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Cwicr Report Generator

Community
datadrivenconstruction
cwicr-report-generator

Generate professional cost estimation reports from CWICR calculations. HTML, PDF, Excel outputs with charts and breakdowns.

Overview

Publisherdatadrivenconstruction
RepositoryDDC_Skills_for_AI_Agents_in_Construction
Skill namecwicr-report-generator
Stars
365
Forks
91
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by datadrivenconstruction on GitHub. Read the source before you install it.

Installation

Install the Cwicr Report Generator AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction/tree/main/1_DDC_Toolkit/CWICR-Database/cwicr-report-generator
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction.git /tmp/DDC_Skills_for_AI_Agents_in_Construction
mkdir -p .claude/skills
cp -r /tmp/DDC_Skills_for_AI_Agents_in_Construction/1_DDC_Toolkit/CWICR-Database/cwicr-report-generator .claude/skills/cwicr-report-generator
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cwicr Report Generator in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Cwicr Report Generator on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Cwicr Report Generator is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

CWICR Report Generator

Overview

Generate professional cost reports from CWICR calculations - executive summaries, detailed breakdowns, charts, and export to multiple formats.

Python Implementation

python
import pandas as pd
from typing import Dict, Any, List, Optional
from dataclasses import dataclass, field
from datetime import datetime
from pathlib import Path
import json


@dataclass
class ReportSection:
    """Report section content."""
    title: str
    content: str
    chart_type: Optional[str] = None
    chart_data: Optional[Dict] = None


@dataclass
class CostReport:
    """Complete cost report."""
    project_name: str
    generated_date: datetime
    total_cost: float
    currency: str
    sections: List[ReportSection]
    line_items: List[Dict]
    summary: Dict[str, Any]


class CWICRReportGenerator:
    """Generate cost estimation reports."""

    def __init__(self, project_name: str = "Project",
                 currency: str = "USD"):
        self.project_name = project_name
        self.currency = currency
        self.sections: List[ReportSection] = []
        self.line_items: List[Dict] = []

    def add_summary(self, summary_data: Dict[str, float]):
        """Add executive summary section."""

        content = f"""
        <div class="summary-box">
            <h3>Cost Summary</h3>
            <table class="summary-table">
                <tr><td>Labor</td><td class="amount">${summary_data.get('labor', 0):,.2f}</td></tr>
                <tr><td>Materials</td><td class="amount">${summary_data.get('material', 0):,.2f}</td></tr>
                <tr><td>Equipment</td><td class="amount">${summary_data.get('equipment', 0):,.2f}</td></tr>
                <tr><td>Overhead</td><td class="amount">${summary_data.get('overhead', 0):,.2f}</td></tr>
                <tr><td>Profit</td><td class="amount">${summary_data.get('profit', 0):,.2f}</td></tr>
                <tr class="total"><td>TOTAL</td><td class="amount">${summary_data.get('total', 0):,.2f}</td></tr>
            </table>
        </div>
        """

        self.sections.append(ReportSection(
            title="Executive Summary",
            content=content,
            chart_type="pie",
            chart_data={
                'labels': ['Labor', 'Materials', 'Equipment', 'Overhead', 'Profit'],
                'values': [
                    summary_data.get('labor', 0),
                    summary_data.get('material', 0),
                    summary_data.get('equipment', 0),
                    summary_data.get('overhead', 0),
                    summary_data.get('profit', 0)
                ]
            }
        ))

    def add_breakdown_by_category(self, breakdown: Dict[str, float]):
        """Add breakdown by category section."""

        rows = ""
        for category, cost in sorted(breakdown.items(), key=lambda x: -x[1]):
            rows += f"<tr><td>{category}</td><td class='amount'>${cost:,.2f}</td></tr>"

        content = f"""
        <table class="detail-table">
            <thead><tr><th>Category</th><th>Cost</th></tr></thead>
            <tbody>{rows}</tbody>
        </table>
        """

        self.sections.append(ReportSection(
            title="Cost by Category",
            content=content,
            chart_type="bar",
            chart_data={
                'labels': list(breakdown.keys()),
                'values': list(breakdown.values())
            }
        ))

    def add_line_items(self, items: List[Dict]):
        """Add detailed line items."""
        self.line_items = items

        rows = ""
        for item in items[:50]:  # Limit for report
            rows += f"""
            <tr>
                <td>{item.get('code', '')}</td>
                <td>{item.get('description', '')[:50]}</td>
                <td>{item.get('quantity', 0):,.2f}</td>
                <td>{item.get('unit', '')}</td>
                <td class="amount">${item.get('unit_price', 0):,.2f}</td>
                <td class="amount">${item.get('total', 0):,.2f}</td>
            </tr>
            """

        content = f"""
        <table class="line-items">
            <thead>
                <tr>
                    <th>Code</th>
                    <th>Description</th>
                    <th>Qty</th>
                    <th>Unit</th>
                    <th>Unit Price</th>
                    <th>Total</th>
                </tr>
            </thead>
            <tbody>{rows}</tbody>
        </table>
        """

        self.sections.append(ReportSection(
            title="Line Items",
            content=content
        ))

    def generate_html(self) -> str:
        """Generate HTML report."""

