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abcnuts/analytics-dashboard

Name: analytics-dashboard
Author: abcnuts

skills/tier3-advanced/analytics-dashboard/SKILL.md

npx skillsauth add abcnuts/manus-skills analytics-dashboard

Clean

TrivyContainer and dependency vulnerability scanner

Clean

SemgrepStatic code analysis for vulnerabilities

Clean

mcp-scan (Snyk)Model Context Protocol security validation

Clean

VirusTotalMulti-engine malware detection

Skipped

Snyk (dep)Open source security scanning

Skipped

Socket.devSupply chain security analysis

Skipped

CrowdStrikeAdvanced threat intelligence

Skipped

OSV-ScannerOpen Source Vulnerability database check

Skipped

OWASP Dep-Check

Analytics Dashboard Skill

Automate setup of analytics tracking and dashboard generation for web applications.

Purpose

This skill helps you implement comprehensive analytics tracking and create beautiful dashboards to understand user behavior, track conversions, and measure product success.

When to Use

Adding analytics to a new application
Implementing event tracking for user actions
Creating analytics dashboards
Switching analytics providers
Setting up conversion tracking
Building admin analytics views

What It Does

Detects project type (Next.js, React, Express, Python)
Installs analytics dependencies (PostHog, Mixpanel, Amplitude, Segment)
Creates analytics configuration with initialization code
Generates dashboard components with key metrics
Provides tracking patterns for common events
Includes best practices for performance and privacy

Quick Start

1. Run Setup Script

python3 /home/ubuntu/skills/analytics-dashboard/scripts/setup_analytics.py \
  /path/to/your/project \
  posthog \
  YOUR_API_KEY

Arguments:

project_dir: Path to your project
provider: Analytics provider (posthog, mixpanel, amplitude, segment)
api_key: Your analytics API key

2. Initialize Analytics

Next.js - Add to app/layout.tsx:

import { initAnalytics } from '@/lib/analytics'

export default function RootLayout({ children }) {
  useEffect(() => {
    initAnalytics()
  }, [])
  
  return <html>{children}</html>
}

Python/Flask - Add to app initialization:

from analytics import track_event, identify_user

@app.before_request
def track_page_view():
    if current_user.is_authenticated:
        track_event(current_user.id, 'page_view', {
            'path': request.path
        })

3. Track Events

import { trackEvent } from '@/lib/analytics'

// Track button click
<button onClick={() => trackEvent('signup_clicked', {
  location: 'homepage'
})}>
  Sign Up
</button>

// Track form submission
const handleSubmit = (data) => {
  trackEvent('form_submitted', {
    form_name: 'contact',
    fields: Object.keys(data)
  })
}

// Track conversion
trackEvent('purchase_completed', {
  amount: 99.99,
  currency: 'USD',
  items: 3
})

4. Add Dashboard

Copy the generated dashboard component:

cp /home/ubuntu/skills/analytics-dashboard/templates/dashboard.tsx \
   /path/to/your/project/components/

Use in your app:

import AnalyticsDashboard from '@/components/AnalyticsDashboard'

export default function AdminPage() {
  return <AnalyticsDashboard />
}

Supported Providers

PostHog (Recommended)

Best for: Startups, product analytics
Features: Session replay, feature flags, A/B testing
Pricing: Generous free tier
Setup time: 5 minutes

Mixpanel

Best for: User behavior analysis
Features: Funnels, retention, cohorts
Pricing: Free up to 100k events/month
Setup time: 10 minutes

Amplitude

Best for: Product-led growth
Features: Behavioral analytics, predictions
Pricing: Free up to 10M events/month
Setup time: 10 minutes

Segment

Best for: Multiple analytics tools
Features: Single API for all providers
Pricing: Free up to 1k users/month
Setup time: 15 minutes

Key Metrics to Track

Engagement

Daily Active Users (DAU)
Weekly Active Users (WAU)
Monthly Active Users (MAU)
Session duration
Pages per session

Conversion

Signup conversion rate
Trial-to-paid conversion
Purchase completion rate
Funnel drop-off points

Retention

Day 1, 7, 30 retention
Churn rate
Cohort analysis

Product

Feature adoption rate
User flows
A/B test results

Event Tracking Patterns

Page Views

useEffect(() => {
  trackEvent('page_view', {
    path: window.location.pathname,
    referrer: document.referrer
  })
}, [pathname])

User Actions

trackEvent('button_clicked', {
  button_name: 'signup',
  location: 'homepage_hero'
})

User Identification

identifyUser(user.id, {
  email: user.email,
  plan: user.subscription_plan,
  signup_date: user.created_at
})

Conversions

trackEvent('purchase_completed', {
  amount: total,
  currency: 'USD',
  payment_method: 'stripe'
})

Dashboard Components

The generated dashboard includes:

