跳到正文
cccskills
免费在 GitHub 公开

xlsx-construction

Excel/spreadsheet processing for construction: estimates, schedules, tracking logs, quantity takeoffs. Formulas, formatting, analysis.

中文简介正在准备中。当前显示原文说明。

集成工具Excel
查看安装方法

包含的文件(3)

  • SKILL.md7.6 KB
  • claw.json518 B
  • instructions.md1.2 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Excel Processing for Construction

Overview

Adapted from Anthropic's XLSX skill for construction spreadsheet workflows.

Construction Use Cases

1. Cost Estimate Template

from openpyxl import Workbook
from openpyxl.styles import Font, Alignment, Border, Side, PatternFill
from openpyxl.utils import get_column_letter

def create_estimate_template(output_path: str, project_name: str):
    """Create construction cost estimate template."""
    wb = Workbook()
    ws = wb.active
    ws.title = "Cost Estimate"

    # Styles
    header_font = Font(bold=True, size=12)
    currency_format = '$#,##0.00'
    thin_border = Border(
        left=Side(style='thin'),
        right=Side(style='thin'),
        top=Side(style='thin'),
        bottom=Side(style='thin')
    )
    header_fill = PatternFill(start_color="4472C4", end_color="4472C4", fill_type="solid")

    # Project header
    ws['A1'] = "CONSTRUCTION COST ESTIMATE"
    ws['A1'].font = Font(bold=True, size=16)
    ws['A2'] = f"Project: {project_name}"
    ws['A3'] = "Date:"
    ws['B3'] = "=TODAY()"

    # Column headers (row 5)
    headers = ['CSI Code', 'Description', 'Quantity', 'Unit', 'Unit Cost',
               'Labor', 'Material', 'Equipment', 'Total']
    for col, header in enumerate(headers, 1):
        cell = ws.cell(row=5, column=col, value=header)
        cell.font = Font(bold=True, color="FFFFFF")
        cell.fill = header_fill
        cell.border = thin_border
        cell.alignment = Alignment(horizontal='center')

    # Set column widths
    widths = [12, 40, 10, 8, 12, 12, 12, 12, 14]
    for i, width in enumerate(widths, 1):
        ws.column_dimensions[get_column_letter(i)].width = width

    # Sample data rows with formulas
    for row in range(6, 26):  # 20 empty rows
        # Total formula: Labor + Material + Equipment
        ws.cell(row=row, column=9,
                value=f"=SUM(F{row}:H{row})")

        # Apply borders
        for col in range(1, 10):
            ws.cell(row=row, column=col).border = thin_border

    # Currency formatting
    for col in [5, 6, 7, 8, 9]:  # Cost columns
        for row in range(6, 26):
            ws.cell(row=row, column=col).number_format = currency_format

    # Subtotals section
    ws['G27'] = "SUBTOTAL"
    ws['I27'] = "=SUM(I6:I25)"
    ws['I27'].number_format = currency_format

    ws['G28'] = "Contingency (10%)"
    ws['I28'] = "=I27*0.10"

    ws['G29'] = "TOTAL"
    ws['I29'] = "=I27+I28"
    ws['I29'].font = Font(bold=True, size=14)

    wb.save(output_path)
    return output_path

2. Schedule Tracker

def create_schedule_tracker(output_path: str, tasks: list):
    """Create construction schedule tracking spreadsheet."""
    wb = Workbook()
    ws = wb.active
    ws.title = "Schedule"

    # Headers
    headers = ['ID', 'Task', 'Start Date', 'End Date', 'Duration',
               'Progress', 'Status', 'Predecessor', 'Notes']

    # Status dropdown options
    from openpyxl.worksheet.datavalidation import DataValidation
    status_dv = DataValidation(
        type="list",
        formula1='"Not Started,In Progress,Complete,On Hold,Delayed"',
        allow_blank=True
    )
    ws.add_data_validation(status_dv)

    # Header row
    for col, header in enumerate(headers, 1):
        cell = ws.cell(row=1, column=col, value=header)
        cell.font = Font(bold=True)

    # Add tasks with formulas
    for i, task in enumerate(tasks, 2):
        ws.cell(row=i, column=1, value=task.get('id', i-1))
        ws.cell(row=i, column=2, value=task.get('name', ''))
        ws.cell(row=i, column=3, value=task.get('start', ''))
        ws.cell(row=i, column=4, value=task.get('end', ''))

        # Duration formula
        ws.cell(row=i, column=5, value=f"=D{i}-C{i}")

        # Progress bar (0-100%)
        ws.cell(row=i, column=6, value=task.get('progress', 0))
        ws.cell(row=i, column=6).number_format = '0%'

