skills/liangdabiao/claude-data-analysis-ultra-main/data-exploration-visualization/Gen Agent Trust Hub
data-exploration-visualization
Pass
Audited by Gen Agent Trust Hub on Sep 15, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: Verified code routines are cleanly constrained to standard mathematical, statistical, and plotting libraries including pandas, numpy, scikit-learn, xgboost, lightgbm, seaborn, and plotly.
- [DYNAMIC_EXECUTION]: The Python
__import__analyzer logs structural checks for dependency loading insidequick_test.pyandquick_start_example.py. The imports strictly process native or explicit technology stacks without external interpolation or dynamically injected remote inputs. - [DATA_EXFILTRATION]: No unrecognized external domains or remote storage endpoints are configured. File actions are localized solely to target logs, tabular configurations, generated plots, and local reporting models.
- [PROMPT_INJECTION]: The system parameters, descriptions, and metadata maintain operational boundaries and lack instructions engineered to jailbreak, bypass safety thresholds, or capture contextual properties.
Audit Metadata