221 AI skills for construction: BIM analysis, cost estimation, scheduling, document control, and automation with Claude Code
- ✓Open-source license (MIT)
- ✓Healthy fork ratio
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git clone https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction ~/.claude/skills/ddc-skills-for-ai-agents-in-construction24 items en este repositorio
Generate automated daily progress reports from site data. Track work completed, labor hours, equipment usage, and weather conditions.
Analyze labor productivity from site data. Compare planned vs actual, identify trends, benchmark against industry standards.
Create interactive KPI dashboards for construction projects. Track schedule, cost, quality, and safety metrics in real-time.
Detect and analyze geometric clashes in BIM models. Identify MEP, structural, and architectural conflicts before construction.
Classify BIM elements using AI and standard classification systems. Map elements to UniFormat, MasterFormat, OmniClass, and CWICR codes.
Generate comprehensive BIM model validation reports. Check data quality, completeness, and compliance with standards.
Calculate CO2 emissions and carbon footprint from BIM model data. Analyze embodied carbon by material, element, and building system.
Extract quantities from IFC/Revit models for quantity takeoff. Uses DDC converters to get element counts, areas, volumes, lengths with grouping and reporting.
Analyze field progress photos. Catalog, tag, and compare against planned progress.
Generate images and visualizations from Revit/IFC files without BIM software. Python-based noBIM tool for batch processing.
Batch convert multiple CAD/BIM files (Revit, IFC, DWG, DGN) with progress tracking, error handling, and consolidated reporting.
Convert DGN files (v7-v8) to Excel databases. Extract elements, levels, and properties from infrastructure CAD files.
Convert AutoCAD DWG files (1983-2026) to Excel databases using DwgExporter CLI. Extract layers, blocks, attributes, and geometry data without Autodesk licenses.
Push Excel data back to BIM models. Update parameters, properties, and attributes from structured spreadsheets.
Import Excel data into RVT projects. Update element parameters, create schedules, and sync external data sources.
Convert IFC files (2x3, 4x1, 4x3) to Excel databases using IfcExporter CLI. Extract BIM data, properties, and geometry without proprietary software.
Convert RVT/RFA files to Excel databases. Extract BIM element data, properties, and quantities.
Convert RVT files to IFC format. Support IFC2x3, IFC4, IFC4.3 with customizable export settings.
Build cost assemblies from CWICR work items. Combine multiple items into reusable templates for common construction elements.
Analyze contractor bids against CWICR benchmarks. Identify pricing anomalies, compare bid components, and support bid evaluation decisions.
Process construction change orders using CWICR data. Calculate cost impact, compare to original estimate, and generate change order documentation.
Compare cost estimates across projects, versions, and scenarios. Identify variances, benchmark against standards, and generate comparison reports.
Calculate construction costs using DDC CWICR resource-based methodology. Break down costs into labor, materials, equipment with transparent pricing.
Optimize crew composition using CWICR labor norms. Balance productivity, cost, and skill requirements for construction crews.
Resumen de Skills
Lo que la gente pregunta sobre DDC_Skills_for_AI_Agents_in_Construction
¿Qué es datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction?
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datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction es skills para el ecosistema de Claude AI. 221 AI skills for construction: BIM analysis, cost estimation, scheduling, document control, and automation with Claude Code Tiene 173 estrellas en GitHub y se actualizó por última vez 3mo ago.
¿Cómo se instala DDC_Skills_for_AI_Agents_in_Construction?
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Puedes instalar DDC_Skills_for_AI_Agents_in_Construction clonando el repositorio (https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction) o siguiendo las instrucciones del README en GitHub. ClaudeWave también te ofrece bloques de instalación rápida en esta misma página.
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Nuestro agente de seguridad ha analizado datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction y le ha asignado un Trust Score de 87/100 (tier: Trusted). Revisa el desglose completo de comprobaciones superadas y flags en esta página.
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datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction es mantenido por datadrivenconstruction. La última actividad registrada en GitHub es de 3mo ago, con 2 issues abiertos.
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Sí. En ClaudeWave puedes explorar skills similares en /categories/skills, ordenados por popularidad o actividad reciente.
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