cwicr-report-generator
The CWICR Report Generator creates professional cost estimation reports from construction cost calculations, producing executive summaries, detailed cost breakdowns, and visual charts exportable as HTML, PDF, or Excel files. Use this skill when you need to transform raw cost data into formatted, client-ready documentation that clearly presents labor, materials, equipment, overhead, and profit components across multiple output formats.
git clone --depth 1 https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction /tmp/cwicr-report-generator && cp -r /tmp/cwicr-report-generator/1_DDC_Toolkit/CWICR-Database/cwicr-report-generator ~/.claude/skills/cwicr-report-generatorSKILL.md
# CWICR Report Generator
## Overview
Generate professional cost reports from CWICR calculations - executive summaries, detailed breakdowns, charts, and export to multiple formats.
## Python Implementation
```python
import pandas as pd
from typing import Dict, Any, List, Optional
from dataclasses import dataclass, field
from datetime import datetime
from pathlib import Path
import json
@dataclass
class ReportSection:
"""Report section content."""
title: str
content: str
chart_type: Optional[str] = None
chart_data: Optional[Dict] = None
@dataclass
class CostReport:
"""Complete cost report."""
project_name: str
generated_date: datetime
total_cost: float
currency: str
sections: List[ReportSection]
line_items: List[Dict]
summary: Dict[str, Any]
class CWICRReportGenerator:
"""Generate cost estimation reports."""
def __init__(self, project_name: str = "Project",
currency: str = "USD"):
self.project_name = project_name
self.currency = currency
self.sections: List[ReportSection] = []
self.line_items: List[Dict] = []
def add_summary(self, summary_data: Dict[str, float]):
"""Add executive summary section."""
content = f"""
<div class="summary-box">
<h3>Cost Summary</h3>
<table class="summary-table">
<tr><td>Labor</td><td class="amount">${summary_data.get('labor', 0):,.2f}</td></tr>
<tr><td>Materials</td><td class="amount">${summary_data.get('material', 0):,.2f}</td></tr>
<tr><td>Equipment</td><td class="amount">${summary_data.get('equipment', 0):,.2f}</td></tr>
<tr><td>Overhead</td><td class="amount">${summary_data.get('overhead', 0):,.2f}</td></tr>
<tr><td>Profit</td><td class="amount">${summary_data.get('profit', 0):,.2f}</td></tr>
<tr class="total"><td>TOTAL</td><td class="amount">${summary_data.get('total', 0):,.2f}</td></tr>
</table>
</div>
"""
self.sections.append(ReportSection(
title="Executive Summary",
content=content,
chart_type="pie",
chart_data={
'labels': ['Labor', 'Materials', 'Equipment', 'Overhead', 'Profit'],
'values': [
summary_data.get('labor', 0),
summary_data.get('material', 0),
summary_data.get('equipment', 0),
summary_data.get('overhead', 0),
summary_data.get('profit', 0)
]
}
))
def add_breakdown_by_category(self, breakdown: Dict[str, float]):
"""Add breakdown by category section."""
rows = ""
for category, cost in sorted(breakdown.items(), key=lambda x: -x[1]):
rows += f"<tr><td>{category}</td><td class='amount'>${cost:,.2f}</td></tr>"
content = f"""
<table class="detail-table">
<thead><tr><th>Category</th><th>Cost</th></tr></thead>
<tbody>{rows}</tbody>
</table>
"""
self.sections.append(ReportSection(
title="Cost by Category",
content=content,
chart_type="bar",
chart_data={
'labels': list(breakdown.keys()),
'values': list(breakdown.values())
}
))
def add_line_items(self, items: List[Dict]):
"""Add detailed line items."""
self.line_items = items
rows = ""
for item in items[:50]: # Limit for report
rows += f"""
<tr>
<td>{item.get('code', '')}</td>
<td>{item.get('description', '')[:50]}</td>
<td>{item.get('quantity', 0):,.2f}</td>
<td>{item.get('unit', '')}</td>
<td class="amount">${item.get('unit_price', 0):,.2f}</td>
<td class="amount">${item.get('total', 0):,.2f}</td>
</tr>
"""
content = f"""
<table class="line-items">
<thead>
<tr>
<th>Code</th>
<th>Description</th>
<th>Qty</th>
<th>Unit</th>
<th>Unit Price</th>
<th>Total</th>
</tr>
</thead>
<tbody>{rows}</tbody>
</table>
"""
self.sections.append(ReportSection(
title="Line Items",
content=content
))
def generate_html(self) -> str:
"""Generate HTML report."""
sections_html = ""
for section in self.sections:
sections_html += f"""
<section class="report-section">
<h2>{section.title}</h2>
{section.content}
</section>
"""
html = f"""
<!DOCTYPE html>
<html>
<head>
<title>Cost Report - {self.project_name}</title>
<style>
body {{ font-family: 'Segoe UI', Arial, sans-serif; margin: 40px; background: #f5f5f5; }}
.report-container {{ max-width: 1200px; margin: 0 auto; background: white; padding: 40px; box-shadow: 0 2px 10px rgba(0,0,0,0.1); }}
h1 {{ color: #2c3e50; border-bottom: 3px solid #3498db; padding-bottom: 10px; }}
h2 {{ color: #34495e; margin-top: 30px; }}
.summary-box {{ background: #ecf0f1; padding: 20px; border-radius: 8px; }}
table {{ width: 100%; border-collapse: collapse; margin: 20px 0; }}
th, td {{ padding: 12px; text-align: left; border-bottom: 1px solid #ddd; }}
th {{ background: #3498db; color: white; }}
.amount {{ text-align: right; font-family: monospace; }}
.total {{ font-weight: bold; background: #f8f9fa; }}
.line-items td {{ font-size: 0.9em; }}
.meta {{ color: #7f8c8d; font-size: 0.9em; margin-bottom: 20px; }}
</style>
</head>
<body>Analyze 5000+ IFC and Revit projects at scale for patterns, benchmarks, and insights. Big data analysis for construction.
Manage as-built documentation for project closeout. Track drawing markups, coordinate updates, and verify completeness.
Track as-built documentation and record drawings. Monitor submission status, manage revisions, and ensure completeness for handover.
Batch convert multiple CAD/BIM files (Revit, IFC, DWG, DGN) with progress tracking, error handling, and consolidated reporting.
Compare and analyze contractor bids. Score proposals, identify scope gaps, and recommend selections.
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.
Automated cost estimation from BIM models using DDC CWICR database (8 national bases, 78,228 positions). AI classification + vector search for accurate pricing.