Token导航 LogoToken导航

Agent Skill · 开发

schedule-cost-link(计划成本链接)

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。

schedule-cost-link 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为权限未标注;许可证信息还不明确,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 18,175。

总安装 353周安装 15GitHub Stars 111下载 124核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

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。

来源仓库内路径:skills/schedule-cost-link

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/datadrivenconstruction/ddc_skills_for_ai_agent…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    权限没有明确标注,第一次使用时只给一个无关紧要的任务,观察它到底读了哪些文件和网络。

常见问题

6 条

schedule-cost-link 怎么安装?

在终端执行 npx skills add https://github.com/datadrivenconstruction/ddc_skills_for_ai_agents_in_const…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

schedule-cost-link 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

schedule-cost-link 需要什么权限?

权限级别没有明确标注。第一次使用时建议只给无关紧要的任务,观察它实际读写了哪些内容。

schedule-cost-link 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

schedule-cost-link 用的人多吗?

公开数据是累计安装 353 次,近一周安装 15 次,下载 124 次,GitHub 111 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

schedule-cost-link 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
schedule-cost-link

计划成本链接 · 本页

353111权限未标注未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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

平台分布

Codex

33.07%
按下载量换算41

Claude

30.72%
按下载量换算38

Cursor

20.25%
按下载量换算25

Gemini CLI

9.69%
按下载量换算12

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

权限未标注

当前来源未能明确判断权限范围,默认进入异常复核队列。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills