Detect anomalies and outliers in construction data: unusual costs, schedule variances, productivity spikes. Statistical and ML-based detection methods.
- Added detailed documentation and usage examples to SKILL.md for construction anomaly detection. - Clarified support for statistical (IQR, z-score) and business rule-based anomaly detection for costs and schedules. - Described construction-specific thresholds and anomaly types handled (cost, schedule, productivity). - Provided technical overview and sample Python implementation in SKILL.md.