labor-rate — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited labor-rate (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
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Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Labor costs account for 30-50% of construction costs. This skill calculates all-in labor rates including wages, benefits, overhead, and regional adjustments.
import pandas as pd
from typing import Dict, Any, List, Optional
from dataclasses import dataclass, field
from enum import Enum
class LaborCategory(Enum):
"""Labor skill categories."""
LABORER = "laborer"
CARPENTER = "carpenter"
ELECTRICIAN = "electrician"
PLUMBER = "plumber"
IRONWORKER = "ironworker"
MASON = "mason"
OPERATOR = "equipment_operator"
FOREMAN = "foreman"
SUPERINTENDENT = "superintendent"
class WorkType(Enum):
"""Work type for productivity."""
NEW_CONSTRUCTION = "new"
RENOVATION = "renovation"
DEMOLITION = "demolition"
MAINTENANCE = "maintenance"
@dataclass
class LaborRate:
"""Complete labor rate breakdown."""
category: str
base_wage: float
benefits: float
taxes: float
insurance: float
overhead: float
profit: float
total_rate: float
unit: str = "hour"
@dataclass
class CrewComposition:
"""Crew composition for work."""
name: str
workers: List[Dict[str, Any]]
total_hourly_cost: float
output_per_hour: float
unit: str
class LaborRateCalculator:
"""Calculate construction labor rates."""
# Default burden rates (percent of base wage)
DEFAULT_BURDENS = {
'benefits': 0.30, # Health, pension, vacation
'taxes': 0.10, # FICA, unemployment
'insurance': 0.08, # Workers comp, liability
'overhead': 0.15, # General conditions
'profit': 0.10 # Contractor profit
}
# Base wages by category (USD/hour, US average)
BASE_WAGES = {
LaborCategory.LABORER: 22,
LaborCategory.CARPENTER: 32,
LaborCategory.ELECTRICIAN: 38,
LaborCategory.PLUMBER: 36,
LaborCategory.IRONWORKER: 35,
LaborCategory.MASON: 34,
LaborCategory.OPERATOR: 40,
LaborCategory.FOREMAN: 45,
LaborCategory.SUPERINTENDENT: 55
}
# Regional factors
REGIONAL_FACTORS = {
'US_National': 1.00,
'New_York': 1.45,
'San_Francisco': 1.40,
'Chicago': 1.15,
'Houston': 0.95,
'Atlanta': 0.90,
'Germany_Berlin': 1.20,
'UK_London': 1.35
}
def __init__(self, burden_rates: Dict[str, float] = None):
self.burdens = burden_rates or self.DEFAULT_BURDENS
def calculate_rate(self, category: LaborCategory,
region: str = 'US_National',
custom_wage: float = None) -> LaborRate:
"""Calculate all-in labor rate."""
# Get base wage
base = custom_wage or self.BASE_WAGES.get(category, 25)
# Apply regional factor
regional_factor = self.REGIONAL_FACTORS.get(region, 1.0)
base *= regional_factor
# Calculate burden components
benefits = base * self.burdens['benefits']
taxes = base * self.burdens['taxes']
insurance = base * self.burdens['insurance']
# Subtotal before markup
subtotal = base + benefits + taxes + insurance
# Overhead and profit
overhead = subtotal * self.burdens['overhead']
profit = (subtotal + overhead) * self.burdens['profit']
total = subtotal + overhead + profit
return LaborRate(
category=category.value,
base_wage=round(base, 2),
benefits=round(benefits, 2),
taxes=round(taxes, 2),
insurance=round(insurance, 2),
overhead=round(overhead, 2),
profit=round(profit, 2),
total_rate=round(total, 2)
)
def calculate_crew_cost(self, composition: Dict[LaborCategory, int],
region: str = 'US_National') -> float:
"""Calculate hourly cost for crew composition."""
total = 0
for category, count in composition.items():
rate = self.calculate_rate(category, region)
total += rate.total_rate * count
return round(total, 2)
def get_rate_table(self, region: str = 'US_National') -> pd.DataFrame:
"""Generate rate table for all categories."""
rates = []
for category in LaborCategory:
rate = self.calculate_rate(category, region)
rates.append({
'category': rate.category,
'base_wage': rate.base_wage,
'benefits': rate.benefits,
'taxes': rate.taxes,
'insurance': rate.insurance,
'overhead': rate.overhead,
'profit': rate.profit,
'total_rate': rate.total_rate
})
return pd.DataFrame(rates)
class ProductivityFactor:
"""Calculate productivity factors for labor."""
