Agent skill · research science · datadrivenconstruction
risk-assessment-ml
Apply machine learning for construction project risk assessment. Predict schedule delays, cost overruns, and safety incidents using historical data and project characteristics.
Why this skill is useful
Provides a comprehensive ML framework for predicting construction project risks that includes specific model training and feature preparation techniques not commonly known.
What it needs
Requires python3 installed locally. About 5k tokens when loaded. Last updated 2026-02-14. 265 stars on the source repository.
What this skill does
Risk Assessment with Machine Learning Overview This skill implements ML-based risk assessment for construction projects. Predict potential risks before they occur and prioritize mitigation strategies based on data-driven insights. Risk Categories: Schedule Risk: Delays, critical path impacts Cost Risk: Budget overruns, change orders Safety Risk: Incident probability, hazard identification Quality Risk: Defects, rework probability Quick Start Comprehensive Risk Model Risk Assessment Framework Feature Engineering Project Risk Features Risk Report Generation Quick Reference Risk Type Key Features Model Type ----------- -------------- ------------ Schedule Duration, complexity, weather Random Forest Cost Budget, scope changes, market Gradient Boosting Safety Work type, team experience Random Forest Quality Supervision, materials Logistic Regression Resources Scikit-learn: https://scikit-learn.org DDC Website: https://datadrivenconstruction.io Next Steps See cost-prediction for detailed cost modeling See 4d-simulation for schedule analysis See data-visualization for risk dashboards
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills datadrivenconstruction/risk-assessment-ml