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Agent Skill · 待分类

lifecycle-carbon-calculator(生命周期碳计算器)

用于辅助数据整理、表格处理、CSV/Excel 分析、指标计算和图表准备。它适合让 Agent 清洗字段、汇总数据、发现异常、生成统计口径或把分析结果转成可读说明。使用时需要确认数据来源、字段含义和时间范围,避免把样本数据当全量事实;涉及敏感数据、导出文件或批量写回时,应先确认权限和脱敏边界。

lifecycle-carbon-calculator 是待分类类 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,按安装量在待分类类的 11,209 个 Skill 里排第 6,526。

总安装 445周安装 18GitHub Stars 113下载 140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:lifecycle-carbon-calculator(生命周期碳计算器)
来源仓库:https://github.com/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction
仓库路径:skills/lifecycle-carbon-calculator
安装命令:
npx skills add https://github.com/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction --skill lifecycle-carbon-calculator
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 lifecycle-carbon-calculator

这个 Skill 是做什么的

这个 Skill 的分类还没最终确定,用法以来源仓库的说明为准。

计算建材与项目的隐含碳与生命周期碳排放。辅助绿色建筑认证与设计优化决策。支持 LEED、BREEAM 等标准合规检查。材料数据库覆盖主流建材类型。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

lifecycle-carbon-calculator 属于待分类类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/lifecycle-carbon-calculator

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

lifecycle-carbon-calculator 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。

lifecycle-carbon-calculator 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。

lifecycle-carbon-calculator 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。

lifecycle-carbon-calculator 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。

lifecycle-carbon-calculator 用的人多吗?

公开数据是累计安装 445 次,近一周安装 18 次,下载 140 次,GitHub 113 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。

lifecycle-carbon-calculator 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。
  • 需要处理待分类类任务、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。

待分类类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
infsh-cli

infsh CLI · Codex、Claude

4,374,576382权限未标注未明确未收录
ai-video-generation

AI 视频生成 · Codex、Claude

4,313,376382调用外部服务未明确有提醒
lark-openapi-explorer

云雀 OpenAPI 浏览器 · Codex、Claude

2,064,1209,011需要联网未明确有提醒
lark-workflow-standup-report

Lark 工作流程站立报告 · Codex、Claude

2,041,6328,978需要联网未明确通过
use-my-browser

使用我的浏览器 · Codex、Claude

1,848,49140操作浏览器未明确未通过
lifecycle-carbon-calculator

生命周期碳计算器 · 本页

445113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

Lifecycle Carbon Calculator for Construction

Overview

Calculate embodied carbon (EC) and lifecycle carbon emissions for construction materials, assemblies, and projects. Support sustainable design decisions and carbon reduction targets.

Business Case

Carbon calculation supports:

  • Regulatory Compliance: Meet carbon reporting requirements
  • Green Certifications: LEED, BREEAM, Living Building Challenge
  • Design Optimization: Choose lower-carbon alternatives
  • Sustainability Goals: Track progress toward net-zero

Technical Implementation

from dataclasses import dataclass, field
from typing import List, Dict, Any, Optional
from enum import Enum
import pandas as pd

class LifecycleStage(Enum):
    A1_A3 = "Product Stage (A1-A3)"  # Raw materials, transport, manufacturing
    A4 = "Transport to Site (A4)"
    A5 = "Construction (A5)"
    B1_B7 = "Use Stage (B1-B7)"  # Maintenance, repair, replacement
    C1_C4 = "End of Life (C1-C4)"  # Demolition, transport, disposal
    D = "Beyond Lifecycle (D)"  # Reuse, recycling potential

@dataclass
class MaterialCarbon:
    material_id: str
    name: str
    category: str
    unit: str
    carbon_a1_a3: float  # kgCO2e per unit
    carbon_a4: float
    carbon_a5: float
    carbon_b: float
    carbon_c: float
    carbon_d: float  # Usually negative (credit)
    density: float  # kg/m³ if applicable
    source: str
    epd_url: str = ""

@dataclass
class AssemblyCarbon:
    assembly_id: str
    name: str
    materials: List[Dict[str, Any]]
    total_carbon: float
    carbon_by_stage: Dict[str, float]

@dataclass
class ProjectCarbon:
    project_id: str
    name: str
    gross_area: float
    assemblies: List[AssemblyCarbon]
    total_embodied_carbon: float
    carbon_per_area: float
    carbon_by_stage: Dict[str, float]
    carbon_by_category: Dict[str, float]
    benchmark_comparison: Dict[str, Any]

class LifecycleCarbonCalculator:
    """Calculate lifecycle carbon for construction."""

