Claude Skills by datadrivenconstruction

Extract structured data from construction PDFs. Convert specifications, BOMs, schedules, and reports from PDF to Excel/CSV/JSON. Use OCR for scanned documents and pdfplumber for native PDFs.

Extract structured data from construction specifications. Parse CSI sections, requirements, submittals, and product data from spec documents.

Design data models for construction projects. Create entity-relationship diagrams, define schemas, and generate database structures.

Check data compliance with construction standards. Validate data against ISO 19650, IFC, COBie, UniFormat standards.

Detect anomalies and outliers in construction data: unusual costs, schedule variances, productivity spikes. Statistical and ML-based detection methods.

Track data origin, transformations, and flow through construction systems. Essential for audit trails, compliance, and debugging data issues.

Assess construction data quality using completeness, accuracy, consistency, timeliness, and validity metrics. Automated validation with regex patterns, thresholds, and reporting.

Build validation rules for construction data. Create RegEx and logic-based validation for BIM elements, cost codes, and schedule data.

Calculate construction costs using resource-based method. Estimate project costs from work items, physical resource norms, and current prices.

Build construction project estimates. Generate detailed cost breakdowns with labor, materials, equipment, and overhead.

Analyze historical construction costs for benchmarking, trend analysis, and estimating calibration. Compare projects, track escalation, identify patterns.

Calculate construction labor rates with overhead, benefits, and productivity factors. Regional rate databases and crew composition.

Manage construction unit price databases: update prices, track vendors, apply location factors, maintain historical records. Essential for accurate estimating.

Automatically generate estimates from QTO data. Apply pricing rules to BIM quantities for cost estimates.

Extract quantities from BIM/CAD data for cost estimation. Group by type, level, zone. Generate QTO reports.

Generate Quantity Take-Off (QTO) reports from BIM/CAD data. Extract volumes, areas, counts by category. Group elements, apply calculation rules, and create cost estimates automatically.

Create 4D construction simulations by linking BIM elements to project schedules. Generate time-based visualizations, sequence analysis, and construction phasing with Gantt integration.

Calculate carbon footprint of construction projects. Estimate CO2 emissions from materials, transportation, and construction processes using emission factors databases.

Generate Gantt charts for construction scheduling. Create visual project timelines with dependencies and progress tracking.

Calculate embodied carbon and lifecycle emissions for construction materials and projects. Support sustainable design decisions with carbon data.

Level and optimize construction resource allocation across project schedule. Balance labor, equipment usage, and avoid overallocation while maintaining critical path.

Extract and analyze data from construction ERP systems. Pull project data for analytics, reporting, and integration.

Analyze data interoperability issues in construction projects. Identify format incompatibilities and data loss points.

Create visualizations for construction data. Generate charts, graphs, heatmaps, and interactive dashboards using Matplotlib, Seaborn, and Plotly for project analysis and reporting.

Provide data-driven decision support for construction. Analyze multiple factors and recommend optimal project decisions.

Build KPI dashboards for construction projects. Track CPI, SPI, quality, safety metrics in real-time.

Forecast project outcomes using historical data: cost overruns, schedule delays, risk probabilities. Machine learning models for construction prediction.

What-if analysis for construction projects: model different scenarios and their cost/schedule/resource impacts. Compare alternatives and optimize decisions.

Create Apache Airflow DAGs for construction data pipelines. Orchestrate ETL, validation, and reporting workflows.

Build automated ETL (Extract-Transform-Load) pipelines for construction data. Process PDFs, Excel, BIM exports. Generate reports, dashboards, and integrate with other systems. Orchestrate with Airflow or n8n.

Automatically generate PDF reports from construction data. Create formatted project reports with charts and tables.

Automate construction data workflows. Build ETL pipelines and DAG workflows for recurring tasks.

Check BIM model consistency: naming conventions, parameter completeness, spatial relationships, and data integrity across model elements.

Build automated BIM validation pipelines for IFC/Revit data. Continuous validation against IDS, LOD requirements, COBie, and project-specific BEP standards.

Analyze BIM clash detection results and suggest resolutions. Prioritize clashes, identify patterns, assign responsibility, and track resolution status.

Check BIM data against IDS (Information Delivery Specification). Validate model information requirements and compliance.

Analyze large-scale construction datasets. Process thousands of projects for patterns, benchmarks, and predictive insights.

Convert construction data to/from Parquet format. Optimize storage, enable fast queries, and integrate with data lakehouses.

Implement semantic vector search for construction data. Build AI-powered search using embeddings and vector databases (Qdrant, ChromaDB) for intelligent querying of specifications, standards, and project documents.

Predict construction project costs using Machine Learning. Use Linear Regression, K-Nearest Neighbors, and Random Forest models on historical project data. Train, evaluate, and deploy cost prediction models.

Predict project duration using k-NN and regression. Estimate timeline based on similar historical projects.

Build ML models for construction predictions. Train and evaluate custom models for cost, duration, and risk prediction.

Automated pipeline for retraining ML models with new construction data. Monitor model drift, trigger retraining, and validate model performance.

Predict project completion dates using ML models. Forecast schedule delays based on current progress, historical patterns, and risk factors.

Assess organization's digital transformation readiness. Evaluate data culture, technology adoption, and process maturity.

Extract structured data from construction documents using LLMs. Process RFIs, submittals, contracts, specifications. Convert unstructured PDFs to structured JSON/Excel.

Build multi-agent AI systems for construction estimation. Use CrewAI/LangGraph to orchestrate specialized agents: QTO agent, pricing agent, validation agent. Automate complex estimation workflows.

Build n8n pipeline for automated cost estimation from Revit/IFC using DDC CWICR database and LLM classification.

Automate daily construction report generation using n8n workflow automation.

Automate construction photo report generation using n8n with AI-powered image analysis.