According to AlphaMoat, as of 2026-09, Agent Team has 4,184 downloads and 0 stars — ranked #2,398 of 5,078 AI skills overall, and #470 of 969 in AI Agent.
| Platform | Installs | Downloads | Stars | Comments |
|---|---|---|---|---|
| ClawHub ↗ | 120 | 3.6K | - | - |
| SkillHub ↗ | 117 | 4.2K | - | — |
Platforms count differently and update at different times.
The primary describes viewing members, starting an agent on a task, and chatting. Tasks and messages may be sent to configured model providers; check the provider and data routing before sharing sensitive content.
Profile published 2026-10-29
Generated from the skill’s documentation as examples; not results of actual runs.
The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change.
| Month | Downloads | MoM | Stars |
|---|---|---|---|
| 2026-09 | 4.2K | — | - |
| 2026-08 | 3.7K | +5.3% | - |
| 2026-07 | 3.5K | — | - |
| 2026-05 | 3.0K | — | - |
| 2026-03 | 1.7K | — | - |
The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.
# agent-team - 多 Agent 团队管理系统 管理和调用具有不同"灵魂"的子 Agent 团队,每个 Agent 拥有独特的身份定义和专用模型。 ## 使用方法 ### 基础命令 ```bash agent-team list # 列出所有 Agent agent-team show <name> # 查看 Agent 详情
agent-team spawn <name> [task] # 启动 Agent 执行任务
agent-team chat <name> # 与 Agent 交互对话
```
### 示例
```bash
# 查看团队所有成员
agent-team list
# 查看 Coder 的详细信息
agent-team show coder
# 让 Coder 帮你写代码
agent-team spawn coder "写一个快速排序算法"
# 与 Writer 对话讨论写作
agent-team chat writer
```
## 内置 Agent 团队
| Agent | 角色 | 主模型 | 专长 |
|:---:|:---|:---|:---|
| 🧑💻 **coder** | 代码专家 | qwen3-coder-next | 编程、重构、测试 |
| ✍️ **writer** | 写作专家 | qwen3.5-plus | 文档、博客、创意写作 |
| 📊 **analyst** | 数据专家 | qwen3.5-plus | 数据分析、可视化 |
| 🔍 **researcher** | 调研专家 | gemini-3.1-pro | 文献调研、竞品分析 |
| 👀 **reviewer** | 审查专家 | qwen3-max | 代码审查、质量把关 |
## 创建新 Agent
### 1. 创建目录
```bash
mkdir -p ~/.openclaw/workspace/agents/<agent-name>
```
### 2. 定义 SOUL.md
```markdown
# SOUL.md - <Agent Name>
## 身份
你是...
## 性格特质
- ...
## 专业领域
- ...
## 沟通风格
- ...
```
### 3. 创建 config.json
```json
{
"name": "AgentName",
"role": "角色描述",
"emoji": "🤖",
"model": {
"primary": "dashscope/qwen3.5-plus",
"fallback": "google/gemini-3-flash-preview"
},
"capabilities": ["能力 1", "能力 2"]
}
```
## 模型配置说明
每个 Agent 可以配置不同的模型:
- **dashscope/qwen3-coder-next**: 编码专用
- **dashscope/qwen3.5-plus**: 通用中文优化
- **dashscope/qwen3-max**: 最强推理
- **google/gemini-3.1-pro**: 深度研究
- **google/gemini-3-flash-preview**: 快速响应
## 工作模式
### 1. 任务模式 (spawn)
```bash
agent-team spawn coder "优化这个函数"
```
- 创建独立子代理会话
- 执行指定任务
- 完成后返回结果
### 2. 对话模式 (chat)
```bash
agent-team chat analyst
```
- 进入交互式对话
- 保持角色一致性
- 适合复杂协作
## 高级用法
### 并行多 Agent
```bash
# 同时启动多个 Agent
agent-team spawn coder "写代码" &
agent-team spawn writer "写文档" &
agent-team spawn reviewer "审查代码" &
wait
```
### 链式调用
```bash
# Coder 写代码 → Reviewer 审查 → Writer 写文档
agent-team spawn coder "实现功能"
agent-team spawn reviewer "审查代码"
agent-team spawn writer "编写文档"
```
## 文件结构
```
~/.openclaw/workspace/
├── agents/
│ ├── coder/
│ │ ├── SOUL.md # 身份定义
│ │ └── config.json # 模型配置
│ ├── writer/
│ └── ...
└── skills/
└── agent-team/
├── agent-team.py # 管理脚本
└── SKILL.md # 本文档
```
## 故障排除
1. **Agent 未找到**: 检查 `~/.openclaw/workspace/agents/` 目录
2. **模型不可用**: 确认模型配置正确且 API Key 有效
3. **会话无法创建**: 检查 OpenClaw 网关状态
## 相关技能
- `sessions_spawn`: OpenClaw 原生子代理创建
- `self-improving`: 自我进化记忆系统
Records learnings, errors and corrections as Markdown files for later reuse and promotion into workspace memory.
Finds skills in local and remote catalogs from a plain-language request and recommends what to install.
A browser-automation command line skill for AI agents.
Turns corrections and self-review into tiered memory and promotes or archives it by use.
Reviews a third-party skill's source, permissions, and danger patterns against a checklist before it is installed.
Stores agent memory and cross-skill state as a typed, constraint-checked knowledge graph.
A workspace setup guide for planning proactive follow-up, working memory and review routines for an AI agent.
A guide to creating and updating effective Claude skills.
Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.