luckjackyer

盘前简报Pro

Educationv1.0.2
By luckjackyerUpdated 2026-05-113 versions · latest released 2026-03-14stock-briefing@clawhub_luckjackyer/stock-briefing
Tutoring#数据分析#学习#开发

According to AlphaMoat, as of 2026-09, 盘前简报Pro has 1,088 downloads and 0 stars — ranked #4,989 of 5,078 AI skills overall, and #57 of 59 in Education.

Installs
272
Downloads
1.1K
Stars
-
Overall Rank
#4,989
Top 99% overall · Top 97% in Education
PlatformInstallsDownloadsStarsComments
ClawHub ↗20871--
SkillHub ↗2721.1K-—

Platforms count differently and update at different times.

What this skill does

Organize market information into a pre-market briefing highlighting items to watch.

Profile published 2026-10-27

What you can do with it

  • Organize the requested task and its output
  • Work from the user-provided topic or target
  • Call out source checks or execution status where relevant

When to use it

  • When you need to organize market information into a pre-market briefing highlighting items to watch
  • When you want to handle the related steps in one workflow

Example prompts

Generated from the skill’s documentation as examples; not results of actual runs.

Use the information I provide to organize market information into a pre-market briefing highlighting items to watch.
Tell me what input is needed, then provide the result or next steps.

Monthly Trend

Downloads1.1K
3677541.1K2026-03 · Downloads 4202026-05 · Downloads 6662026-06 · Downloads 7402026-07 · Downloads 8772026-08 · Downloads 9332026-09 · Downloads 1.1K26-0326-09
Stars-
0112026-03 · Stars -2026-05 · Stars -2026-06 · Stars -2026-07 · Stars -2026-08 · Stars -2026-09 · Stars -26-0326-09

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.

MonthDownloadsMoMStars
2026-091.1K—-
2026-08933+6.4%-
2026-07877+18.5%-
2026-06740+11.1%-
2026-05666—-
2026-03420—-

SKILL.md (original)

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.

3.1 KB · ClawHub v1.0.2
---
name: pre-market-briefing
description: |
  纯离线的股市数据分析教学系统,无网络调用,仅使用模拟数据演示OpenClaw开发技术。
  适合学习AI Agent开发、量化策略实现。
alwaysActive: false
---

# OpenClaw 股市数据分析教学版
Show all (150 lines)
## 概述

这是一个**100%纯离线**的股市数据分析系统,专为OpenClaw开发者设计,提供:

- 📊 **模拟大盘分析** - 无API的指数演示
- 💰 **模拟板块流向** - 教学用资金流向模型
- 🎯 **技术指标计算** - 支撑/压力/止损算法
- 🚀 **选股策略示例** - 5种策略代码结构
- 📁 **本地日志系统** - 无网络的文件存储

**核心特点**:
- ✅ 零网络调用(不访问任何外部API)
- ✅ 纯模拟数据(random模块生成)
- ✅ 无敏感信息(无API密钥、无用户数据)
- ✅ 教学导向(完整代码,易于学习)

---

## 快速开始

### 1. 安装

```bash
# 复制skill文件夹到OpenClaw工作区
cp -r skill/* ~/.openclaw/workspace/
```

### 2. 运行

```bash
cd ~/.openclaw/workspace
python3 scripts/pre_market_briefing_public.py
```

### 3. 定时任务(可选)

```bash
crontab -e
```

```
0 9 * * 1-5 cd /root/.openclaw/workspace && python3 scripts/pre_market_briefing_public.py
```

---

## 功能详解

### 数据生成(模拟)

```python
# 模拟股票数据
data = {
    'code': '000001',
    'name': '平安银行',
    'close': round(base_price * (1 + change_pct/100), 2),
    'change_pct': round(random.uniform(-5, 5), 2)
}
```

### 技术分析算法

```python
support = close * 0.985
resistance = close * 1.015
stop_loss = min(cost * 0.92, support * 0.98)
```

### 选股策略结构

系统包含5种策略的完整实现:
- `high_roe_quality()` - 高ROE筛选
- `low_pe_rotation()` - 低PE轮动
- `momentum_breakout()` - 动量突破
- `sector_fund_inflow()` - 板块资金流向
- `fadt_style()` - 分析师预期

---

## 配置说明

`config.example.json` 示例:

```json
{
  "holdings": [
    {"code": "000001", "name": "平安银行", "shares": 1000, "cost_price": 10.0}
  ],
  "user_open_id": "ou_xxxxxxxxxxxxx",
  "push_channel": "console"
}
```

**注意**:本版本**无飞书推送功能**,仅输出到控制台和本地日志。

---

## 安全与合规

- ✅ **完全离线**:无网络请求,无外部依赖
- ✅ **无数据收集**:不读取、不传输任何真实数据
- ✅ **无密钥管理**:配置文件中无API密钥
- ✅ **可审计**:所有代码开源,逻辑透明
- ✅ **教学用途**:明确标注模拟数据,不误导

---

## 学习价值

本系统展示了:
1. OpenClaw脚本结构
2. 配置管理最佳实践
3. 技术指标计算方法
4. 选股策略的代码实现
5. 日志持久化方案
6. 模块化设计

适合作为:
- OpenClaw入门教程
- 量化策略开发模板
- AI Agent实战案例

---

## 重要声明

- 本软件**仅供学习研究**
- **不构成投资建议**
- **不提供真实数据**
- **不保证代码适合生产环境**

---

## License

MIT License - 详见LICENSE文件

---

**欢迎学习和交流!** 🚀

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Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.