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Agent Skill · 研究检索

cwicr-material-substitution(CWICR 材料替代)

cwicr-material-substitution 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

cwicr-material-substitution 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 62,001。

总安装 343周安装 14GitHub Stars 111下载 111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:cwicr-material-substitution(CWICR 材料替代)
来源仓库:https://github.com/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction
仓库路径:skills/cwicr-material-substitution
安装命令:
npx skills add https://github.com/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction --skill cwicr-material-substitution
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 cwicr-material-substitution

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

CWICR 材料替代方案提供功能等效的备选材料及其成本性能对比。适用于供应链中断应对、成本节约与规范合规性验证。支持快速搜索与替代可行性分析,加速决策流程。需评估替代材料对工期与安全的影响,并取得设计方认可。

cwicr-material-substitution 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/cwicr-material-substitution

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

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

cwicr-material-substitution 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。

cwicr-material-substitution 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。

cwicr-material-substitution 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

cwicr-material-substitution 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。

cwicr-material-substitution 用的人多吗?

公开数据是累计安装 343 次,近一周安装 14 次,下载 111 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。

cwicr-material-substitution 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。
  • 需要处理研究检索类任务、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。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
cwicr-material-substitution

CWICR 材料替代 · 本页

343111需要联网未明确通过

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

CWICR Material Substitution

Business Case

Problem Statement

Material substitution challenges:

  • Supply chain issues
  • Cost optimization
  • Specification compliance
  • Equivalent performance

Solution

Systematic material substitution using CWICR data to find functionally equivalent alternatives with cost and performance analysis.

Business Value

  • Supply flexibility - Alternative sources
  • Cost savings - Lower-cost equivalents
  • Compliance - Specification matching
  • Quick decisions - Rapid alternative search

Technical Implementation

import pandas as pd
import numpy as np
from typing import Dict, Any, List, Optional, Tuple
from dataclasses import dataclass
from enum import Enum
from difflib import SequenceMatcher

class SubstitutionType(Enum):
    """Types of substitution."""
    DIRECT = "direct"        # Drop-in replacement
    EQUIVALENT = "equivalent"  # Same function, different material
    UPGRADE = "upgrade"      # Better performance
    DOWNGRADE = "downgrade"  # Lower performance (cost saving)

class CompatibilityLevel(Enum):
    """Compatibility levels."""
    EXACT = "exact"          # Identical specs
    HIGH = "high"            # Minor differences
    MEDIUM = "medium"        # Requires review
    LOW = "low"              # Significant differences

@dataclass
class MaterialSubstitute:
    """Material substitution option."""
    original_code: str
    original_description: str
    substitute_code: str
    substitute_description: str
    substitution_type: SubstitutionType
    compatibility: CompatibilityLevel
    original_cost: float
    substitute_cost: float
    cost_difference: float
    cost_difference_pct: float
    notes: str

# Material compatibility groups
MATERIAL_GROUPS = {
    'concrete': ['cement', 'beton', 'concrete', 'C20', 'C25', 'C30', 'C35', 'C40'],
    'steel': ['steel', 'rebar', 'reinforcement', 'S235', 'S275', 'S355'],
    'lumber': ['wood', 'timber', 'lumber', 'plywood', 'OSB'],
    'masonry': ['brick', 'block', 'CMU', 'masonry'],
    'insulation': ['insulation', 'rockwool', 'glasswool', 'EPS', 'XPS', 'PIR'],
    'pipe': ['pipe', 'PVC', 'HDPE', 'copper', 'steel pipe'],
    'electrical': ['wire', 'cable', 'conduit'],
    'finishing': ['paint', 'plaster', 'drywall', 'gypsum'],
    'flooring': ['tile', 'vinyl', 'laminate', 'carpet', 'hardwood'],
    'roofing': ['shingle', 'membrane', 'metal roof', 'tile roof']
}

class CWICRMaterialSubstitution:
    """Find material substitutions using CWICR data."""

