Quant System 5steps

5-Step Quant Trading System with multi-source data, enhanced ML models, and 15+ strategy templates

This skill appears to implement the trading system it describes, but proceed with caution: - Dependency mismatch: the Python file imports lightgbm, numpy, and requests, but the skill provides no install steps. Run it only in a controlled environment (virtualenv/container) where you install and verify these packages yourself. - External endpoints: it performs outbound HTTP calls to api.hyperliquid.xyz and api.binance.com. Ensure you trust those endpoints and be aware running the skill will make network requests from your environment. - Provenance: registry metadata shows no homepage, while SKILL.md includes one; the source is unknown. If you need to trust this for production use, request provenance (author, license, full source review). - Safety steps: review the entire Python file (including truncated sections) before executing, run it in an isolated sandbox, and avoid providing any secret/API keys unless you confirm they are required and the code handles them safely. If you want, I can scan the remainder of quant_pipeline.py (the truncated part) for other behaviors before you run it.

Type: OpenClaw Skill Name: quant-system-5steps Version: 1.1.0 The skill implements a standard quantitative trading pipeline including data collection from legitimate crypto APIs (Binance and Hyperliquid), technical indicator calculation, and machine learning model training using LightGBM. The code in quant_pipeline.py is well-structured, lacks any obfuscation, and does not perform any sensitive operations such as accessing environment variables, local credentials, or executing arbitrary shell commands.