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Get Started Free →Assist with quantity takeoff using CWICR data. Calculate quantities from dimensions, apply waste factors, and suggest related work items.
.claude/skills/datadrivenconstruction-cwicr-takeoff-helper/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-02 | ✗→✓ | ▲ Improved | 148% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 143% | 0% |
| case-05 | ✗→✓ | ▲ Improved | 213% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 284% | 0% |
| case-15 | ✗→✓ | ▲ Improved | 173% | 0% |
Quantity takeoff requires:
Assist takeoff process with CWICR-based calculations, automatic waste factors, unit conversions, and related item suggestions.
pythonimport pandas as pd import numpy as np from typing import Dict, Any, List, Optional, Tuple from dataclasses import dataclass from enum import Enum import math class TakeoffType(Enum): """Types of takeoff calculations.""" LINEAR = "linear" # Length AREA = "area" # Square measure VOLUME = "volume" # Cubic measure COUNT = "count" # Each/number WEIGHT = "weight" # By weight class UnitSystem(Enum): """Unit systems.""" METRIC = "metric" IMPERIAL = "imperial" @dataclass class TakeoffItem: """Single takeoff item.""" work_item_code: str description: str takeoff_type: TakeoffType gross_quantity: float waste_factor: float net_quantity: float unit: str dimensions: Dict[str, float] calculation: str @dataclass class TakeoffResult: """Complete takeoff result.""" items: List[TakeoffItem] total_items: int related_suggestions: List[str] # Unit conversion factors CONVERSIONS = { # Length ('m', 'ft'): 3.28084, ('ft', 'm'): 0.3048, ('m', 'in'): 39.3701, ('in', 'm'): 0.0254, # Area ('m2', 'sf'): 10.7639, ('sf', 'm2'): 0.0929, # Volume ('m3', 'cf'): 35.3147, ('cf', 'm3'): 0.0283, ('m3', 'cy'): 1.30795, ('cy', 'm3'): 0.7646, # Weight ('kg', 'lb'): 2.20462, ('lb', 'kg'): 0.453592, ('ton', 'kg'): 1000, ('kg', 'ton'): 0.001 } # Standard waste factors WASTE_FACTORS = { 'concrete': 0.05, 'rebar': 0.08, 'formwork': 0.10, 'brick': 0.10, 'block': 0.08, 'drywall': 0.12, 'tile': 0.15, 'lumber': 0.12, 'roofing': 0.10, 'paint': 0.10, 'pipe': 0.05, 'wire': 0.05, 'duct': 0.08, 'default': 0.05 } # Related work items by category RELATED_ITEMS = { 'concrete': ['formwork', 'rebar', 'curing', 'finishing'], 'masonry': ['mortar', 'reinforcement', 'ties', 'lintels'], 'drywall': ['framing', 'insulation', 'taping', 'painting'], 'roofing': ['underlayment', 'flashing', 'ventilation', 'insulation'], 'flooring': ['underlayment', 'adhesive', 'trim', 'transitions'] } class CWICRTakeoffHelper: """Assist with quantity takeoff using CWICR data.""" def __init__(self, cwicr_data: pd.DataFrame = None): self.cwicr = cwicr_data if cwicr_data is not None: self._index_cwicr() def _index_cwicr(self): """Index CWICR data.""" if 'work_item_code' in self.cwicr.columns: self._cwicr_index = self.cwicr.set_index('work_item_code') else: self._cwicr_index = None def convert_unit(self, value: float, from_unit: str, to_unit: str) -> float: """Convert between units.""" if from_unit == to_unit: return value key = (from_unit.lower(), to_unit.lower()) if key in CONVERSIONS: return value * CONVERSIONS[key] # Try reverse reverse_key = (to_unit.lower(), from_unit.lower()) if reverse_key in CONVERSIONS: return value / CONVERSIONS[reverse_key] return value def get_waste_factor(self, work_item_code: str) -> float: """Get waste factor for work item.""" code_lower = work_item_code.lower() for material, factor in WASTE_FACTORS.items(): if material in code_lower: return factor return WASTE_FACTORS['default'] def calculate_area(self, length: float, width: float, deductions: List[Tuple[float, float]] = None) -> Dict[str, float]: """Calculate area with deductions.""" gross_area = length * width deduction_area = 0 if deductions: for d_length, d_width in deductions: deduction_area += d_length * d_width net_area = gross_area - deduction_area return { 'gross_area': round(gross_area, 2), 'deductions': round(deduction_area, 2), 'net_area': round(net_area, 2), 'calculation': f"{length} x {width} = {gross_area}, minus {deduction_area} deductions" } def calculate_volume(self, length: float, width: float, depth: float) -> Dict[str, float]: """Calculate volume.""" volume = length * width * depth return { 'volume': round(volume, 3), 'calculation': f"{length} x {width} x {depth} = {volume}" } def calculate_perimeter(self, length: float, width: float) -> Dict[str, float]: """Calculate perimeter.""" perimeter = 2 * (length + width) return { 'perimeter': round(perimeter, 2), 'calculation': f"2 x ({length} + {width}) = {perimeter}" } def calculate_concrete(self, length: float, width: float, thickness: float, work_item_code: str = "CONC-001") -> TakeoffItem: """Calculate concrete quantity with related items.""" volume = length * width * thickness waste = self.get_waste_factor(work_item_code) net_qty = volume * (1 + waste) return TakeoffItem( work_item_code=work_item_code, description="Concrete", takeoff_type=TakeoffType.VOLUME, gross_quantity=round(volume, 3), waste_factor=waste, net_quantity=round(net_qty, 3), unit="m3", dimensions={'length': length, 'width': width, 'thickness': thickness}, calculation=f"{length}m x {width}m x {thickness}m = {volume:.3f} m3 + {waste:.0%} waste" ) def calculate_wall_area(self, perimeter: float, height: float, openings: List[Tuple[float, float]] = None, work_item_code: str = "WALL-001") -> TakeoffItem: """Calculate wall area with openings deducted.""" gross_area = perimeter * height opening_area = 0 if openings: for w, h in openings: opening_area += w * h net_area = gross_area - opening_area waste = self.get_waste_factor(work_item_code) order_qty = net_area * (1 + waste) return TakeoffItem( work_item_code=work_item_code, description="Wall finish", takeoff_type=TakeoffType.AREA, gross_quantity=round(gross_area, 2), waste_factor=waste, net_quantity=round(order_qty, 2), unit="m2", dimensions={'perimeter': perimeter, 'height': height, 'openings': len(openings or [])}, calculation=f"{perimeter}m x {height}m = {gross_area:.2f} m2 - {opening_area:.2f} openings + {waste:.0%} waste" ) def calculate_flooring(self, length: float, width: float, work_item_code: str = "FLOOR-001") -> TakeoffItem: """Calculate flooring quantity.""" area = length * width waste = self.get_waste_factor(work_item_code) order_qty = area * (1 + waste) return TakeoffItem( work_item_code=work_item_code, description="Flooring", takeoff_type=TakeoffType.AREA, gross_quantity=round(area, 2), waste_factor=waste, net_quantity=round(order_qty, 2), unit="m2", dimensions={'length': length, 'width': width}, calculation=f"{length}m x {width}m = {area:.2f} m2 + {waste:.0%} waste" ) def calculate_rebar(self, concrete_volume: float, kg_per_m3: float = 100, work_item_code: str = "REBAR-001") -> TakeoffItem: """Calculate rebar from concrete volume.""" weight = concrete_volume * kg_per_m3 waste = self.get_waste_factor(work_item_code) order_qty = weight * (1 + waste) return TakeoffItem( work_item_code=work_item_code, description="Reinforcement", takeoff_type=TakeoffType.WEIGHT, gross_quantity=round(weight, 1), waste_factor=waste, net_quantity=round(order_qty, 1), unit="kg", dimensions={'concrete_m3': concrete_volume, 'kg_per_m3': kg_per_m3}, calculation=f"{concrete_volume} m3 x {kg_per_m3} kg/m3 = {weight:.1f} kg + {waste:.0%} waste" ) def suggest_related_items(self, work_item_code: str) -> List[str]: """Suggest related work items.""" code_lower = work_item_code.lower() for category, related in RELATED_ITEMS.items(): if category in code_lower: return related return [] def room_takeoff(self, length: float, width: float, height: float, openings: List[Tuple[float, float]] = None) -> TakeoffResult: """Complete room takeoff.""" items = [] # Floor floor = self.calculate_flooring(length, width, "FLOOR-001") items.append(floor) # Ceiling (same as floor) ceiling = TakeoffItem( work_item_code="CEIL-001", description="Ceiling", takeoff_type=TakeoffType.AREA, gross_quantity=floor.gross_quantity, waste_factor=floor.waste_factor, net_quantity=floor.net_quantity, unit="m2", dimensions=floor.dimensions, calculation=f"Same