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schedule-cost-link

Link schedule activities to cost items. Create cost-loaded schedules, generate cash flow curves, and track earned value.

Install / Use

npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill schedule-cost-link

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

91/100

Supported Platforms

Universal

Our assessment of schedule-cost-link

schedule-cost-link scores 91/100 on our quality scale, 1298th of 4,601 Development & Engineering skills we index (top 29%).

Its SKILL.md is 14 KB long, well organised into 16 sections with 5 code examples: a thorough specification that gives an agent plenty to work with.

It has 333 GitHub stars, a meaningful sign that others use it.

Substance
30/30
Structure
20/20
Description
15/15
Adoption
11/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated about 2 months ago, so schedule-cost-link is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

schedule-cost-link compared with similar skills

All 4 of these similar skills score higher than schedule-cost-link; compare them before choosing.

SkillScoreStarsUpdatedFormat
schedule-cost-link (this skill)by datadrivenconstruction9133356d agoSKILL.md
Agent-Reachby Panniantong10098.3k2d agoCLAUDE.md
taste-skillby Leonxlnx10098.1k2d agoCLAUDE.md
headroomby headroomlabs-ai10075.5ktodayCLAUDE.md
ai-job-searchby MadsLorentzen10048.8k1d agoCLAUDE.md

Frequently asked questions

How do I install schedule-cost-link?
Run npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill schedule-cost-link. The install tabs above show the steps for each supported agent.
Which AI agents does schedule-cost-link work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is schedule-cost-link safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is schedule-cost-link still maintained?
The repository was last updated about 2 months ago, so schedule-cost-link is actively maintained.

name: "schedule-cost-link" description: "Link schedule activities to cost items. Create cost-loaded schedules, generate cash flow curves, and track earned value." homepage: "https://datadrivenconstruction.io" metadata: {"openclaw": {"emoji": "📅", "os": ["darwin", "linux", "win32"], "homepage": "https://datadrivenconstruction.io", "requires": {"bins": ["python3"]}}}

Schedule-Cost Linker

Business Case

Problem Statement

Integrating schedule and cost requires:

  • Linking activities to budget items
  • Creating cost-loaded schedules
  • Generating cash flow forecasts
  • Tracking earned value metrics

Solution

Systematic linkage between schedule activities and cost data to enable integrated project control.

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 date, timedelta
from enum import Enum
from collections import defaultdict


class LoadingMethod(Enum):
    UNIFORM = "uniform"          # Even distribution
    FRONT_LOADED = "front_loaded"
    BACK_LOADED = "back_loaded"
    BELL_CURVE = "bell_curve"


@dataclass
class ScheduleActivity:
    activity_id: str
    name: str
    start_date: date
    finish_date: date
    duration: int
    percent_complete: float = 0


@dataclass
class CostItem:
    cost_code: str
    description: str
    budgeted_cost: float
    labor_cost: float
    material_cost: float
    equipment_cost: float


@dataclass
class ActivityCostLink:
    activity_id: str
    cost_code: str
    budgeted_cost: float
    loading_method: LoadingMethod


@dataclass
class EarnedValueMetrics:
    data_date: date
    bcws: float  # Budgeted Cost of Work Scheduled (PV)
    bcwp: float  # Budgeted Cost of Work Performed (EV)
    acwp: float  # Actual Cost of Work Performed (AC)
    sv: float    # Schedule Variance
    cv: float    # Cost Variance
    spi: float   # Schedule Performance Index
    cpi: float   # Cost Performance Index
    eac: float   # Estimate at Completion
    etc: float   # Estimate to Complete
    vac: float   # Variance at Completion


class ScheduleCostLinker:
    """Link schedule activities to cost items."""

    def __init__(self, project_name: str, budget_at_completion: float):
        self.project_name = project_name
        self.bac = budget_at_completion
        self.activities: Dict[str, ScheduleActivity] = {}
        self.cost_items: Dict[str, CostItem] = {}
        self.links: List[ActivityCostLink] = []
        self.actual_costs: Dict[str, float] = {}  # activity_id -> actual cost

    def add_activity(self,
                     activity_id: str,
                     name: str,
                     start_date: date,
                     finish_date: date,
                     percent_complete: float = 0):
        """Add schedule activity."""

