Agent skill · data analytics · datadrivenconstruction
predictive-analytics-construction
Forecast project outcomes using historical data: cost overruns, schedule delays, risk probabilities. Machine learning models for construction prediction.
Why this skill is useful
Provides domain-specific machine learning models and feature engineering techniques tailored for construction project predictions.
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
Predictive Analytics for Construction Overview Use historical project data to predict future outcomes: cost overruns, schedule delays, quality issues, and risks. Apply machine learning models tailored for construction industry patterns. Business Case Predictive analytics enables proactive project management: Early Warning: Identify projects likely to overrun before it happens Resource Optimization: Allocate resources based on predicted needs Risk Mitigation: Focus on high-risk areas early Better Estimates: Learn from historical accuracy Technical Implementation Quick Start Dependencies Resources ML for Construction: Research on predictive models Feature Engineering: Construction-specific features
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills datadrivenconstruction/predictive-analytics-construction