Email Notifier

SKILL.md

---
name: email-notifier
description: Email sending and receiving module with multi-provider support (Gmail, Outlook, QQ, custom SMTP). Supports multiple configuration methods (interactive, config file, environment variables). Use for sending alerts, notifications, and checking emails via SMTP/IMAP/POP3.
version: 2.0.0
maturity: stable
author: OpenClaw Community
license: MIT
metadata:
    skill-author: OpenClaw Community
    created: 2026-01-10
    updated: 2026-03-08
dependencies: []
tags:
  - email
  - smtp
  - imap
  - notification
  - alert
role:
  name: 邮件通信专家
  personality: 专业、可靠、注重隐私
  expertise:
    - 多平台邮件发送 (Gmail/Outlook/QQ/自定义 SMTP)
    - 邮件接收和管理 (IMAP/POP3)
    - 邮件模板和格式化
    - 批量邮件和通知
  scenarios:
    - 系统告警通知
    - 日报/周报发送
    - 批量邮件通知
    - 邮件自动回复
---

# Email Notifier

Lightweight, reusable email module with no external dependencies beyond Python standard library.

## Quick Start

### Send an Email (SMTP)

```python
from scripts.sender import EmailSender

sender = EmailSender(provider="gmail")
sender.send(
    to="recipient@example.com",
    subject="Alert: System Status",
    body="CPU usage is above 90%",
    html_body="<h1>Alert</h1><p>CPU usage is <strong>above 90%</strong></p>"
)
```

### Check for New Emails (IMAP)

```python
from scripts.receiver import EmailReceiver

receiver = EmailReceiver(provider="outlook", mailbox="INBOX")
emails = receiver.fetch_unread(limit=5)
for email in emails:
    print(f"From: {email['from']}, Subject: {email['subject']}")
```

## Configuration

Three methods available, in order of precedence: **environment variables > config file > interactive**.

### Method 1: Environment Variables

Create `.env` file in the skill directory:

```bash
# Provider: gmail, outlook, qq, custom
EMAIL_PROVIDER=gmail

# SMTP Settings
SMTP_SERVER=smtp.gmail.com
SMTP_PORT=587
SMTP_USERNAME=your-email@gmail.com
SMTP_PASSWORD=your-app-password

# IMAP Settings (optional, for receiving)
IMAP_SERVER=imap.gmail.com
IMAP_PORT=993
IMAP_USERNAME=your-email@gmail.com
IMAP_PASSWORD=your-app-password

# Default sender (optional)
DEFAULT_FROM=no-reply@gmail.com
```

### Method 2: Config File

Create `config.json` in the skill directory:

```json
{
  "provider": "gmail",
  "smtp": {
    "server": "smtp.gmail.com",
    "port": 587,
    "username": "your-email@gmail.com",
    "password": "your-app-password"
  },
  "imap": {
    "server": "imap.gmail.com",
    "port": 993,
    "username": "your-email@gmail.com",
    "password": "your-app-password"
  }
}
```

### Method 3: Interactive Configuration

Run the configuration wizard:

```bash
python scripts/configurer.py
```

## Provider Settings

| Provider | SMTP Server | SMTP Port | IMAP Server | IMAP Port | Notes |
|----------|-------------|-----------|-------------|-----------|-------|
| Gmail | smtp.gmail.com | 587 | imap.gmail.com | 993 | Use App Password |
| Outlook | smtp.office365.com | 587 | outlook.office365.com | 993 | Use App Password |
| QQ | smtp.qq.com | 465/587 | imap.qq.com | 993 | Use App Password |
| Custom | your-server | your-port | your-server | your-port | Configure manually |

For Gmail/Outlook/QQ, enable 2FA and generate an **App Password** instead of using your login password.

## Scripts Reference

| Script | Purpose |
|--------|---------|
| `scripts/sender.py` | SMTP email sending module |
| `scripts/receiver.py` | IMAP/POP3 email receiving module |
| `scripts/configurer.py` | Interactive configuration wizard |
| `scripts/validator.py` | Test and validate email configuration |

### Run Configuration Wizard

```bash
python scripts/configurer.py
```

This creates a `config.json` file interactively.

### Validate Configuration

```bash
python scripts/validator.py
```

Tests SMTP connection and IMAP connection (if configured).

