财经分析工具包
This financial analysis toolkit provides AI agents with comprehensive capabilities for stock data analysis, market trend prediction, portfolio optimization, and investment advisory functions. Use it when conducting financial research, evaluating investment opportunities, monitoring market indices across sectors, assessing risk profiles, and generating data-driven investment recommendations based on technical indicators and fundamental analysis.
git clone --depth 1 https://github.com/wanxingai/LightAgent /tmp/- && cp -r /tmp/-/skills/gupiaozhushou ~/.claude/skills/-SKILL.md
# 财经分析工具包
专业的财经分析工具包，为AI Agent提供全面的财经分析能力。包含股票数据分析、市场趋势预测、投资组合优化等功能。
## 📊 功能模块
### 1. 股票数据分析
- 实时股票价格获取
- 历史数据查询与分析
- 技术指标计算（MA, RSI, MACD等）
- 基本面数据获取
### 2. 市场趋势分析
- 大盘指数监控
- 行业板块分析
- 市场情绪指标
- 宏观经济数据集成
### 3. 投资建议引擎
- 风险评估模型
- 投资组合优化
- 资产配置建议
- 止损止盈策略
### 4. 财经新闻聚合
- 实时财经新闻
- 热点事件分析
- 舆情监控
- 影响评估
## 🚀 快速开始
### 安装依赖
```bash
pip install yfinance pandas numpy matplotlib
```
### 基本使用示例
```python
from finance_toolkit import StockAnalyzer
# 创建分析器
analyzer = StockAnalyzer()
# 获取股票数据
data = analyzer.get_stock_data("AAPL", period="1mo")
# 技术分析
analysis = analyzer.technical_analysis(data)
print(analysis)
```
## 📁 文件结构
```
finance-toolkit/
├── SKILL.md # 技能说明文档
├── README.md # 用户文档
├── finance_toolkit.py # 核心Python模块
├── stock_analyzer.py # 股票分析模块
├── market_trends.py # 市场趋势模块
├── investment_advisor.py # 投资建议模块
├── news_aggregator.py # 新闻聚合模块
└── examples/ # 使用示例
```
## 🔧 工具函数
### 股票分析工具
- `get_stock_price(symbol)` - 获取实时股价
- `get_historical_data(symbol, period)` - 获取历史数据
- `calculate_technical_indicators(data)` - 计算技术指标
- `analyze_fundamentals(symbol)` - 分析基本面
### 市场分析工具
- `get_market_indices()` - 获取大盘指数
- `analyze_sector_performance()` - 分析行业表现
- `get_market_sentiment()` - 获取市场情绪
- `predict_market_trend()` - 预测市场趋势
### 投资建议工具
- `assess_risk_profile()` - 评估风险偏好
- `optimize_portfolio(assets)` - 优化投资组合
- `generate_investment_advice()` - 生成投资建议
- `set_stop_loss_targets()` - 设置止损止盈
## 📈 数据源
- Yahoo Finance (yfinance)
- 公开市场数据API
- 财经新闻API
- 宏观经济数据库
## ⚠️ 免责声明
本工具包提供的分析结果仅供参考，不构成投资建议。投资有风险，决策需谨慎。
## 🔗 相关资源
- [Yahoo Finance API](https://pypi.org/project/yfinance/)
- [Pandas数据分析](https://pandas.pydata.org/)
- [财经数据源列表](https://github.com/awesomedata/awesome-public-datasets#finance)
## 📝 更新日志
- v1.0.0 (2026-02-20): 初始版本发布，包含基础股票分析和市场趋势功能生成上市公司可比公司分析报告。当用户请求分析某家公司的竞争对手、可比公司、同业对比、竞品分析、对标公司分析时使用此技能。
全自动生成前沿技术领域的全景图谱。适用于以技术为核心的赛道（如量子计算、核聚变、AI Agent 等），通过双向挖掘（正向追踪学术源头 + 逆向溯源独角兽创始团队）构建学术→开源→商业化的完整脉络。触发词：「技术mapping」「技术全景图」「technology map」「赛道图谱」「前沿技术」「技术路线图」。
Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.
Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill.
Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like \"the xlsx in my downloads\") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.