    def __init__(self, cwicr_data: pd.DataFrame):
        self.materials = cwicr_data
        self._index_data()

    def _index_data(self):
        """Index material data."""
        if 'work_item_code' in self.materials.columns:
            self._code_index = self.materials.set_index('work_item_code')
        elif 'material_code' in self.materials.columns:
            self._code_index = self.materials.set_index('material_code')
        else:
            self._code_index = None

    def _similarity(self, a: str, b: str) -> float:
        """Calculate string similarity."""
        return SequenceMatcher(None, a.lower(), b.lower()).ratio()

    def _get_material_group(self, description: str) -> Optional[str]:
        """Identify material group from description."""
        desc_lower = description.lower()

        for group, keywords in MATERIAL_GROUPS.items():
            if any(kw.lower() in desc_lower for kw in keywords):
                return group

        return None

    def _get_cost(self, code: str) -> Tuple[float, str]:
        """Get material cost."""
        if self._code_index is None or code not in self._code_index.index:
            return (0, 'unit')

        item = self._code_index.loc[code]
        cost = float(item.get('material_cost', item.get('total_cost', 0)) or 0)
        unit = str(item.get('unit', 'unit'))

        return (cost, unit)

    def find_substitutes(self,
                          material_code: str,
                          max_results: int = 10,
                          max_cost_increase: float = 0.20,
                          include_upgrades: bool = True) -> List[MaterialSubstitute]:
        """Find substitute materials."""

        if self._code_index is None or material_code not in self._code_index.index:
            return []

        original = self._code_index.loc[material_code]
        original_desc = str(original.get('description', material_code))
        original_cost, original_unit = self._get_cost(material_code)

        group = self._get_material_group(original_desc)

        substitutes = []

        for code, row in self._code_index.iterrows():
            if code == material_code:
                continue

            sub_desc = str(row.get('description', code))
            sub_group = self._get_material_group(sub_desc)

            # Check if same group or similar description
            if group and sub_group == group:
                similarity = 0.7
            else:
                similarity = self._similarity(original_desc, sub_desc)

            if similarity < 0.3:
                continue

            sub_cost, sub_unit = self._get_cost(code)

            if sub_unit != original_unit:
                continue

            cost_diff = sub_cost - original_cost
            cost_diff_pct = (cost_diff / original_cost * 100) if original_cost > 0 else 0

            # Filter by cost increase limit
            if not include_upgrades and cost_diff_pct > max_cost_increase * 100:
                continue

            # Determine substitution type
            if cost_diff_pct < -10:
                sub_type = SubstitutionType.DOWNGRADE
            elif cost_diff_pct > 10:
                sub_type = SubstitutionType.UPGRADE
            elif similarity > 0.8:
                sub_type = SubstitutionType.DIRECT
            else:
                sub_type = SubstitutionType.EQUIVALENT

            # Determine compatibility
            if similarity > 0.9:
                compat = CompatibilityLevel.EXACT
            elif similarity > 0.7:
                compat = CompatibilityLevel.HIGH
            elif similarity > 0.5:
                compat = CompatibilityLevel.MEDIUM
            else:
                compat = CompatibilityLevel.LOW

            substitutes.append(MaterialSubstitute(
                original_code=material_code,
                original_description=original_desc,
                substitute_code=code,
                substitute_description=sub_desc,
                substitution_type=sub_type,
                compatibility=compat,
                original_cost=round(original_cost, 2),
                substitute_cost=round(sub_cost, 2),
                cost_difference=round(cost_diff, 2),
                cost_difference_pct=round(cost_diff_pct, 1),
                notes=f"Similarity: {similarity:.0%}"
            ))

        # Sort by compatibility then cost
        substitutes.sort(key=lambda x: (
            list(CompatibilityLevel).index(x.compatibility),
            x.cost_difference
        ))

        return substitutes[:max_results]

    def find_cost_saving_alternatives(self,
                                       material_code: str,
                                       min_savings_pct: float = 5.0) -> List[MaterialSubstitute]:
        """Find lower-cost alternatives."""

        subs = self.find_substitutes(material_code, max_results=20)

        cost_saving = [
            s for s in subs
            if s.cost_difference_pct <= -min_savings_pct
        ]

        return sorted(cost_saving, key=lambda x: x.cost_difference)

    def find_by_group(self,
                       group_name: str,
                       max_results: int = 20) -> List[Dict[str, Any]]:
        """Find all materials in a group."""

        if self._code_index is None:
            return []

        results = []

        for code, row in self._code_index.iterrows():
            desc = str(row.get('description', code))
            item_group = self._get_material_group(desc)

            if item_group == group_name.lower():
                cost, unit = self._get_cost(code)
                results.append({
                    'code': code,
                    'description': desc,
                    'cost': cost,
                    'unit': unit,
                    'group': item_group
                })

        return sorted(results, key=lambda x: x['cost'])[:max_results]

    def substitution_impact(self,
                            original_code: str,
                            substitute_code: str,
                            quantity: float) -> Dict[str, Any]:
        """Calculate impact of substitution."""