        sections_html = ""
        for section in self.sections:
            sections_html += f"""
            <section class="report-section">
                <h2>{section.title}</h2>
                {section.content}
            </section>
            """

        html = f"""
<!DOCTYPE html>
<html>
<head>
    <title>Cost Report - {self.project_name}</title>
    <style>
        body {{ font-family: 'Segoe UI', Arial, sans-serif; margin: 40px; background: #f5f5f5; }}
        .report-container {{ max-width: 1200px; margin: 0 auto; background: white; padding: 40px; box-shadow: 0 2px 10px rgba(0,0,0,0.1); }}
        h1 {{ color: #2c3e50; border-bottom: 3px solid #3498db; padding-bottom: 10px; }}
        h2 {{ color: #34495e; margin-top: 30px; }}
        .summary-box {{ background: #ecf0f1; padding: 20px; border-radius: 8px; }}
        table {{ width: 100%; border-collapse: collapse; margin: 20px 0; }}
        th, td {{ padding: 12px; text-align: left; border-bottom: 1px solid #ddd; }}
        th {{ background: #3498db; color: white; }}
        .amount {{ text-align: right; font-family: monospace; }}
        .total {{ font-weight: bold; background: #f8f9fa; }}
        .line-items td {{ font-size: 0.9em; }}
        .meta {{ color: #7f8c8d; font-size: 0.9em; margin-bottom: 20px; }}
    </style>
</head>
<body>
    <div class="report-container">
        <h1>Cost Estimation Report</h1>
        <div class="meta">
            <p>Project: {self.project_name}</p>
            <p>Generated: {datetime.now().strftime('%Y-%m-%d %H:%M')}</p>
            <p>Currency: {self.currency}</p>
        </div>
        {sections_html}
        <footer style="margin-top: 40px; color: #95a5a6; text-align: center;">
            Generated by DDC CWICR | DataDrivenConstruction.io
        </footer>
    </div>
</body>
</html>
        """

        return html

    def save_html(self, output_path: str) -> str:
        """Save HTML report to file."""
        html = self.generate_html()
        with open(output_path, 'w', encoding='utf-8') as f:
            f.write(html)
        return output_path

    def generate_excel(self, output_path: str) -> str:
        """Generate Excel report."""

        with pd.ExcelWriter(output_path, engine='openpyxl') as writer:
            # Summary sheet
            if self.sections:
                summary_data = []
                for section in self.sections:
                    if section.chart_data:
                        for i, label in enumerate(section.chart_data.get('labels', [])):
                            summary_data.append({
                                'Category': label,
                                'Amount': section.chart_data.get('values', [])[i]
                            })
                if summary_data:
                    pd.DataFrame(summary_data).to_excel(
                        writer, sheet_name='Summary', index=False)

            # Line items sheet
            if self.line_items:
                pd.DataFrame(self.line_items).to_excel(
                    writer, sheet_name='Line Items', index=False)

        return output_path

    def generate_json(self) -> str:
        """Generate JSON report."""

        report = {
            'project_name': self.project_name,
            'generated_date': datetime.now().isoformat(),
            'currency': self.currency,
            'sections': [
                {
                    'title': s.title,
                    'chart_data': s.chart_data
                } for s in self.sections
            ],
            'line_items': self.line_items
        }

        return json.dumps(report, indent=2)


class QuickReport:
    """Quick report generation from cost data."""

    @staticmethod
    def from_dataframe(df: pd.DataFrame,
                       project_name: str = "Project") -> CWICRReportGenerator:
        """Generate report from cost DataFrame."""

        gen = CWICRReportGenerator(project_name)

        # Calculate summary
        summary = {
            'labor': df['labor_cost'].sum() if 'labor_cost' in df.columns else 0,
            'material': df['material_cost'].sum() if 'material_cost' in df.columns else 0,
            'equipment': df['equipment_cost'].sum() if 'equipment_cost' in df.columns else 0,
            'overhead': df['overhead_cost'].sum() if 'overhead_cost' in df.columns else 0,
            'profit': df['profit_cost'].sum() if 'profit_cost' in df.columns else 0,
            'total': df['total_cost'].sum() if 'total_cost' in df.columns else 0
        }
        gen.add_summary(summary)

        # Category breakdown
        if 'category' in df.columns and 'total_cost' in df.columns:
            breakdown = df.groupby('category')['total_cost'].sum().to_dict()
            gen.add_breakdown_by_category(breakdown)

        # Line items
        items = df.to_dict('records')
        gen.add_line_items(items)

        return gen

Quick Start

python
# Create report generator
gen = CWICRReportGenerator("Office Building", currency="EUR")

# Add sections
gen.add_summary({
    'labor': 125000,
    'material': 350000,
    'equipment': 75000,
    'overhead': 82500,
    'profit': 63250,
    'total': 695750
})

# Save reports
gen.save_html("cost_report.html")
gen.generate_excel("cost_report.xlsx")

From DataFrame

python
# Quick report from cost DataFrame
report = QuickReport.from_dataframe(cost_df, "My Project")
report.save_html("quick_report.html")

Resources

  • DDC Book: Chapter 4.2 - ETL Load Reports

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Cwicr Report Generator AI skill do?

Generate professional cost estimation reports from CWICR calculations. HTML, PDF, Excel outputs with charts and breakdowns.

Why use Cwicr Report Generator on TypingMind?

Because you install it once and use it with any model. Cwicr Report Generator is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Cwicr Report Generator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction/tree/main/1_DDC_Toolkit/CWICR-Database/cwicr-report-generator. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Cwicr Report Generator?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Cwicr Report Generator?

As many as you like. As long as a model supports skills, you can use Cwicr Report Generator with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Cwicr Report Generator AI skill free?

Yes. It is published on GitHub by datadrivenconstruction under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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