cwicr-report-generator

cwicr-report-generator is a skill for Claude Code, Codex from datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction. It costs 29 tokens per session (2,541 once invoked), scanned A, original, MIT.

A tool that turns CWICR cost calculations into reports with summaries, detailed line items, charts, and HTML, PDF, or Excel output.

In plain words
What is it for?
Use it to create project cost reports, show cost breakdowns, and export results for sharing or further analysis.
Why use it?
It removes the work of assembling calculation results into a readable report in several file formats.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: built for openclaw.

Good fit Use it to create project cost reports, show cost breakdowns, and export results for sharing or further analysis.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/cwicr-report-generator
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill cwicr-report-generator
Clone the repo
git clone --depth 1 https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for cwicr-report-generator

README.md
[![agentmods](https://agentmods.dev/badge/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/cwicr-report-generator/github.svg)](https://agentmods.dev/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/cwicr-report-generator)
Your own site
<a href="https://agentmods.dev/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/cwicr-report-generator"><img src="https://agentmods.dev/badge/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/cwicr-report-generator/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for cwicr-report-generator

Your own site · 80×15
<a href="https://agentmods.dev/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/cwicr-report-generator"><img src="https://agentmods.dev/badge/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/cwicr-report-generator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 29 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,541 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00029 $0.02541
Opus 5 $0.00015 $0.01270
Sonnet 5 $0.00006 $0.00508
Haiku 4.5 $0.00003 $0.00254

Measured 13d ago against content hash 3cdf9db5a362, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

cwicr-report-generator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

1_DDC_Toolkit/CWICR-Database/cwicr-report-generator/SKILL.md · 315 lines

How it starts

The opening of the file, as written. The whole thing — 315 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CWICR Report Generator

Overview

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

Python Implementation

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

Read the full file on GitHub · 315 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 13d ago First seen · 315 lines · 29 tokens per session scan A 3cdf9db5a362

Subscribe to this mod's changes

cwicr-report-generator is a skill published in the GitHub repository datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction (310 stars, last pushed 21d ago), licensed MIT. It adds 29 tokens to every session and 2,541 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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