    # Sample material carbon data (kgCO2e per unit)
    DEFAULT_MATERIALS = {
        'concrete_30mpa': MaterialCarbon(
            material_id='C30', name='Concrete 30MPa', category='Concrete',
            unit='m³', carbon_a1_a3=300, carbon_a4=5, carbon_a5=2,
            carbon_b=0, carbon_c=10, carbon_d=-20, density=2400,
            source='EPD Database'
        ),
        'concrete_40mpa': MaterialCarbon(
            material_id='C40', name='Concrete 40MPa', category='Concrete',
            unit='m³', carbon_a1_a3=350, carbon_a4=5, carbon_a5=2,
            carbon_b=0, carbon_c=10, carbon_d=-20, density=2400,
            source='EPD Database'
        ),
        'steel_rebar': MaterialCarbon(
            material_id='REBAR', name='Steel Reinforcing Bar', category='Steel',
            unit='kg', carbon_a1_a3=1.99, carbon_a4=0.05, carbon_a5=0.02,
            carbon_b=0, carbon_c=0.05, carbon_d=-0.5, density=7850,
            source='WorldSteel EPD'
        ),
        'steel_structural': MaterialCarbon(
            material_id='STEEL', name='Structural Steel', category='Steel',
            unit='kg', carbon_a1_a3=1.55, carbon_a4=0.05, carbon_a5=0.03,
            carbon_b=0, carbon_c=0.05, carbon_d=-0.8, density=7850,
            source='AISC EPD'
        ),
        'timber_clt': MaterialCarbon(
            material_id='CLT', name='Cross-Laminated Timber', category='Timber',
            unit='m³', carbon_a1_a3=-500, carbon_a4=10, carbon_a5=5,
            carbon_b=0, carbon_c=50, carbon_d=-100, density=500,
            source='AWC EPD'
        ),
        'gypsum_board': MaterialCarbon(
            material_id='GYP', name='Gypsum Board 12.5mm', category='Finishes',
            unit='m²', carbon_a1_a3=3.2, carbon_a4=0.2, carbon_a5=0.1,
            carbon_b=0, carbon_c=0.3, carbon_d=-0.1, density=10,
            source='EUROGYPSUM EPD'
        ),
        'insulation_mineral': MaterialCarbon(
            material_id='INS_MW', name='Mineral Wool Insulation', category='Insulation',
            unit='m³', carbon_a1_a3=45, carbon_a4=2, carbon_a5=1,
            carbon_b=0, carbon_c=5, carbon_d=-2, density=40,
            source='EURIMA EPD'
        ),
        'glass_double': MaterialCarbon(
            material_id='GLASS', name='Double Glazed Unit', category='Glazing',
            unit='m²', carbon_a1_a3=35, carbon_a4=1, carbon_a5=0.5,
            carbon_b=0, carbon_c=2, carbon_d=-5, density=25,
            source='Glass for Europe EPD'
        ),
        'aluminum': MaterialCarbon(
            material_id='ALU', name='Aluminum Profile', category='Metals',
            unit='kg', carbon_a1_a3=8.0, carbon_a4=0.1, carbon_a5=0.05,
            carbon_b=0, carbon_c=0.1, carbon_d=-4.0, density=2700,
            source='EAA EPD'
        ),
    }

