cwicr-work-breakdown

cwicr-work-breakdown is a skill for Claude Code, Codex from datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction. It costs 34 tokens per session (3,747 once invoked), scanned A, original, MIT.

A construction estimating helper that opens up a combined work item into its component resources, such as labor, materials, equipment, and overhead.

In plain words
What is it for?
Use it to create detailed resource bills, prepare material lists, identify labor and equipment needs, and track resource quantities and costs.
Why use it?
It makes aggregated costs easier to understand and shows what resources a work item actually needs.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: built for openclaw.

Good fit Use it to create detailed resource bills, prepare material lists, identify labor and equipment needs, and track resource quantities and costs.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/cwicr-work-breakdown
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill cwicr-work-breakdown
Clone the repo
git clone --depth 1 https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction

Made for: Claude Code, Codex.

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README.md
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Per session 34 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,747 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00034 $0.03747
Opus 5 $0.00017 $0.01873
Sonnet 5 $0.00007 $0.00749
Haiku 4.5 $0.00003 $0.00375

Measured 13d ago against content hash cbd91d7be357, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

cwicr-work-breakdown scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

1_DDC_Toolkit/CWICR-Database/cwicr-work-breakdown/SKILL.md · 469 lines

How it starts

The opening of the file, as written. The whole thing — 469 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CWICR Work Breakdown

Business Case

Problem Statement

Work items in CWICR contain aggregated resources:

  • What materials make up a concrete work item?
  • What labor categories are needed?
  • What equipment is involved?
  • How to generate detailed resource bills?

Solution

Decompose CWICR work items into their constituent resources (labor, materials, equipment) with quantities and costs.

Business Value

  • Transparency - See inside aggregated items
  • Procurement - Generate material lists
  • Scheduling - Identify resource needs
  • Cost control - Track resource consumption

Technical Implementation

import pandas as pd
import numpy as np
from typing import Dict, Any, List, Optional, Tuple
from dataclasses import dataclass, field
from datetime import datetime
from enum import Enum
from collections import defaultdict


class ResourceType(Enum):
    """Types of resources in work items."""
    LABOR = "labor"
    MATERIAL = "material"
    EQUIPMENT = "equipment"
    OVERHEAD = "overhead"


@dataclass
class ResourceComponent:
    """Single resource component of a work item."""
    resource_code: str
    resource_type: ResourceType
    description: str
    unit: str
    quantity_per_unit: float  # Per unit of work item
    unit_rate: float
    cost_per_unit: float  # Per unit of work item


@dataclass
class WorkItemBreakdown:
    """Complete breakdown of a work item."""
    work_item_code: str
    work_item_description: str
    work_item_unit: str
    components: List[ResourceComponent]
    labor_cost_per_unit: float
    material_cost_per_unit: float
    equipment_cost_per_unit: float
    total_cost_per_unit: float


@dataclass
class BillOfResources:
    """Bill of resources for multiple work items."""
    project_name: str
    total_labor_cost: float
    total_material_cost: float
    total_equipment_cost: float
    total_cost: float
    labor_resources: List[Dict[str, Any]]
    material_resources: List[Dict[str, Any]]
    equipment_resources: List[Dict[str, Any]]


class CWICRWorkBreakdown:
    """Break down work items into resources."""

    def __init__(self, cwicr_data: pd.DataFrame,
                 resources_data: pd.DataFrame = None):
        self.work_items = cwicr_data
        self.resources = resources_data
        self._index_data()

    def _index_data(self):
        """Index data for fast lookup."""
        if 'work_item_code' in self.work_items.columns:
            self._work_index = self.work_items.set_index('work_item_code')
        else:
            self._work_index = None

        if self.resources is not None and 'resource_code' in self.resources.columns:
            self._resource_index = self.resources.set_index('resource_code')
        else:
            self._resource_index = None

    def breakdown_work_item(self, work_item_code: str) -> Optional[WorkItemBreakdown]:
        """Break down single work item into components."""

        if self._work_index is None or work_item_code not in self._work_index.index:
            return None

        item = self._work_index.loc[work_item_code]
        components = []

        # Extract labor component
        labor_norm = float(item.get('labor_norm', 0) or 0)
        labor_rate = float(item.get('labor_rate', 35) or 35)
        labor_cost = float(item.get('labor_cost', labor_norm * labor_rate) or labor_norm * labor_rate)

        if labor_norm > 0:
            components.append(ResourceComponent(
                resource_code=f"{work_item_code}-LABOR",
                resource_type=ResourceType.LABOR,
                description=f"Labor for {item.get('description', '')}",
                unit="hr",
                quantity_per_unit=labor_norm,
                unit_rate=labor_rate,
                cost_per_unit=labor_cost
            ))

        # Extract material component
        material_norm = float(item.get('material_norm', 1) or 1)
        material_cost = float(item.get('material_cost', 0) or 0)

        if material_cost > 0:
            components.append(ResourceComponent(
                resource_code=f"{work_item_code}-MAT",
                resource_type=ResourceType.MATERIAL,
                description=str(item.get('material_description', 'Materials')),
                unit=str(item.get('material_unit', item.get('unit', 'ea'))),
                quantity_per_unit=material_norm,
                unit_rate=material_cost / material_norm if material_norm > 0 else material_cost,
                cost_per_unit=material_cost
            ))