## Usage Examples

### Alert Notification

```python
from scripts.sender import EmailSender
from scripts.config import load_config

config = load_config()
sender = EmailSender(config=config)

sender.send(
    to="admin@example.com",
    subject="⚠️ Server Alert",
    body=f"Server {hostname} is under high load\nCPU: {cpu}%\nMemory: {mem}%",
    priority="high"
)
```

### Daily Digest

```python
from scripts.receiver import EmailReceiver

receiver = EmailReceiver(provider="outlook")
unread = receiver.fetch_unread(folder="INBOX", limit=20)

if unread:
    summary = f"You have {len(unread)} unread emails"
    # Send summary to yourself or dashboard
```

### Batch Send Notifications

```python
from scripts.sender import EmailSender

sender = EmailSender(provider="gmail")

recipients = ["user1@example.com", "user2@example.com"]
for recipient in recipients:
    sender.send(
        to=recipient,
        subject="Meeting Reminder",
        body="Reminder: Team meeting at 3 PM"
    )
```

## 使用场景示例

### 场景 1: 系统告警通知

**用户请求:**
```
服务器 CPU 使用率超过 90%，发邮件告警
```

**处理流程:**
1. 调用 `email-notifier` 技能
2. 配置 SMTP 服务器
3. 发送邮件给管理员
4. 确认发送成功

**预期输出:**
```
✅ 已完成：告警邮件发送
📧 收件人：admin@example.com
📝 主题：⚠️ 服务器告警 - CPU 使用率 90%
⏱️ 发送时间：2 秒
```

**成功指标:**
- ✅ 邮件发送成功率 100%
- ✅ 发送时间 <5 秒
- ✅ 邮件格式正确

---

### 场景 2: GitHub 报告发送

**用户请求:**
```
把今天的 GitHub 趋势报告发邮件给我
```

**处理流程:**
1. 调用 `github-analysis-report` 生成报告
2. 调用 `email-notifier` 发送报告
3. 添加 HTML 格式美化
4. 确认发送成功

**预期输出:**
```
✅ 已完成：GitHub 报告邮件发送
📧 收件人：2197057577@qq.com
📝 主题：📊 GitHub Trending 每日报告 - 2026-03-08
📎 附件：github-trending-2026-03-08.md
⏱️ 发送时间：3 秒
```

**成功指标:**
- ✅ 报告格式完整
- ✅ HTML 渲染正确
- ✅ 附件正确添加

---

### 场景 3: 批量会议通知

**用户请求:**
```
给团队成员发会议提醒，下午 3 点开会
```

**处理流程:**
1. 获取团队成员邮箱列表
2. 创建会议通知模板
3. 批量发送邮件
4. 统计发送结果

**预期输出:**
```
✅ 已完成：批量会议通知发送
📧 发送数量：10 封
✅ 成功：10 封
❌ 失败：0 封
⏱️ 总耗时：15 秒
```

**成功指标:**
- ✅ 发送成功率 >98%
- ✅ 邮件内容一致
- ✅ 无重复发送

---

## 成功指标

| 指标 | 目标值 | 测量方式 |
|------|--------|----------|
| 邮件发送成功率 | >98% | 成功发送数/总发送数 |
| 平均发送时间 | <5 秒 | 从命令到发送完成时间 |
| 邮件格式正确率 | 100% | HTML/纯文本格式验证 |
| 用户满意度 | >4.5/5 | 用户评分 |
| 配置成功率 | >95% | 首次配置成功数/总配置数 |

## 相关文件

- **主程序:** `skills/email-notifier/sender.py`, `skills/email-notifier/receiver.py`
- **配置工具:** `skills/email-notifier/configurer.py`
- **依赖声明:** `skills/email-notifier/SKILL.md`

### 角色定义
GitHub 开发助手，擅长代码审查、PR 管理、Issue 跟踪和仓库自动化。

### 成功指标
- PR/Issue 处理准确率 >95%
- 代码审查建议采纳率 >80%
- 自动化任务成功率 >90%

### 使用场景
- 当用户需要审查 GitHub PR 代码时，自动分析代码变更并提供改进建议。
- 当用户需要跟踪 Issue 进度时，自动查询状态并生成进度报告。
- 当用户需要批量处理仓库操作时，自动执行并生成操作日志。