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open-construction-estimate

Access and utilize open construction pricing databases. Match BIM elements to standardized work items, calculate costs using public unit price databases with 55,000+ work items.

datadrivenconstruction0 来源安装数☆ 0 仓库 Stars

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。

SkillHub CLI

skillhub install datadrivenconstruction/open-construction-estimate

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技能说明

Open Construction Estimate

Overview

This skill leverages open construction pricing databases for automated cost estimation. Match project elements to standardized work items and calculate costs using publicly available unit prices.

Data Sources:

  • OpenConstructionEstimate (55,000+ work items)
  • RSMeans Online (subscription)
  • Government pricing databases
  • Regional cost indexes

"Открытые базы данных расценок содержат более 55,000 позиций работ, что позволяет автоматизировать сметные расчеты для большинства проектов." — DDC LinkedIn

Quick Start

import pandas as pd
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.metrics.pairwise import cosine_similarity

# Load work items database
work_items = pd.read_csv("open_construction_estimate.csv")
print(f"Loaded {len(work_items)} work items")

# Simple matching function
vectorizer = TfidfVectorizer(ngram_range=(1, 2))
item_vectors = vectorizer.fit_transform(work_items['description'])

def find_matching_items(query, top_n=5):
    query_vec = vectorizer.transform([query])
    similarities = cosine_similarity(query_vec, item_vectors)[0]
    top_indices = similarities.argsort()[-top_n:][::-1]

    return work_items.iloc[top_indices][['code', 'description', 'unit', 'unit_price']]

# Find matches
matches = find_matching_items("reinforced concrete wall 300mm")
print(matches)

Open Database Structure

Database Schema
# Standard work items database structure
WORK_ITEMS_SCHEMA = {
    'code': 'Work item code (e.g., 03.31.13.13)',
    'description': 'Full description of work',
    'short_description': 'Abbreviated description',
    'unit': 'Unit of measure (m³, m², ton, pcs)',
    'unit_price': 'Base unit price',
    'labor_cost': 'Labor component per unit',
    'material_cost': 'Material component per unit',
    'equipment_cost': 'Equipment component per unit',
    'labor_hours': 'Labor hours per unit',...

来源信息

Source
github
Repository
openclaw/skills
Path
skills/datadrivenconstruction/open-construction-estimate
Version
—
Commit
e4e062379b49ba8958ba3fd6e487abd809e1f79e
分类来源
rules
状态
active
可见性
public

这些信息来自收录时的来源分析,可能滞后;使用前请核对最新来源文件。

来源内容

SKILL.md
# Open Construction Estimate

## Overview

This skill leverages open construction pricing databases for automated cost estimation. Match project elements to standardized work items and calculate costs using publicly available unit prices.

**Data Sources:**
- OpenConstructionEstimate (55,000+ work items)
- RSMeans Online (subscription)
- Government pricing databases
- Regional cost indexes

> "Открытые базы данных расценок содержат более 55,000 позиций работ, что позволяет автоматизировать сметные расчеты для большинства проектов."
> — DDC LinkedIn

## Quick Start

```python
import pandas as pd
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.metrics.pairwise import cosine_similarity

# Load work items database
work_items = pd.read_csv("open_construction_estimate.csv")
print(f"Loaded {len(work_items)} work items")

# Simple matching function
vectorizer = TfidfVectorizer(ngram_range=(1, 2))
item_vectors = vectorizer.fit_transform(work_items['description'])

def find_matching_items(query, top_n=5):
    query_vec = vectorizer.transform([query])
    similarities = cosine_similarity(query_vec, item_vectors)[0]
    top_indices = similarities.argsort()[-top_n:][::-1]

    return work_items.iloc[top_indices][['code', 'description', 'unit', 'unit_price']]

# Find matches
matches = find_matching_items("reinforced concrete wall 300mm")
print(matches)
```

## Open Database Structure

### Database Schema

```python
# Standard work items database structure
WORK_ITEMS_SCHEMA = {
    'code': 'Work item code (e.g., 03.31.13.13)',
    'description': 'Full description of work',
    'short_description': 'Abbreviated description',
    'unit': 'Unit of measure (m³, m², ton, pcs)',
    'unit_price': 'Base unit price',
    'labor_cost': 'Labor component per unit',
    'material_cost': 'Material component per unit',
    'equipment_cost': 'Equipment component per unit',
    'labor_hours': 'Labor hours per unit',...

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