    # Building type benchmarks (kgCO2e/m²)
    BENCHMARKS = {
        'Office': {'typical': 500, 'good': 350, 'best': 200},
        'Residential': {'typical': 400, 'good': 280, 'best': 150},
        'Retail': {'typical': 450, 'good': 320, 'best': 180},
        'Industrial': {'typical': 350, 'good': 250, 'best': 150},
        'Healthcare': {'typical': 700, 'good': 500, 'best': 350},
    }

    def __init__(self):
        self.materials: Dict[str, MaterialCarbon] = dict(self.DEFAULT_MATERIALS)
        self.assemblies: Dict[str, AssemblyCarbon] = {}

    def add_material(self, material: MaterialCarbon):
        """Add or update a material."""
        self.materials[material.material_id] = material

    def calculate_material_carbon(self, material_id: str, quantity: float,
                                   stages: List[LifecycleStage] = None) -> Dict:
        """Calculate carbon for a material quantity."""
        if material_id not in self.materials:
            raise ValueError(f"Unknown material: {material_id}")

        material = self.materials[material_id]

        if stages is None:
            stages = list(LifecycleStage)

        carbon_by_stage = {}
        total = 0

        for stage in stages:
            if stage == LifecycleStage.A1_A3:
                carbon = material.carbon_a1_a3 * quantity
            elif stage == LifecycleStage.A4:
                carbon = material.carbon_a4 * quantity
            elif stage == LifecycleStage.A5:
                carbon = material.carbon_a5 * quantity
            elif stage == LifecycleStage.B1_B7:
                carbon = material.carbon_b * quantity
            elif stage == LifecycleStage.C1_C4:
                carbon = material.carbon_c * quantity
            elif stage == LifecycleStage.D:
                carbon = material.carbon_d * quantity
            else:
                carbon = 0

            carbon_by_stage[stage.value] = carbon
            total += carbon

        return {
            'material_id': material_id,
            'material_name': material.name,
            'quantity': quantity,
            'unit': material.unit,
            'total_carbon': total,
            'carbon_by_stage': carbon_by_stage
        }

    def create_assembly(self, assembly_id: str, name: str,
                        components: List[Dict]) -> AssemblyCarbon:
        """Create an assembly from multiple materials."""
        total_carbon = 0
        carbon_by_stage = {stage.value: 0 for stage in LifecycleStage}
        material_details = []

        for comp in components:
            material_id = comp['material_id']
            quantity = comp['quantity']

            result = self.calculate_material_carbon(material_id, quantity)
            total_carbon += result['total_carbon']

            for stage, carbon in result['carbon_by_stage'].items():
                carbon_by_stage[stage] += carbon

            material_details.append({
                'material': result['material_name'],
                'quantity': quantity,
                'unit': result['unit'],
                'carbon': result['total_carbon']
            })

        assembly = AssemblyCarbon(
            assembly_id=assembly_id,
            name=name,
            materials=material_details,
            total_carbon=total_carbon,
            carbon_by_stage=carbon_by_stage
        )

        self.assemblies[assembly_id] = assembly
        return assembly

    def calculate_project_carbon(self, project_id: str, project_name: str,
                                  gross_area: float, building_type: str,
                                  quantities: List[Dict]) -> ProjectCarbon:
        """Calculate total project carbon."""
        assemblies = []
        total_carbon = 0
        carbon_by_stage = {stage.value: 0 for stage in LifecycleStage}
        carbon_by_category = {}

        for qty in quantities:
            if 'assembly_id' in qty:
                # Use predefined assembly
                if qty['assembly_id'] in self.assemblies:
                    assembly = self.assemblies[qty['assembly_id']]
                    multiplier = qty.get('multiplier', 1)
                    scaled_carbon = assembly.total_carbon * multiplier

                    assemblies.append(AssemblyCarbon(
                        assembly_id=assembly.assembly_id,
                        name=assembly.name,
                        materials=assembly.materials,
                        total_carbon=scaled_carbon,
                        carbon_by_stage={k: v * multiplier for k, v in assembly.carbon_by_stage.items()}
                    ))
                    total_carbon += scaled_carbon

            elif 'material_id' in qty:
                # Direct material
                result = self.calculate_material_carbon(
                    qty['material_id'], qty['quantity']
                )
                total_carbon += result['total_carbon']

                for stage, carbon in result['carbon_by_stage'].items():
                    carbon_by_stage[stage] += carbon