        original_cost, _ = self._get_cost(original_code)
        substitute_cost, _ = self._get_cost(substitute_code)

        original_total = original_cost * quantity
        substitute_total = substitute_cost * quantity
        impact = substitute_total - original_total

        return {
            'original_code': original_code,
            'substitute_code': substitute_code,
            'quantity': quantity,
            'original_unit_cost': original_cost,
            'substitute_unit_cost': substitute_cost,
            'original_total': round(original_total, 2),
            'substitute_total': round(substitute_total, 2),
            'cost_impact': round(impact, 2),
            'impact_percent': round(impact / original_total * 100, 1) if original_total > 0 else 0
        }

    def batch_substitution(self,
                            materials: List[Dict[str, Any]]) -> Dict[str, Any]:
        """Find substitutions for multiple materials."""

        results = []
        total_original = 0
        total_potential_savings = 0

        for mat in materials:
            code = mat.get('material_code', mat.get('code'))
            qty = mat.get('quantity', 1)

            subs = self.find_cost_saving_alternatives(code)

            original_cost, _ = self._get_cost(code)
            original_total = original_cost * qty
            total_original += original_total

            best_sub = subs[0] if subs else None
            potential_savings = 0

            if best_sub:
                impact = self.substitution_impact(code, best_sub.substitute_code, qty)
                potential_savings = abs(impact['cost_impact']) if impact['cost_impact'] < 0 else 0
                total_potential_savings += potential_savings

            results.append({
                'code': code,
                'quantity': qty,
                'original_total': round(original_total, 2),
                'best_substitute': best_sub.substitute_code if best_sub else None,
                'potential_savings': round(potential_savings, 2),
                'alternatives_count': len(subs)
            })

        return {
            'materials': results,
            'total_original_cost': round(total_original, 2),
            'total_potential_savings': round(total_potential_savings, 2),
            'savings_percent': round(total_potential_savings / total_original * 100, 1) if total_original > 0 else 0
        }

    def export_substitution_report(self,
                                    substitutes: List[MaterialSubstitute],
                                    output_path: str) -> str:
        """Export substitution report to Excel."""

        with pd.ExcelWriter(output_path, engine='openpyxl') as writer:
            df = pd.DataFrame([
                {
                    'Original Code': s.original_code,
                    'Original Description': s.original_description,
                    'Substitute Code': s.substitute_code,
                    'Substitute Description': s.substitute_description,
                    'Type': s.substitution_type.value,
                    'Compatibility': s.compatibility.value,
                    'Original Cost': s.original_cost,
                    'Substitute Cost': s.substitute_cost,
                    'Cost Difference': s.cost_difference,
                    'Difference %': s.cost_difference_pct,
                    'Notes': s.notes
                }
                for s in substitutes
            ])
            df.to_excel(writer, sheet_name='Substitutes', index=False)

        return output_path

Quick Start

# Load CWICR data
cwicr = pd.read_parquet("ddc_cwicr_en.parquet")

# Initialize substitution finder
sub_finder = CWICRMaterialSubstitution(cwicr)

# Find substitutes
substitutes = sub_finder.find_substitutes("CONC-C30-001")

for sub in substitutes[:5]:
    print(f"{sub.substitute_code}: ${sub.cost_difference:+.2f} ({sub.cost_difference_pct:+.1f}%)")

Common Use Cases

1. Cost Saving Alternatives

savings = sub_finder.find_cost_saving_alternatives("STEEL-S355", min_savings_pct=10)
for s in savings:
    print(f"{s.substitute_code}: Save ${abs(s.cost_difference):.2f}/unit")

2. Batch Analysis

materials = [
    {'code': 'CONC-001', 'quantity': 200},
    {'code': 'STEEL-002', 'quantity': 5000},
    {'code': 'BRICK-003', 'quantity': 10000}
]

batch = sub_finder.batch_substitution(materials)
print(f"Potential Savings: ${batch['total_potential_savings']:,.2f}")

3. Material Group Search

concrete_options = sub_finder.find_by_group('concrete')
for opt in concrete_options[:5]:
    print(f"{opt['code']}: ${opt['cost']:.2f}/{opt['unit']}")

Resources

平台分布

Codex

34.51%
按下载量换算38

Claude

29.89%
按下载量换算33

Cursor

17.52%
按下载量换算19

Gemini CLI

8.7%
按下载量换算10

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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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