Security checks across malware telemetry and agentic risk
This is a disclosed stock analysis and report-generation skill with normal dependency and financial-advice risks, but no evidence of hidden, destructive, or exfiltrating behavior.
Install in a normal project sandbox or virtual environment. Expect it to contact market-data services, install Python packages, write stock_data_output reports, and open local report files. Treat investment conclusions as research only, do not provide unrelated secrets, and avoid sharing generated HTML if local path disclosure matters.
# 安装：pip install -r requirements.txt # 核心数据源 akshare>=1.18.0 yfinance>=1.0.0 tushare>=1.4.0
# 核心数据源 akshare>=1.18.0 yfinance>=1.0.0 tushare>=1.4.0 # 数据处理
# 核心数据源 akshare>=1.18.0 yfinance>=1.0.0 tushare>=1.4.0 # 数据处理 pandas>=2.0.0
tushare>=1.4.0 # 数据处理 pandas>=2.0.0 numpy>=1.24.0 # 图表生成
# 数据处理 pandas>=2.0.0 numpy>=1.24.0 # 图表生成 matplotlib>=3.7.0
numpy>=1.24.0 # 图表生成 matplotlib>=3.7.0 # PDF 处理（纯 Python，无需 poppler） pymupdf>=1.23.0
matplotlib>=3.7.0 # PDF 处理（纯 Python，无需 poppler） pymupdf>=1.23.0 # 报告导出 fpdf2>=2.7.0
pymupdf>=1.23.0 # 报告导出 fpdf2>=2.7.0 python-docx>=1.0.0 Pillow>=10.0.0
# 报告导出 fpdf2>=2.7.0 python-docx>=1.0.0 Pillow>=10.0.0 # MD→HTML 转换
# 报告导出 fpdf2>=2.7.0 python-docx>=1.0.0 Pillow>=10.0.0 # MD→HTML 转换 markdown>=3.6.0
Pillow>=10.0.0 # MD→HTML 转换 markdown>=3.6.0 # 通用 requests>=2.31.0
markdown>=3.6.0 # 通用 requests>=2.31.0
66/66 vendors flagged this skill as clean.