                # Track by category
                material = self.materials[qty['material_id']]
                cat = material.category
                carbon_by_category[cat] = carbon_by_category.get(cat, 0) + result['total_carbon']

        # Calculate metrics
        carbon_per_area = total_carbon / gross_area if gross_area > 0 else 0

        # Compare to benchmarks
        benchmark = self.BENCHMARKS.get(building_type, self.BENCHMARKS['Office'])
        benchmark_comparison = {
            'carbon_per_area': carbon_per_area,
            'typical_benchmark': benchmark['typical'],
            'good_benchmark': benchmark['good'],
            'best_benchmark': benchmark['best'],
            'vs_typical': (carbon_per_area / benchmark['typical'] - 1) * 100,
            'rating': self._get_rating(carbon_per_area, benchmark)
        }

        return ProjectCarbon(
            project_id=project_id,
            name=project_name,
            gross_area=gross_area,
            assemblies=assemblies,
            total_embodied_carbon=total_carbon,
            carbon_per_area=carbon_per_area,
            carbon_by_stage=carbon_by_stage,
            carbon_by_category=carbon_by_category,
            benchmark_comparison=benchmark_comparison
        )

    def _get_rating(self, carbon: float, benchmark: Dict) -> str:
        """Get rating based on benchmark comparison."""
        if carbon <= benchmark['best']:
            return 'A (Best Practice)'
        elif carbon <= benchmark['good']:
            return 'B (Good Practice)'
        elif carbon <= benchmark['typical']:
            return 'C (Typical)'
        else:
            return 'D (Above Typical)'

    def compare_alternatives(self, base_project: ProjectCarbon,
                              alternatives: List[Dict]) -> pd.DataFrame:
        """Compare carbon of design alternatives."""
        comparisons = [{
            'Option': 'Base Design',
            'Total Carbon (tCO2e)': base_project.total_embodied_carbon / 1000,
            'Carbon/m² (kgCO2e)': base_project.carbon_per_area,
            'vs Base': '0%',
            'Rating': base_project.benchmark_comparison['rating']
        }]

        for alt in alternatives:
            project = self.calculate_project_carbon(
                alt['id'], alt['name'], alt['gross_area'],
                alt.get('building_type', 'Office'), alt['quantities']
            )

            change = (project.total_embodied_carbon - base_project.total_embodied_carbon) / base_project.total_embodied_carbon * 100

            comparisons.append({
                'Option': alt['name'],
                'Total Carbon (tCO2e)': project.total_embodied_carbon / 1000,
                'Carbon/m² (kgCO2e)': project.carbon_per_area,
                'vs Base': f'{change:+.1f}%',
                'Rating': project.benchmark_comparison['rating']
            })

        return pd.DataFrame(comparisons)

    def suggest_reductions(self, project: ProjectCarbon) -> List[Dict]:
        """Suggest carbon reduction opportunities."""
        suggestions = []

        # Analyze by category
        if 'Concrete' in project.carbon_by_category:
            concrete_carbon = project.carbon_by_category['Concrete']
            if concrete_carbon > project.total_embodied_carbon * 0.3:
                suggestions.append({
                    'category': 'Concrete',
                    'current_carbon': concrete_carbon,
                    'suggestion': 'Consider low-carbon concrete (GGBS/PFA replacement)',
                    'potential_reduction': '20-40%',
                    'impact': concrete_carbon * 0.3
                })

        if 'Steel' in project.carbon_by_category:
            steel_carbon = project.carbon_by_category['Steel']
            if steel_carbon > project.total_embodied_carbon * 0.2:
                suggestions.append({
                    'category': 'Steel',
                    'current_carbon': steel_carbon,
                    'suggestion': 'Specify high recycled content steel',
                    'potential_reduction': '10-25%',
                    'impact': steel_carbon * 0.2
                })

