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schedule-cost-link计划成本链接

Agent Skill

schedule-cost-link 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

353

周安装

15

GitHub Stars

111

下载量

124
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:schedule-cost-link(计划成本链接)
来源仓库:https://github.com/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction
仓库路径:skills/schedule-cost-link
安装命令:
npx skills add https://github.com/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction --skill schedule-cost-link
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction --skill schedule-cost-link

简介

用于关联项目计划与成本估算,形成预算跟踪机制。

  • 适合在财务管控中监控资源投入与进度匹配度。
  • 可输出成本分布图和偏差分析报告。schedule-cost-link 属于开发类 Skill,可作为该场景下的辅助能力补充。
  • 安装方式基于 GitHub,需确保输入包含任务与费用映射。
  • 成本数据应由财务部门提供,避免使用过时信息。

SKILL.md

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,
                'ACWP (AC)': evm.acwp,
                'SV': evm.sv,
                'CV': evm.cv,
                'SPI': evm.spi,
                'CPI': evm.cpi,
                'EAC': evm.eac,
                'ETC': evm.etc,
                'VAC': evm.vac
            }])
            evm_df.to_excel(writer, sheet_name='Earned Value', index=False)

        return output_path

Quick Start

from datetime import date, timedelta

# Initialize linker
linker = ScheduleCostLinker("Office Building", budget_at_completion=5000000)

# Add activities
linker.add_activity("A-001", "Foundation", date(2024, 6, 1), date(2024, 6, 30), percent_complete=100)
linker.add_activity("A-002", "Structure", date(2024, 7, 1), date(2024, 9, 30), percent_complete=60)
linker.add_activity("A-003", "MEP", date(2024, 8, 1), date(2024, 11, 30), percent_complete=30)

# Add cost items
linker.add_cost_item("01-FOUND", "Foundation Work", 500000)
linker.add_cost_item("02-STRUCT", "Structural Work", 2000000)
linker.add_cost_item("03-MEP", "MEP Systems", 1500000)

# Link
linker.link_activity_cost("A-001", "01-FOUND")
linker.link_activity_cost("A-002", "02-STRUCT", LoadingMethod.BELL_CURVE)
linker.link_activity_cost("A-003", "03-MEP", LoadingMethod.BACK_LOADED)

# Record actuals
linker.record_actual_cost("A-001", 520000)
linker.record_actual_cost("A-002", 1300000)

Common Use Cases

1. Earned Value Analysis

evm = linker.calculate_earned_value(date.today())
print(f"CPI: {evm.cpi}")
print(f"SPI: {evm.spi}")
print(f"EAC: ${evm.eac:,.2f}")

2. Cash Flow Forecast

cash_flow = linker.generate_cash_flow()
print(cash_flow.tail(10))

3. Monthly Breakdown

monthly = linker.get_monthly_cash_flow()
print(monthly)

Resources

  • DDC Book: Chapter 4.2 - Schedule-Cost Integration

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

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