        duration = (finish_date - start_date).days + 1

        self.activities[activity_id] = ScheduleActivity(
            activity_id=activity_id,
            name=name,
            start_date=start_date,
            finish_date=finish_date,
            duration=duration,
            percent_complete=percent_complete
        )

    def add_cost_item(self,
                      cost_code: str,
                      description: str,
                      budgeted_cost: float,
                      labor_pct: float = 0.4,
                      material_pct: float = 0.5,
                      equipment_pct: float = 0.1):
        """Add cost item."""

        self.cost_items[cost_code] = CostItem(
            cost_code=cost_code,
            description=description,
            budgeted_cost=budgeted_cost,
            labor_cost=budgeted_cost * labor_pct,
            material_cost=budgeted_cost * material_pct,
            equipment_cost=budgeted_cost * equipment_pct
        )

    def link_activity_cost(self,
                           activity_id: str,
                           cost_code: str,
                           loading_method: LoadingMethod = LoadingMethod.UNIFORM):
        """Link activity to cost item."""

        if activity_id not in self.activities:
            return

        cost_item = self.cost_items.get(cost_code)
        budgeted = cost_item.budgeted_cost if cost_item else 0

        self.links.append(ActivityCostLink(
            activity_id=activity_id,
            cost_code=cost_code,
            budgeted_cost=budgeted,
            loading_method=loading_method
        ))

    def record_actual_cost(self, activity_id: str, actual_cost: float):
        """Record actual cost for activity."""
        self.actual_costs[activity_id] = actual_cost

    def _distribute_cost(self,
                          cost: float,
                          start_date: date,
                          duration: int,
                          method: LoadingMethod) -> Dict[date, float]:
        """Distribute cost over activity duration."""

        daily_costs = {}

        if duration <= 0:
            return {start_date: cost}

        if method == LoadingMethod.UNIFORM:
            daily = cost / duration
            for i in range(duration):
                daily_costs[start_date + timedelta(days=i)] = daily

        elif method == LoadingMethod.FRONT_LOADED:
            total_weight = sum(range(duration, 0, -1))
            for i in range(duration):
                weight = (duration - i) / total_weight
                daily_costs[start_date + timedelta(days=i)] = cost * weight

        elif method == LoadingMethod.BACK_LOADED:
            total_weight = sum(range(1, duration + 1))
            for i in range(duration):
                weight = (i + 1) / total_weight
                daily_costs[start_date + timedelta(days=i)] = cost * weight

        elif method == LoadingMethod.BELL_CURVE:
            # Simplified bell curve
            mid = duration / 2
            for i in range(duration):
                distance = abs(i - mid)
                weight = 1 - (distance / mid) * 0.5
                daily_costs[start_date + timedelta(days=i)] = cost * weight / duration

        return daily_costs

    def generate_cost_loaded_schedule(self) -> pd.DataFrame:
        """Generate cost-loaded schedule."""

        data = []

        for link in self.links:
            activity = self.activities.get(link.activity_id)
            cost_item = self.cost_items.get(link.cost_code)

            if activity and cost_item:
                data.append({
                    'Activity ID': activity.activity_id,
                    'Activity Name': activity.name,
                    'Cost Code': link.cost_code,
                    'Description': cost_item.description,
                    'Start': activity.start_date,
                    'Finish': activity.finish_date,
                    'Duration': activity.duration,
                    'Budget': link.budgeted_cost,
                    '% Complete': activity.percent_complete,
                    'Earned Value': link.budgeted_cost * activity.percent_complete / 100,
                    'Loading': link.loading_method.value
                })

        return pd.DataFrame(data)

    def generate_cash_flow(self,
                           project_start: date = None,
                           project_end: date = None) -> pd.DataFrame:
        """Generate cash flow curve."""

        if not self.links:
            return pd.DataFrame()

        # Get date range
        if project_start is None:
            project_start = min(self.activities[l.activity_id].start_date for l in self.links)
        if project_end is None:
            project_end = max(self.activities[l.activity_id].finish_date for l in self.links)

