a65adcc2e5
Sources: extracted from two upstream archives (skill-repo, skills-main),
merged with the following policy:
- 15 broken symlinks (pointing to /Users/jameslee/.cc-switch/skills or
../../.agents/skills on a foreign machine) discarded
- 3 real name collisions with identical content (ai-pair, ifind-http-api,
zhipu-websearch) kept as one copy
- Functional overlaps deduped keeping the strongest variant:
- docx family: kept docx (official, full toolchain) + docx-cn
(GB/T 9704 Chinese official-document constants),
dropped docx_writer (no scripts, name collided with docx)
- humanizer family: kept humanizer-zh (6 zh reference docs),
dropped humanizer (en, redundant for CN workflow)
- Skills that only ran in a foreign environment removed:
ablemind-ops, app-publish, hlb-design-system, openclaw-adj-skill,
claude-driver
- alphapai excluded from this public repo because its SKILL.md hard-coded
live credentials
Result: 25 skills, 572 files, ~7.5 MB.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
193 lines
4.5 KiB
Markdown
193 lines
4.5 KiB
Markdown
---
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name: asset-monitor
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description: 资产异常波动日频监控与报告生成。当用户需要对股票、指数、商品等资产进行日频异常波动监控，检测偏离历史均值超过2倍标准差的异常，并生成Excel报告时使用此技能。
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---
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# 资产异常波动日频监控
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## 触发条件
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当用户需要：
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- 监控多资产类别的日频异常波动
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- 检测偏离历史均值超过2倍标准差的资产
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- 生成异常波动报告（Excel/Markdown）
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- 批量分析申万三级行业、A股指数、商品期货、全球指数等
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## 依赖
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本 skill 依赖 windpy-sdk 获取数据。使用时需要：
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1. Wind 金融终端已启动
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2. 参考 windpy-sdk skill 了解数据获取方法
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## 监控脚本
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使用 `scripts/monitor.py` 进行监控：
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```bash
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# 基础监控
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python scripts/monitor.py
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# 带报告输出
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python scripts/monitor.py --notify
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# 自定义参数
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python scripts/monitor.py --threshold 2.5 --min-days 60
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```
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## 监控资产范围
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| 资产类别 | 数量 | 说明 |
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|---------|------|------|
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| 申万三级行业 | 259个 | 全量三级行业指数 |
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| A股主要指数 | 9个 | 沪深300、中证500等 |
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| 中债指数 | 5个 | 中债总指数、国债指数等 |
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| 主流ETF | 8个 | 沪深300ETF、创业板ETF等 |
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| 商品期货 | 8个 | 黄金、白银、铜、原油等 |
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| 全球指数 | 9个 | 标普500、纳指、道指等 |
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**总计**: 298个资产
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## 核心监控逻辑
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### Z-Score 异常检测
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```python
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# 计算Z值
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z_score = (今日涨跌幅 - 历史均值) / 历史标准差
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# 异常判定
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if abs(z_score) > 2.0:
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标记为异常
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```
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### 筛选条件
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- 历史数据 > 30个交易日
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- 历史标准差 > 0
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- 按 |Z| 绝对值降序排列
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## 输出结果
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### Excel 报告
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| 字段 | 说明 |
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|------|------|
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| category | 资产类别 |
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| code | 资产代码 |
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| name | 资产名称 |
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| today_return | 今日涨跌幅(%) |
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| z_score | Z值 |
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| direction | 大涨/大跌 |
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### 监控输出示例
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```
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================================================================================
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📊 资产异常波动监控
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时间: 2026-02-09 06:22
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Z值阈值: 2.0
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================================================================================
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[监控] 申万三级行业 (259个)
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共 259 个资产
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⚠️ 印染(申万): +5.30% (Z=+3.33)
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⚠️ 纺织化学制品(申万): +5.35% (Z=+3.22)
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发现 5 个异常
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[监控] 商品期货 (8个)
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⚠️ 沪银近月: -14.02% (Z=-4.39)
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发现 1 个异常
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[监控] 全球指数 (9个)
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⚠️ 道琼斯: +2.47% (Z=+2.34)
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⚠️ VIX波动率: -18.42% (Z=-2.26)
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发现 2 个异常
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================================================================================
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✅ 监控完成，共发现 8 个异常
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================================================================================
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```
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## 脚本使用方法
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详见 `scripts/monitor.py` 代码注释。
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### 命令行参数
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```bash
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python scripts/monitor.py --help
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Options:
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--threshold FLOAT Z-Score阈值，默认2.0
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--min-days INT 最小交易日，默认30
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--output DIR 输出目录，默认output
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--notify 打印文本报告
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```
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### Python API
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```python
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# 直接导入脚本中的函数使用
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import sys
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sys.path.insert(0, 'scripts')
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from monitor import run_monitoring, generate_excel_report
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# 运行监控（需先连接Wind）
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from WindPy import w
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w.start()
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anomalies = run_monitoring(threshold_z=2.0)
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w.stop()
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# 生成报告
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excel_path = generate_excel_report(anomalies)
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```
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## 定时任务设置
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```bash
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# crontab -e
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# 每日15:30运行
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30 15 * * * cd /path/to/skill && python scripts/monitor.py --notify
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```
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## 配置文件
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配置示例见 `references/monitor-config-example.json`
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```json
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{
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"monitor": {
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"threshold_z": 2.0,
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"min_trading_days": 30
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},
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"assets": {
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"sw3_industry": {"enabled": true},
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"ashare_index": {"enabled": true},
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"commodity": {"enabled": true}
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}
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}
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```
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## 故障排查
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| 问题 | 原因 | 解决方案 |
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|------|------|---------|
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| Wind连接失败 | Wind终端未启动 | 启动Wind终端 |
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| 无数据返回 | 无数据权限 | 联系Wind开通权限 |
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| 报告为空 | 今日无异常 | 正常现象 |
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## 与其他 Skill 的关系
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```
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asset-monitor (监控逻辑 + 报告生成)
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↓ 使用 WindPy 获取数据
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WindPy SDK (Wind 金融终端 API)
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```
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**注意**: asset-monitor 直接使用 WindPy，但字段和板块代码可参考 windpy-sdk skill 的文档。
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## 参考
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- windpy-sdk skill - WindPy 函数参考和字段速查
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- `references/monitor-config-example.json` - 配置示例
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