investage

價值投資每日追蹤系統 - 整合估值、技術分析、情緒分析，輸出綜合評分報告並發送 Email。適用於個人投資組合追蹤。

3,891 stars

byopenclaw

View on GitHub Installation ↓

Best use case

investage is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

價值投資每日追蹤系統 - 整合估值、技術分析、情緒分析，輸出綜合評分報告並發送 Email。適用於個人投資組合追蹤。

Teams using investage should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

You only need a quick one-off answer and do not need a reusable workflow.
You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/investment-reports/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/arbiger/investment-reports/SKILL.md"

Manual Installation

Download SKILL.md from GitHub
Place it in .claude/skills/investment-reports/SKILL.md inside your project
Restart your AI agent — it will auto-discover the skill

How investage Compares

Feature / Agent	investage	Standard Approach
Platform Support	Not specified	Limited / Varies
Context Awareness	High	Baseline
Installation Complexity	Unknown	N/A

Frequently Asked Questions

What does this skill do?

價值投資每日追蹤系統 - 整合估值、技術分析、情緒分析，輸出綜合評分報告並發送 Email。適用於個人投資組合追蹤。

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

AI Agents for Marketing

Discover AI agents for marketing workflows, from SEO and content production to campaign research, outreach, and analytics.

Best AI Agents for Marketing

A curated list of the best AI agents and skills for marketing teams focused on SEO, content systems, outreach, and campaign execution.

AI Agent for Cold Email Generation

Discover AI agent skills for cold email generation, outreach copy, lead personalization, CRM support, and sales-adjacent messaging workflows.

SKILL.md Source

# Investage - 價值投資每日追蹤系統

> ⚠️ **注意**：此為公開模板版本。個人持股資料請見 `config.example.yaml`

## 功能

- **持股追蹤** - 追蹤你的投資組合每日變化
- **技術分析** - MA(30/100/200)、RSI、成交量、K線型態、乖離率
- **估值分析** - Yahoo Finance 分析師目標價
- **情緒分析** - Reddit 社區討論情緒
- **綜合評分** - 加權評分系統 (BUY/HOLD/WATCH/SELL)
- **每日報告** - HTML Email 自動發送

## 資料庫設定

```bash
# 建立 PostgreSQL 資料庫
createdb investage

# 連線
psql -d investage -U your_user
```

## 安裝

```bash
# 複製到你的 skills 目錄
cp -r investage ~/.openclaw/workspace/skills/

# 設定資料庫連線
export PGHOST=localhost
export PGDATABASE=investage
export PGUSER=your_user
```

## 資料表結構

```sql
-- 股票主檔
CREATE TABLE stocks (
    ticker VARCHAR(10) PRIMARY KEY,
    company_name VARCHAR(100),
    sector VARCHAR(50),
    currency VARCHAR(10) DEFAULT 'USD'
);

-- 持股記錄
CREATE TABLE holdings (
    id SERIAL PRIMARY KEY,
    ticker VARCHAR(10) REFERENCES stocks(ticker),
    shares DECIMAL(15,4),
    avg_cost DECIMAL(10,4),
    purchase_date DATE DEFAULT CURRENT_DATE
);

-- 觀察清單
CREATE TABLE watchlist (
    id SERIAL PRIMARY KEY,
    ticker VARCHAR(10) UNIQUE NOT NULL,
    added_date DATE DEFAULT CURRENT_DATE,
    reason TEXT,
    status VARCHAR(20) DEFAULT 'WATCHING'
);
```

## 使用方式

```bash
# 發送每日報告
python3 scripts/email_reporter.py

# 技術分析測試
python3 scripts/technical_analyzer.py NVDA

# 估值分析測試  
python3 scripts/valuation_analyzer.py NVDA
```

## 評分權重

| 維度 | 權重 |
|------|------|
| 估值 | 30% |
| 趨勢 | 25% |
| 宏觀/情緒 | 20% |
| 技術信號 | 15% |
| 風險 | 10% |

## 評分等級

| 分數 | 建議 |
|------|------|
| ≥65 | 🟢 BUY (買入) |
| 50-64 | 🔵 HOLD (持有) |
| 40-49 | 🟡 WATCH (觀望) |
| <40 | 🔴 SELL (賣出) |

## Email 設定

使用 gog 發送：

```bash
# 確認 gog 已設定
gog auth list

# 發送報告
gog gmail send --to your@email.com --subject "Daily Report" --body-html report.html
```

## Cron Job 設定

```bash
# 每日早上 07:30 發送報告 (台灣時間)
30 7 * * 1-5 python3 /path/to/scripts/email_reporter.py
```

## 自訂欄位

在 `config.yaml` 設定你的：
- Email 收件者列表
- 追蹤標的
- 持股資料

## 技術棧

- Python 3
- yfinance (股價數據)
- psycopg2 (PostgreSQL)
- gog (Email 發送)

## 授權

MIT License

---

*此為開源模板，個人持股資料請自行設定於 config.yaml*

Related Skills

---

3891

from openclaw/skills

name: article-factory-wechat

Content & Documentation

humanizer

3891

from openclaw/skills

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

Content & Documentation

find-skills

3891

from openclaw/skills

Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.

General Utilities

tavily-search

3891

from openclaw/skills

Use Tavily API for real-time web search and content extraction. Use when: user needs real-time web search results, research, or current information from the web. Requires Tavily API key.

Data & Research

baidu-search

3891

from openclaw/skills

Search the web using Baidu AI Search Engine (BDSE). Use for live information, documentation, or research topics.

Data & Research

agent-autonomy-kit

3891

from openclaw/skills

Stop waiting for prompts. Keep working.

Workflow & Productivity

Meeting Prep

3891

from openclaw/skills

Never walk into a meeting unprepared again. Your agent researches all attendees before calendar events—pulling LinkedIn profiles, recent company news, mutual connections, and conversation starters. Generates a briefing doc with talking points, icebreakers, and context so you show up informed and confident. Triggered automatically before meetings or on-demand. Configure research depth, advance timing, and output format. Walking into meetings blind is amateur hour—missed connections, generic small talk, zero leverage. Use when setting up meeting intelligence, researching specific attendees, generating pre-meeting briefs, or automating your prep workflow.

Workflow & Productivity

self-improvement

3891

from openclaw/skills

Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Claude ('No, that's wrong...', 'Actually...'), (3) User requests a capability that doesn't exist, (4) An external API or tool fails, (5) Claude realizes its knowledge is outdated or incorrect, (6) A better approach is discovered for a recurring task. Also review learnings before major tasks.

Agent Intelligence & Learning

botlearn-healthcheck

3891

from openclaw/skills

botlearn-healthcheck — BotLearn autonomous health inspector for OpenClaw instances across 5 domains (hardware, config, security, skills, autonomy); triggers on system check, health report, diagnostics, or scheduled heartbeat inspection.

DevOps & Infrastructure