Quant Tools 1.0.0

This skill is a documentation/architecture guide pointing you to many legitimate open-source quant projects — it appears coherent and not malicious. Before using the guidance in production, consider: (1) provenance: the skill has no homepage and an unknown source — ask the author for provenance or a trusted repository/packaged release; (2) dependency risk: following the guide will lead to installing many third-party packages — pin versions, audit dependencies, and prefer official GitHub releases or package registries; (3) credential handling: live-trading frameworks (VeighNa, broker integrations), cloud GPUs, and data APIs require secrets — store them securely (vault, env with least privilege), and never paste them into chat; (4) network exposure: JupyterHub, FastAPI services, or trading gateways must be behind TLS, auth, and network isolation; (5) sandbox first: test heavy-resource tools (VectorBT, FinBERT) in isolated, resource-limited environments (Docker, k8s namespaces) to avoid accidental data leaks or runaway compute costs; (6) licensing & compliance: check each project's license and ensure your use (especially anything public-facing or paid advice) complies with regulations. If you want a deeper safety check, provide any planned deployment scripts, Dockerfiles, or a list of exact package versions you intend to install so those can be reviewed for risky install sources or suspicious post-install actions.