        # Status with validation
        status_cell = ws.cell(row=i, column=7, value=task.get('status', 'Not Started'))
        status_dv.add(status_cell)

    wb.save(output_path)
    return output_path

3. RFI Log Template

def create_rfi_log(output_path: str):
    """Create RFI tracking log."""
    wb = Workbook()
    ws = wb.active
    ws.title = "RFI Log"

    headers = [
        'RFI #', 'Date Submitted', 'Subject', 'Spec Section',
        'Drawing Ref', 'Submitted By', 'Assigned To',
        'Response Due', 'Date Responded', 'Status', 'Days Open'
    ]

    for col, header in enumerate(headers, 1):
        ws.cell(row=1, column=col, value=header)

    # Days Open formula (in column K)
    for row in range(2, 100):
        ws.cell(row=row, column=11,
                value=f'=IF(I{row}="",TODAY()-B{row},I{row}-B{row})')

    # Conditional formatting for overdue items
    from openpyxl.formatting.rule import FormulaRule
    from openpyxl.styles import PatternFill

    red_fill = PatternFill(bgColor="FFC7CE")
    ws.conditional_formatting.add(
        'K2:K100',
        FormulaRule(formula=['K2>7'], fill=red_fill)
    )

    wb.save(output_path)
    return output_path

4. Quantity Takeoff Processing

import pandas as pd

def process_qto_from_bim(bim_xlsx: str, output_path: str):
    """Process BIM export for quantity takeoff."""
    # Read BIM export
    df = pd.read_excel(bim_xlsx)

    # Group by category and type
    qto = df.groupby(['Category', 'Type']).agg({
        'Volume': 'sum',
        'Area': 'sum',
        'Length': 'sum',
        'Count': 'count'
    }).reset_index()

    # Rename columns for clarity
    qto.columns = ['Category', 'Type', 'Total Volume (m³)',
                   'Total Area (m²)', 'Total Length (m)', 'Element Count']

    # Create workbook with formatting
    with pd.ExcelWriter(output_path, engine='openpyxl') as writer:
        qto.to_excel(writer, sheet_name='QTO Summary', index=False)

        # Get workbook to apply formatting
        wb = writer.book
        ws = wb['QTO Summary']

        # Format numeric columns
        for col in ['C', 'D', 'E']:
            for row in range(2, len(qto) + 2):
                ws[f'{col}{row}'].number_format = '#,##0.00'

    return output_path

Best Practices for Construction Spreadsheets

Color Coding (Industry Standard)

  • Blue text: Input values (quantities, rates)
  • Black text: Formulas and calculations
  • Green text: Links from other sheets
  • Yellow highlight: Assumptions to verify

Formula Guidelines

  1. Never hardcode values in formulas
  2. Create separate assumption cells
  3. Use named ranges for clarity
  4. Include unit checks

Error Prevention

# Add error handling to formulas
formula_with_error_check = "=IFERROR(B5/C5, 0)"

Integration with DDC

# Convert BIM export to estimate
from ddc_toolkit import RevitExporter, CWICRSemanticSearch

# Export BIM data
exporter = RevitExporter()
bim_data = exporter.read_elements("project.xlsx")

# Process QTO
qto = process_qto_from_bim("project.xlsx", "qto_output.xlsx")

# Match to cost database
search = CWICRSemanticSearch()
for category in bim_data['Category'].unique():
    prices = search.search_work_items(category)
    # Apply prices to QTO...

Dependencies

pip install openpyxl pandas xlrd

Resources

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

Create 4D construction simulations by linking BIM elements to project schedules. Generate time-based visualizations, sequence analysis, and construction phasing with Gantt integration.

中文简介正在准备中。当前显示原文说明。

datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction3632026年10月20日 更新

Analyze 5000+ IFC and Revit projects at scale for patterns, benchmarks, and insights. Big data analysis for construction.

中文简介正在准备中。当前显示原文说明。

datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction3632026年10月20日 更新

Check construction AI systems against the EU AI Act (Regulation 2024/1689): classify risk of estimation, scheduling, CV and agent tools, document transparency, keep human oversight. Use when deploying or auditing AI in construction.

中文简介正在准备中。当前显示原文说明。

datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction3632026年10月20日 更新

Orchestrate multiple AI agents for construction workflows: estimator, scheduler, document, QA and safety agents coordinated by a supervisor agent, with human checkpoints. Use when automating end-to-end project processes with agentic AI.

中文简介正在准备中。当前显示原文说明。

datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction3632026年10月20日 更新

Create Apache Airflow DAGs for construction data pipelines. Orchestrate ETL, validation, and reporting workflows.

中文简介正在准备中。当前显示原文说明。

datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction3632026年10月20日 更新

Automate as-built documentation and digital handover for construction. Compile project records, generate O&M manuals, create asset databases, and ensure complete project closeout.

中文简介正在准备中。当前显示原文说明。

datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction3632026年10月20日 更新

查看 datadrivenconstruction 的全部技能

报告此技能的问题