        # Aggregate daily costs
        daily_totals = defaultdict(float)

        for link in self.links:
            activity = self.activities.get(link.activity_id)
            if not activity:
                continue

            daily_costs = self._distribute_cost(
                link.budgeted_cost,
                activity.start_date,
                activity.duration,
                link.loading_method
            )

            for day, cost in daily_costs.items():
                daily_totals[day] += cost

        # Build cash flow data
        data = []
        cumulative = 0
        current = project_start

        while current <= project_end:
            daily = daily_totals.get(current, 0)
            cumulative += daily

            data.append({
                'Date': current,
                'Daily': round(daily, 2),
                'Cumulative': round(cumulative, 2),
                'Cumulative %': round(cumulative / self.bac * 100, 1) if self.bac > 0 else 0
            })

            current += timedelta(days=1)

        return pd.DataFrame(data)

    def calculate_earned_value(self, data_date: date) -> EarnedValueMetrics:
        """Calculate earned value metrics at data date."""

        # BCWS - Planned Value through data date
        bcws = 0
        for link in self.links:
            activity = self.activities.get(link.activity_id)
            if not activity:
                continue

            daily_costs = self._distribute_cost(
                link.budgeted_cost,
                activity.start_date,
                activity.duration,
                link.loading_method
            )

            for day, cost in daily_costs.items():
                if day <= data_date:
                    bcws += cost

        # BCWP - Earned Value (budget * % complete)
        bcwp = 0
        for link in self.links:
            activity = self.activities.get(link.activity_id)
            if activity:
                bcwp += link.budgeted_cost * activity.percent_complete / 100

        # ACWP - Actual Cost
        acwp = sum(self.actual_costs.values())

        # Variances
        sv = bcwp - bcws
        cv = bcwp - acwp

        # Indices
        spi = bcwp / bcws if bcws > 0 else 0
        cpi = bcwp / acwp if acwp > 0 else 0

        # Forecasts
        eac = self.bac / cpi if cpi > 0 else self.bac
        etc = eac - acwp
        vac = self.bac - eac

        return EarnedValueMetrics(
            data_date=data_date,
            bcws=round(bcws, 2),
            bcwp=round(bcwp, 2),
            acwp=round(acwp, 2),
            sv=round(sv, 2),
            cv=round(cv, 2),
            spi=round(spi, 2),
            cpi=round(cpi, 2),
            eac=round(eac, 2),
            etc=round(etc, 2),
            vac=round(vac, 2)
        )

    def get_monthly_cash_flow(self) -> pd.DataFrame:
        """Aggregate cash flow by month."""

        daily = self.generate_cash_flow()
        if daily.empty:
            return pd.DataFrame()

        daily['Month'] = pd.to_datetime(daily['Date']).dt.to_period('M')
        monthly = daily.groupby('Month').agg({
            'Daily': 'sum',
            'Cumulative': 'last'
        }).reset_index()

        monthly.columns = ['Month', 'Monthly Cost', 'Cumulative']
        return monthly

    def export_to_excel(self, output_path: str) -> str:
        """Export integrated data to Excel."""

        with pd.ExcelWriter(output_path, engine='openpyxl') as writer:
            # Cost-loaded schedule
            schedule = self.generate_cost_loaded_schedule()
            schedule.to_excel(writer, sheet_name='Cost-Loaded Schedule', index=False)

            # Cash flow
            cash_flow = self.generate_cash_flow()
            if not cash_flow.empty:
                cash_flow.to_excel(writer, sheet_name='Cash Flow', index=False)

            # Monthly
            monthly = self.get_monthly_cash_flow()
            if not monthly.empty:
                monthly.to_excel(writer, sheet_name='Monthly', index=False)

            # Earned Value
            evm = self.calculate_earned_value(date.today())
            evm_df = pd.DataFrame([{
                'Data Date': evm.data_date,
                'BCWS (PV)': evm.bcws,
                'BCWP (EV)': evm.bcwp,

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars333
CategoryDevelopment
Updated1mo ago
Forks82

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions