有 skills 的列表
+    """
+    skills_path = Path(skills_dir or DEFAULT_SKILLS_DIR)
+
+    if not skills_path.exists():
+        return ToolResult(
+            title="Skills 目录不存在",
+            output=f"找不到 skills 目录: {skills_path}",
+            error=f"Directory not found: {skills_path}"
+        )
+
+    try:
+        loader = SkillLoader(str(skills_path))
+        skills = loader.load_all()
+
+        if not skills:
+            return ToolResult(
+                title="没有可用的 Skills",
+                output="skills 目录中没有找到任何 .md 文件",
+                metadata={"count": 0}
+            )
+
+        # 按 category 分组
+        by_category = {}
+        for skill_obj in skills:
+            category = skill_obj.category or "general"
+            if category not in by_category:
+                by_category[category] = []
+            by_category[category].append(skill_obj)
+
+        # 格式化输出
+        output = f"# 可用的 Skills ({len(skills)} 个)\n\n"
+
+        for category in sorted(by_category.keys()):
+            output += f"## {category.title()}\n\n"
+            for skill_obj in by_category[category]:
+                skill_id = skill_obj.skill_id or skill_obj.name.lower().replace(' ', '-')
+                output += f"- **{skill_obj.name}** (`{skill_id}`)\n"
+                if skill_obj.description:
+                    desc = skill_obj.description.split('\n')[0]  # 第一行
+                    output += f"  {desc[:100]}{'...' if len(desc) > 100 else ''}\n"
+            output += "\n"
+
+        output += "\n使用 `skill` 工具加载具体的 skill：`skill(skill_name=\"browser-use\")`"
+
+        return ToolResult(
+            title=f"可用 Skills ({len(skills)} 个)",
+            output=output,
+            long_term_memory=f"找到 {len(skills)} 个可用 skills，分为 {len(by_category)} 个类别",
+            include_output_only_once=True,
+            metadata={
+                "count": len(skills),
+                "categories": list(by_category.keys()),
+                "skills": [{"name": s.name, "category": s.category} for s in skills]
+            }
+        )
+
+    except Exception as e:
+        return ToolResult(
+            title="列出 Skills 错误",
+            output=f"列出 skills 时出错: {str(e)}",
+            error=str(e)
+        )