        # Extract equipment component
        equipment_norm = float(item.get('equipment_norm', 0) or 0)
        equipment_rate = float(item.get('equipment_rate', 0) or 0)
        equipment_cost = float(item.get('equipment_cost', equipment_norm * equipment_rate) or 0)

        if equipment_norm > 0 or equipment_cost > 0:
            components.append(ResourceComponent(
                resource_code=f"{work_item_code}-EQUIP",
                resource_type=ResourceType.EQUIPMENT,
                description=str(item.get('equipment_description', 'Equipment')),
                unit="hr",
                quantity_per_unit=equipment_norm,
                unit_rate=equipment_rate,
                cost_per_unit=equipment_cost
            ))

        return WorkItemBreakdown(
            work_item_code=work_item_code,
            work_item_description=str(item.get('description', '')),
            work_item_unit=str(item.get('unit', '')),
            components=components,
            labor_cost_per_unit=labor_cost,
            material_cost_per_unit=material_cost,
            equipment_cost_per_unit=equipment_cost,
            total_cost_per_unit=labor_cost + material_cost + equipment_cost
        )

    def generate_bill_of_resources(self,
                                    items: List[Dict[str, Any]],
                                    project_name: str = "Project") -> BillOfResources:
        """Generate bill of resources from work items."""

        labor_agg = defaultdict(lambda: {'hours': 0, 'cost': 0, 'work_items': []})
        material_agg = defaultdict(lambda: {'quantity': 0, 'cost': 0, 'unit': '', 'work_items': []})
        equipment_agg = defaultdict(lambda: {'hours': 0, 'cost': 0, 'work_items': []})

        for item in items:
            code = item.get('work_item_code', item.get('code'))
            qty = item.get('quantity', 0)

            breakdown = self.breakdown_work_item(code)
            if not breakdown:
                continue

            for component in breakdown.components:
                scaled_qty = component.quantity_per_unit * qty
                scaled_cost = component.cost_per_unit * qty

                if component.resource_type == ResourceType.LABOR:
                    key = 'General Labor'  # Could be more specific with skill data
                    labor_agg[key]['hours'] += scaled_qty
                    labor_agg[key]['cost'] += scaled_cost
                    labor_agg[key]['work_items'].append(code)

                elif component.resource_type == ResourceType.MATERIAL:
                    key = component.description
                    material_agg[key]['quantity'] += scaled_qty
                    material_agg[key]['cost'] += scaled_cost
                    material_agg[key]['unit'] = component.unit
                    material_agg[key]['work_items'].append(code)

                elif component.resource_type == ResourceType.EQUIPMENT:
                    key = component.description
                    equipment_agg[key]['hours'] += scaled_qty
                    equipment_agg[key]['cost'] += scaled_cost
                    equipment_agg[key]['work_items'].append(code)

        # Convert to lists
        labor_resources = [
            {
                'resource': name,
                'hours': round(data['hours'], 1),
                'cost': round(data['cost'], 2),
                'work_items': len(set(data['work_items']))
            }
            for name, data in labor_agg.items()
        ]

        material_resources = [
            {
                'resource': name,
                'quantity': round(data['quantity'], 2),
                'unit': data['unit'],
                'cost': round(data['cost'], 2),
                'work_items': len(set(data['work_items']))
            }
            for name, data in material_agg.items()
        ]

        equipment_resources = [
            {
                'resource': name,
                'hours': round(data['hours'], 1),
                'cost': round(data['cost'], 2),
                'work_items': len(set(data['work_items']))
            }
            for name, data in equipment_agg.items()
        ]

        total_labor = sum(r['cost'] for r in labor_resources)
        total_material = sum(r['cost'] for r in material_resources)
        total_equipment = sum(r['cost'] for r in equipment_resources)

        return BillOfResources(
            project_name=project_name,
            total_labor_cost=round(total_labor, 2),
            total_material_cost=round(total_material, 2),
            total_equipment_cost=round(total_equipment, 2),
            total_cost=round(total_labor + total_material + total_equipment, 2),
            labor_resources=labor_resources,
            material_resources=material_resources,
            equipment_resources=equipment_resources
        )

    def get_resource_composition(self, work_item_code: str) -> Dict[str, float]:
        """Get percentage composition of work item by resource type."""

        breakdown = self.breakdown_work_item(work_item_code)
        if not breakdown or breakdown.total_cost_per_unit == 0:
            return {'labor': 0, 'material': 0, 'equipment': 0}

        total = breakdown.total_cost_per_unit
        return {
            'labor': round(breakdown.labor_cost_per_unit / total * 100, 1),
            'material': round(breakdown.material_cost_per_unit / total * 100, 1),
            'equipment': round(breakdown.equipment_cost_per_unit / total * 100, 1)
        }

    def analyze_labor_intensity(self,
                                 work_items: List[str]) -> pd.DataFrame:
        """Analyze labor intensity of work items."""

