report-generator

Report Generator Skill

Generate professional markdown and HTML reports from data with charts, tables, and analysis.

Instructions

You are a report generation expert. When invoked:

1. Analyze Data:

   • Understand data structure and content
   • Identify key metrics and insights
   • Calculate statistics and trends
   • Detect patterns and anomalies
   • Generate executive summaries

2. Create Report Structure:

   • Design clear, logical sections
   • Create table of contents
   • Add executive summary
   • Include detailed analysis
   • Provide recommendations

3. Generate Visualizations:

   • Create tables for structured data
   • Generate charts (bar, line, pie, scatter)
   • Add badges and indicators
   • Include code blocks and examples
   • Format numbers and percentages

4. Format Output:

   • Generate markdown reports
   • Create HTML reports with styling
   • Export to PDF
   • Add branding and customization
   • Ensure responsive design

Usage Examples

@report-generator data.csv
@report-generator --format html
@report-generator --template executive-summary
@report-generator --charts --pdf
@report-generator --compare baseline.json current.json

Report Types

Executive Summary Report

def generate_executive_summary(data, title="Executive Summary"):
    """
    Generate high-level executive summary report
    """
    from datetime import datetime

    report = f"""# {title}
**Generated:** {datetime.now().strftime('%B %d, %Y at %I:%M %p')}

---

## Key Highlights

"""

    # Calculate key metrics
    metrics = calculate_key_metrics(data)

    for metric in metrics:
        icon = "✅" if metric['status'] == 'good' else "⚠️" if metric['status'] == 'warning' else "❌"
        report += f"{icon} **{metric['name']}**: {metric['value']}\n"

    report += f"""

---

## Performance Overview

| Metric | Current | Previous | Change |
|--------|---------|----------|--------|
"""

    for metric in metrics:
        if 'previous' in metric:
            change = calculate_change(metric['current'], metric['previous'])
            arrow = "↑" if change > 0 else "↓" if change < 0 else "→"
            color = "green" if change > 0 else "red" if change < 0 else "gray"

            report += f"| {metric['name']} | {metric['current']:,} | {metric['previous']:,} | {arrow} {abs(change):.1f}% |\n"

    report += """

---

## Recommendations

"""

    recommendations = generate_recommendations(metrics)
    for i, rec in enumerate(recommendations, 1):
        priority = rec.get('priority', 'medium')
        emoji = "🔴" if priority == 'high' else "🟡" if priority == 'medium' else "🟢"

        report += f"{i}. {emoji} **{rec['title']}**\n"
        report += f"   {rec['description']}\n\n"

    return report