risk-assessment-ml-datadrivenconstructi-ddc-skills-for-ai-ag
Apply machine learning for construction project risk assessment. Predict schedule delays, cost overruns, and safety incidents using historical data and project characteristics.
npx skills add majiayu000/claude-skill-registry --skill risk-assessment-ml-datadrivenconstructi-ddc-skills-for-ai-ag --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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 ```python import pandas as pd import numpy as np from sklearn.ensemble import RandomForestClassifier, GradientBoostingRegressor from sklearn.model_selection import train_test_split from sklearn.preprocessing import StandardScaler # Load historical project data projects = pd.read_csv("project_history.csv") # Features for risk prediction features = ['project_size_m2', 'budget_usd', 'duration_days', 'complexity_score', 'team_size', 'similar_projects_exp'] X = projects[features] y_delay = projects['had_delay'] # Binary: 1=delay, 0=on-time # Train risk model X_train, X_test, y_train, y_test = train_test_split(X, y_delay, test_size=0.2) model = RandomForestClassifier(n_estimators=100, random_state=42) model.fit(X_t
- Overview
- Quick Start
- Comprehensive Risk Model
- Risk Assessment Framework
- Feature Engineering
- Project Risk Features
- Risk Report Generation
- Quick Reference
- Resources
- Next Steps
What does the risk-assessment-ml-datadrivenconstructi-ddc-skills-for-ai-ag skill do?
Apply machine learning for construction project risk assessment. Predict schedule delays, cost overruns, and safety incidents using historical data and project characteristics.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill risk-assessment-ml-datadrivenconstructi-ddc-skills-for-ai-ag --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.