        data = []
        for code in work_items:
            breakdown = self.breakdown_work_item(code)
            if breakdown:
                composition = self.get_resource_composition(code)
                labor_components = [c for c in breakdown.components if c.resource_type == ResourceType.LABOR]
                labor_hours = sum(c.quantity_per_unit for c in labor_components)

                data.append({
                    'work_item_code': code,
                    'description': breakdown.work_item_description,
                    'labor_hours_per_unit': labor_hours,
                    'labor_cost_pct': composition['labor'],
                    'material_cost_pct': composition['material'],
                    'equipment_cost_pct': composition['equipment'],
                    'labor_intensive': composition['labor'] > 50
                })

        return pd.DataFrame(data).sort_values('labor_cost_pct', ascending=False)

    def export_breakdown(self,
                         breakdown: WorkItemBreakdown,
                         output_path: str) -> str:
        """Export single work item breakdown."""

        df = pd.DataFrame([
            {
                'Resource Code': c.resource_code,
                'Type': c.resource_type.value,
                'Description': c.description,
                'Unit': c.unit,
                'Quantity/Unit': c.quantity_per_unit,
                'Rate': c.unit_rate,
                'Cost/Unit': c.cost_per_unit
            }
            for c in breakdown.components
        ])

        df.to_excel(output_path, index=False)
        return output_path

    def export_bill_of_resources(self,
                                  bill: BillOfResources,
                                  output_path: str) -> str:
        """Export bill of resources to Excel."""

        with pd.ExcelWriter(output_path, engine='openpyxl') as writer:
            # Summary
            summary_df = pd.DataFrame([{
                'Project': bill.project_name,
                'Total Labor Cost': bill.total_labor_cost,
                'Total Material Cost': bill.total_material_cost,
                'Total Equipment Cost': bill.total_equipment_cost,
                'Grand Total': bill.total_cost
            }])
            summary_df.to_excel(writer, sheet_name='Summary', index=False)

            # Labor
            labor_df = pd.DataFrame(bill.labor_resources)
            labor_df.to_excel(writer, sheet_name='Labor', index=False)

            # Materials
            material_df = pd.DataFrame(bill.material_resources)
            material_df.to_excel(writer, sheet_name='Materials', index=False)

            # Equipment
            equipment_df = pd.DataFrame(bill.equipment_resources)
            equipment_df.to_excel(writer, sheet_name='Equipment', index=False)

        return output_path


class ResourceAggregator:
    """Aggregate resources across work items."""

    def __init__(self, breakdown_tool: CWICRWorkBreakdown):
        self.breakdown = breakdown_tool

    def aggregate_by_trade(self,
                           items: List[Dict[str, Any]]) -> Dict[str, Dict[str, float]]:
        """Aggregate resources by trade/category."""

        by_trade = defaultdict(lambda: {'labor_hours': 0, 'labor_cost': 0, 'items': 0})

        for item in items:
            code = item.get('work_item_code', item.get('code'))
            qty = item.get('quantity', 0)

            # Extract trade from code prefix
            trade = code.split('-')[0] if '-' in code else 'General'

            breakdown = self.breakdown.breakdown_work_item(code)
            if breakdown:
                by_trade[trade]['labor_hours'] += breakdown.labor_cost_per_unit / 35 * qty  # Estimate hours
                by_trade[trade]['labor_cost'] += breakdown.labor_cost_per_unit * qty
                by_trade[trade]['items'] += 1

        return dict(by_trade)

    def identify_critical_resources(self,
                                     bill: BillOfResources,
                                     threshold_pct: float = 10) -> Dict[str, List[Dict]]:
        """Identify resources that contribute significantly to cost."""

        critical = {
            'labor': [],
            'material': [],
            'equipment': []
        }

        # Labor
        for r in bill.labor_resources:
            if bill.total_labor_cost > 0:
                pct = r['cost'] / bill.total_labor_cost * 100
                if pct >= threshold_pct:
                    critical['labor'].append({**r, 'percentage': round(pct, 1)})

        # Materials
        for r in bill.material_resources:
            if bill.total_material_cost > 0:
                pct = r['cost'] / bill.total_material_cost * 100
                if pct >= threshold_pct:
                    critical['material'].append({**r, 'percentage': round(pct, 1)})

        # Equipment
        for r in bill.equipment_resources:
            if bill.total_equipment_cost > 0:
                pct = r['cost'] / bill.total_equipment_cost * 100
                if pct >= threshold_pct:
                    critical['equipment'].append({**r, 'percentage': round(pct, 1)})

        return critical

Read the full file on GitHub · 469 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 13d ago First seen · 469 lines · 34 tokens per session scan A cbd91d7be357

Subscribe to this mod's changes

cwicr-work-breakdown is a skill published in the GitHub repository datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction (310 stars, last pushed 21d ago), licensed MIT. It adds 34 tokens to every session and 3,747 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.