as floor: {floor.gross_quantity} m2" ) items.append(ceiling) # Walls perimeter = 2 * (length + width) walls = self.calculate_wall_area(perimeter, height, openings, "WALL-001") items.append(walls) # Related suggestions suggestions = ['paint', 'baseboard', 'trim', 'electrical outlets'] return TakeoffResult( items=items, total_items=len(items), related_suggestions=suggestions ) def export_takeoff(self, items: List[TakeoffItem], output_path: str) -> str: """Export takeoff to Excel.""" with pd.ExcelWriter(output_path, engine='openpyxl') as writer: df = pd.DataFrame([ { 'Work Item Code': item.work_item_code, 'Description': item.description, 'Type': item.takeoff_type.value, 'Gross Qty': item.gross_quantity, 'Waste %': f"{item.waste_factor:.0%}", 'Net Qty': item.net_quantity, 'Unit': item.unit, 'Calculation': item.calculation } for item in items ]) df.to_excel(writer, sheet_name='Takeoff', index=False) return output_path
python# Initialize helper helper = CWICRTakeoffHelper() # Calculate concrete slab concrete = helper.calculate_concrete( length=10, width=8, thickness=0.2 ) print(f"Gross: {concrete.gross_quantity} m3") print(f"Order Qty: {concrete.net_quantity} m3") print(f"Calculation: {concrete.calculation}")
pythonroom = helper.room_takeoff( length=5, width=4, height=2.8, openings=[(0.9, 2.1), (1.2, 1.5)] # door, window ) for item in room.items: print(f"{item.description}: {item.net_quantity} {item.unit}")
pythonmeters = helper.convert_unit(100, 'ft', 'm') print(f"100 ft = {meters:.2f} m")
pythonconcrete = helper.calculate_concrete(10, 8, 0.3) rebar = helper.calculate_rebar(concrete.gross_quantity, kg_per_m3=120) print(f"Rebar: {rebar.net_quantity} kg")
pythonrelated = helper.suggest_related_items("CONC-SLAB-001") print(f"Related: {related}")
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-20 | pass→pass | 15,895 | 12,085 | -24% | 1 | 1 | 0% | 3,176 | 6,209 | +95% | 0 | 0 | — |
case-01 | fail→fail | 14,692 | 12,681 | -14% | 1 | 1 | 0% | 3,216 | 6,586 | +105% | 0 | 0 | — |
case-06 | pass→pass | 7,921 | 6,498 | -18% | 1 | 1 | 0% | 1,346 | 5,004 | +272% | 0 | 0 | — |
case-02 | fail→pass | 22,074 | 9,849 | -55% | 1 | 1 | 0% | 2,322 | 5,754 | +148% | 0 | 0 | — |
case-03 | pass→pass | 8,209 | 5,111 | -38% | 1 | 1 | 0% | 1,613 | 4,800 | +198% | 0 | 0 | — |
case-04 | fail→pass | 11,014 | 6,722 | -39% | 1 | 1 | 0% | 2,121 | 5,158 | +143% | 0 | 0 | — |
case-05 | fail→pass | 8,331 | 4,665 | -44% | 1 | 1 | 0% | 1,488 | 4,651 | +213% | 0 | 0 | — |
case-07 | fail→pass | 13,741 | 5,498 | -60% | 1 | 1 | 0% | 1,240 | 4,756 | +284% | 0 | 0 | — |
case-08 | pass→pass | 2,946 | 2,977 | +1% | 1 | 1 | 0% | 521 | 4,261 | +718% | 0 | 0 | — |
case-09 | pass→pass | 6,816 | 3,804 | -44% | 1 | 1 | 0% | 1,154 | 4,447 | +285% | 0 | 0 | — |
case-10 | pass→pass | 3,217 | 2,790 | -13% | 1 | 1 | 0% | 564 | 4,252 | +654% | 0 | 0 | — |
case-11 | pass→pass | 2,253 | 2,741 | +22% | 1 | 1 | 0% | 364 | 4,239 | +1065% | 0 | 0 | — |
case-12 | pass→pass | 4,277 | 4,607 | +8% | 1 | 1 | 0% | 954 | 4,679 | +390% | 0 | 0 | — |
case-13 | pass→pass | 5,695 | 6,914 | +21% | 1 | 1 | 0% | 1,351 | 5,293 | +292% | 0 | 0 | — |
case-14 | pass→pass | 14,352 | 7,618 | -47% | 1 | 1 | 0% | 2,197 | 5,068 | +131% | 0 | 0 | — |
case-15 | fail→pass | 13,479 | 12,239 | -9% | 1 | 1 | 0% | 2,159 | 5,900 | +173% | 0 | 0 | — |
case-16 | pass→pass | 12,120 | 8,930 | -26% | 1 | 1 | 0% | 1,977 | 5,464 | +176% | 0 | 0 | — |
case-17 | fail→pass | 10,387 | 6,752 | -35% | 1 | 1 | 0% | 1,877 | 5,125 | +173% | 0 | 0 | — |
case-18 | pass→pass | 4,944 | 3,905 | -21% | 1 | 1 | 0% | 904 | 4,549 | +403% | 0 | 0 | — |
case-19 | fail→fail | 16,602 | 9,971 | -40% | 1 | 1 | 0% | 3,446 | 5,855 | +70% | 0 | 0 | — |
case-21 | pass→pass | 22,192 | 27,819 | +25% | 1 | 1 | 0% | 4,679 | 9,977 | +113% | 0 | 0 | — |
case-22 | pass→pass | 9,465 | 13,418 | +42% | 1 | 1 | 0% | 1,550 | 6,209 | +301% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +27 percentage points is the difference between those two pass rates over the 22 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.