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SkillsMP has collected 238 skills from datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction. Open a skill to review its source and details.
datadrivenconstruction/DDC_Skills_for_AI_Agents_in_ConstructionShowing 40 of 238 collected skills.
Comprehensive Pandas toolkit for construction data analysis. Filter, group, aggregate BIM elements, calculate quantities, merge datasets, and generate reports from structured construction data.
Source text: Mixed languages
Build RAG systems for construction knowledge bases. Create searchable AI-powered construction document systems
Convert CAD/BIM files to structured data. Extract element data from Revit, IFC, DWG, DGN files.
Analyze construction drawings to extract dimensions, annotations, symbols, and metadata. Support quantity takeoff and design review automation.
Extract data from construction images using AI Vision. Analyze site photos, scanned documents, drawings.
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.
Source text: Mixed languages
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.
Source text: Russian
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.
Source text: Russian
Calculate carbon footprint of construction projects. Estimate CO2 emissions from materials, transportation, and construction processes using emission factors databases.
Source text: Mixed languages
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.
Source text: Russian
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.