        # Benchmark-based suggestions
        if project.benchmark_comparison['vs_typical'] > 0:
            suggestions.append({
                'category': 'Overall',
                'current_carbon': project.total_embodied_carbon,
                'suggestion': 'Project exceeds typical benchmark - review high-carbon elements',
                'potential_reduction': f"{abs(project.benchmark_comparison['vs_typical']):.0f}%",
                'impact': project.total_embodied_carbon * abs(project.benchmark_comparison['vs_typical']) / 100
            })

        return sorted(suggestions, key=lambda x: -x['impact'])

    def generate_report(self, project: ProjectCarbon) -> str:
        """Generate carbon assessment report."""
        lines = ["# Embodied Carbon Assessment Report", ""]
        lines.append(f"**Project:** {project.name}")
        lines.append(f"**Gross Area:** {project.gross_area:,.0f} m²")
        lines.append(f"**Assessment Date:** {pd.Timestamp.now().strftime('%Y-%m-%d')}")
        lines.append("")

        # Summary
        lines.append("## Carbon Summary")
        lines.append(f"- **Total Embodied Carbon:** {project.total_embodied_carbon/1000:,.0f} tCO2e")
        lines.append(f"- **Carbon Intensity:** {project.carbon_per_area:,.0f} kgCO2e/m²")
        lines.append(f"- **Rating:** {project.benchmark_comparison['rating']}")
        lines.append("")

        # By lifecycle stage
        lines.append("## Carbon by Lifecycle Stage")
        for stage, carbon in project.carbon_by_stage.items():
            if carbon != 0:
                pct = carbon / project.total_embodied_carbon * 100
                lines.append(f"- {stage}: {carbon/1000:,.1f} tCO2e ({pct:.1f}%)")
        lines.append("")

        # By category
        lines.append("## Carbon by Material Category")
        for cat, carbon in sorted(project.carbon_by_category.items(), key=lambda x: -x[1]):
            pct = carbon / project.total_embodied_carbon * 100
            lines.append(f"- {cat}: {carbon/1000:,.1f} tCO2e ({pct:.1f}%)")
        lines.append("")

        # Benchmark
        lines.append("## Benchmark Comparison")
        bc = project.benchmark_comparison
        lines.append(f"- Project: {bc['carbon_per_area']:.0f} kgCO2e/m²")
        lines.append(f"- Typical: {bc['typical_benchmark']} kgCO2e/m²")
        lines.append(f"- Good Practice: {bc['good_benchmark']} kgCO2e/m²")
        lines.append(f"- Best Practice: {bc['best_benchmark']} kgCO2e/m²")
        lines.append("")

        # Reduction opportunities
        suggestions = self.suggest_reductions(project)
        if suggestions:
            lines.append("## Reduction Opportunities")
            for sug in suggestions[:5]:
                lines.append(f"\n### {sug['category']}")
                lines.append(f"- **Suggestion:** {sug['suggestion']}")
                lines.append(f"- **Potential Reduction:** {sug['potential_reduction']}")
                lines.append(f"- **Impact:** {sug['impact']/1000:,.1f} tCO2e")

        return "\n".join(lines)

Quick Start

# Initialize calculator
calc = LifecycleCarbonCalculator()

# Calculate project carbon
project = calc.calculate_project_carbon(
    project_id="PROJ-001",
    project_name="Office Building",
    gross_area=5000,
    building_type="Office",
    quantities=[
        {'material_id': 'concrete_40mpa', 'quantity': 1500},  # m³
        {'material_id': 'steel_rebar', 'quantity': 150000},   # kg
        {'material_id': 'steel_structural', 'quantity': 200000},
        {'material_id': 'gypsum_board', 'quantity': 8000},    # m²
        {'material_id': 'glass_double', 'quantity': 1200},    # m²
    ]
)

print(f"Total Carbon: {project.total_embodied_carbon/1000:,.0f} tCO2e")
print(f"Carbon Intensity: {project.carbon_per_area:,.0f} kgCO2e/m²")
print(f"Rating: {project.benchmark_comparison['rating']}")

# Get reduction suggestions
suggestions = calc.suggest_reductions(project)
for sug in suggestions:
    print(f"- {sug['category']}: {sug['suggestion']}")

# Generate full report
report = calc.generate_report(project)
print(report)

Dependencies

pip install pandas

平台分布

Codex

34.64%
按下载量换算48

Claude

31.82%
按下载量换算45

Cursor

20.99%
按下载量换算29

Gemini CLI

10.45%
按下载量换算15

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。

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