# Base productivity factors
WORK_TYPE_FACTORS = {
WorkType.NEW_CONSTRUCTION: 1.0,
WorkType.RENOVATION: 0.75,
WorkType.DEMOLITION: 0.90,
WorkType.MAINTENANCE: 0.65
}
# Condition factors
CONDITION_FACTORS = {
'ideal': 1.0,
'normal': 0.90,
'difficult': 0.75,
'hazardous': 0.60,
'confined_space': 0.50
}
# Weather factors
WEATHER_FACTORS = {
'clear': 1.0,
'hot': 0.85,
'cold': 0.80,
'rain': 0.60,
'wind': 0.75
}
def calculate_factor(self, work_type: WorkType,
condition: str = 'normal',
weather: str = 'clear',
overtime_hours: int = 0) -> float:
"""Calculate combined productivity factor."""
base = self.WORK_TYPE_FACTORS.get(work_type, 1.0)
cond = self.CONDITION_FACTORS.get(condition, 0.9)
weath = self.WEATHER_FACTORS.get(weather, 1.0)
# Overtime degradation (productivity drops after 8 hours)
overtime_factor = 1.0
if overtime_hours > 0:
# Each OT hour is ~15% less productive
overtime_factor = 1 - (overtime_hours * 0.015)
combined = base * cond * weath * overtime_factor
return round(max(combined, 0.3), 2) # Minimum 30% productivity
def adjust_labor_hours(self, base_hours: float,
work_type: WorkType,
condition: str = 'normal',
weather: str = 'clear') -> float:
"""Adjust labor hours for conditions."""
factor = self.calculate_factor(work_type, condition, weather)
return round(base_hours / factor, 1)
class CrewBuilder:
"""Build and optimize crew compositions."""
# Standard crew compositions
STANDARD_CREWS = {
'concrete_pour': {
LaborCategory.FOREMAN: 1,
LaborCategory.CARPENTER: 2,
LaborCategory.LABORER: 4,
LaborCategory.OPERATOR: 1
},
'framing': {
LaborCategory.FOREMAN: 1,
LaborCategory.CARPENTER: 4,
LaborCategory.LABORER: 2
},
'electrical_rough': {
LaborCategory.FOREMAN: 1,
LaborCategory.ELECTRICIAN: 3,
LaborCategory.LABORER: 1
},
'plumbing_rough': {
LaborCategory.FOREMAN: 1,
LaborCategory.PLUMBER: 2,
LaborCategory.LABORER: 1
},
'masonry': {
LaborCategory.FOREMAN: 1,
LaborCategory.MASON: 4,
LaborCategory.LABORER: 4
}
}
def __init__(self, rate_calculator: LaborRateCalculator):
self.calc = rate_calculator
def get_crew(self, work_type: str,
region: str = 'US_National') -> CrewComposition:
"""Get standard crew composition with costs."""
if work_type not in self.STANDARD_CREWS:
raise ValueError(f"Unknown work type: {work_type}")
composition = self.STANDARD_CREWS[work_type]
total_cost = self.calc.calculate_crew_cost(composition, region)
workers = []
for category, count in composition.items():
rate = self.calc.calculate_rate(category, region)
workers.append({
'category': category.value,
'count': count,
'hourly_rate': rate.total_rate,
'subtotal': rate.total_rate * count
})
return CrewComposition(
name=work_type,
workers=workers,
total_hourly_cost=total_cost,
output_per_hour=1.0, # Placeholder
unit='hour'
)
def custom_crew(self, workers: Dict[LaborCategory, int],
region: str = 'US_National') -> CrewComposition:
"""Build custom crew composition."""
total_cost = self.calc.calculate_crew_cost(workers, region)
worker_list = []
for category, count in workers.items():
rate = self.calc.calculate_rate(category, region)
worker_list.append({
'category': category.value,
'count': count,
'hourly_rate': rate.total_rate,
'subtotal': rate.total_rate * count
})
return CrewComposition(
name='custom',
workers=worker_list,
total_hourly_cost=total_cost,
output_per_hour=1.0,
unit='hour'
)calc = LaborRateCalculator()
# Get single rate
rate = calc.calculate_rate(LaborCategory.CARPENTER, region='New_York')
print(f"Carpenter rate NYC: ${rate.total_rate}/hr")
# Rate table
rates = calc.get_rate_table('US_National')
print(rates)builder = CrewBuilder(calc)
concrete_crew = builder.get_crew('concrete_pour', 'Chicago')
print(f"Crew cost: ${concrete_crew.total_hourly_cost}/hr")productivity = ProductivityFactor()
factor = productivity.calculate_factor(
WorkType.RENOVATION,
condition='difficult',
weather='hot'
)
adjusted_hours = productivity.adjust_labor_hours(100, WorkType.RENOVATION)~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.