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Calculate construction labor rates with overhead, benefits, and productivity factors. Regional rate databases and crew composition.
Passed 17 of 22 test cases with the skill, and 3 of 22 without it.
and 24 more in the full report
14 fixed3 passed either way5 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 14 test cases the skill fixed. Same model, same prompt, with and without the skill.
I'm estimating a renovation project that normally takes 150 base labor hours, but it will take place under difficult working conditions with hot weather. Please adjust the labor hours to account for these conditions and present the resulting productivity factor alongside the adjusted total labor hours.
| Checked | Without skill | With skill |
|---|---|---|
| identifies the combined productivity factor as 0.48 | Missed | Passed |
| calculates the adjusted total labor hours as 312.5 hours | Missed | Passed |
The instructions your model reads when the skill loads.
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
test cases passed, vs 3 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.