skills/g1joshi/agent-skills/xgboost/Gen Agent Trust Hub

xgboost

Pass

Audited by Gen Agent Trust Hub on Oct 11, 2026

Risk Level: SAFE
Full Analysis
  • [SAFE]: The skill documentation and provided code snippets utilize well-known, established data science libraries including xgboost, scikit-learn, pandas, and numpy. All code examples demonstrate standard usage patterns for training and evaluating machine learning models without suspicious external dependencies or execution methods.
  • [SAFE]: The instructions explicitly recommend using the native JSON format for saving and loading models (model.save_model("model.json")) rather than Python's binary pickle format. This is a recognized security best practice that reduces the risk of arbitrary code execution during model deserialization.
  • [SAFE]: The code snippets for GPU acceleration (device="cuda") and early stopping are standard performance features of the library and do not involve unauthorized privilege escalation or network exfiltration patterns.
Audit Metadata
Risk Level
SAFE
Analyzed
Oct 11, 2026, 03:37 AM