100/100 (Very Low)

OpenClaw： benign
VirusTotal： benign
StaticScan： clean

OpenClaw： benign

The skill's code, instructions, and resource requirements are consistent with its stated purpose (extracting features from an orders CSV and fetching historical data from Yahoo Finance) and do not req...

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VirusTotal： benign VT 报告

静态扫描： clean

No suspicious patterns detected.

README 未提供

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        "changelog": "Initial release of qc-deep-feature-forensics — a 12-dimensional technical feature attribution engine for quantitative trading.\n\n- Compares entry conditions of winning vs losing trades using 12 key market features (e.g., RSI, Bollinger, MACD, volume, gap).\n- Produces a report with winner\/loser feature comparison, what-if filter analysis, and the statistical profile of ideal winning entries.\n- Supports batch order reconstruction, historical data download with per-ticker caching, and full feature matrix export.\n- Includes robust caching, diagnostic outputs, and best-practice usage notes.\n- Requires Python 3, pip3, and Python packages: pandas, numpy, yfinance.",
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