Key Metrics Cards
- Total events
- Unique users
- Average session duration
- Bounce rate
Charts
- User growth (line chart)
- Top events (bar chart)
- Conversion funnel
Tables
- Top pages by views
- Top events by count
- Recent user activity

Best Practices

Performance

✅ Load analytics asynchronously
✅ Batch events together
✅ Debounce high-frequency events
❌ Don't block page load

Privacy

✅ Get user consent (GDPR)
✅ Provide opt-out mechanism
✅ Anonymize sensitive data
❌ Don't track PII without consent

Data Quality

✅ Include context with events
✅ Use consistent naming
✅ Test in development
❌ Don't track too much

Files Generated

Scripts

scripts/setup_analytics.py - Automated setup script

Templates

templates/dashboard.tsx - Analytics dashboard component

References

references/analytics_patterns.md - Comprehensive guide (300+ lines)

Workflow

Setup → Run script to install and configure
Initialize → Add analytics to app entry point
Track → Add event tracking throughout app
Dashboard → Add dashboard component for viewing
Optimize → Refine based on data

Examples

E-commerce Site

// Product viewed
trackEvent('product_viewed', {
  product_id: product.id,
  category: product.category,
  price: product.price
})

// Added to cart
trackEvent('add_to_cart', {
  product_id: product.id,
  quantity: 1,
  cart_total: cart.total
})

// Purchase completed
trackEvent('purchase_completed', {
  order_id: order.id,
  total: order.total,
  items: order.items.length
})

SaaS Application

// Trial started
trackEvent('trial_started', {
  plan: 'pro',
  trial_days: 14
})

// Feature used
trackEvent('feature_used', {
  feature_name: 'export_data',
  usage_count: user.export_count
})

// Subscription upgraded
trackEvent('subscription_upgraded', {
  from_plan: 'basic',
  to_plan: 'pro',
  mrr_change: 20
})

Troubleshooting

Events not showing up

Check API key is correct
Verify analytics is initialized
Check browser console for errors
Test in production mode

Dashboard not loading

Verify API endpoint exists
Check CORS settings
Ensure data is being tracked
Check network tab for errors

Performance issues

Batch events together
Debounce high-frequency events
Load analytics asynchronously
Use sampling for high-volume

Time Savings

Manual Setup: 2-3 hours

Research providers: 30 min
Install dependencies: 15 min
Write configuration: 45 min
Create dashboard: 60 min
Test and debug: 30 min

With This Skill: 15-20 minutes

Run setup script: 5 min
Configure API keys: 5 min
Add tracking: 5 min
Test: 5 min

Time Saved: ~2 hours per project

Related Skills

deployment-automation - Deploy with analytics configured
user-authentication-system - Identify users after login
feature-flag-system - Track feature flag usage
error-monitoring-setup - Combine with error tracking

Resources

PostHog Documentation
Mixpanel Best Practices
Amplitude Playbook
Analytics Patterns Reference

Built with best practices, privacy-conscious, performance-optimized.

abcnuts/analytics-dashboard

skills/tier3-advanced/analytics-dashboard/SKILL.md

User behavior tracking and analytics dashboards

4 stars

data-ai

Updated Mar 26, 2026

$ install --global

skillsauth

npx skillsauth add abcnuts/manus-skills analytics-dashboard

Install this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.

Security Scan Results

4 of 9 scanners reported clean

Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.

Scanners Passed

Scanners in report

Clean

TrivyContainer and dependency vulnerability scanner

95%

Clean

SemgrepStatic code analysis for vulnerabilities

95%

Clean

mcp-scan (Snyk)Model Context Protocol security validation

95%

Clean

VirusTotalMulti-engine malware detection

95%

Skipped

Snyk (dep)Open source security scanning

50%

Skipped

Socket.devSupply chain security analysis

50%

Skipped

CrowdStrikeAdvanced threat intelligence

50%

Skipped

OSV-ScannerOpen Source Vulnerability database check

50%

Skipped

OWASP Dep-Check

50%

Last scanned: Apr 16, 2026, 11:57 AM53.5s1 file scanned

SKILL.md

name:: analytics-dashboard
description:: User behavior tracking and analytics dashboards

Analytics Dashboard Skill

Automate setup of analytics tracking and dashboard generation for web applications.

Purpose

This skill helps you implement comprehensive analytics tracking and create beautiful dashboards to understand user behavior, track conversions, and measure product success.

When to Use

Adding analytics to a new application
Implementing event tracking for user actions
Creating analytics dashboards
Switching analytics providers
Setting up conversion tracking
Building admin analytics views

What It Does

Detects project type (Next.js, React, Express, Python)
Installs analytics dependencies (PostHog, Mixpanel, Amplitude, Segment)
Creates analytics configuration with initialization code
Generates dashboard components with key metrics
Provides tracking patterns for common events
Includes best practices for performance and privacy

Quick Start

1. Run Setup Script

python3 /home/ubuntu/skills/analytics-dashboard/scripts/setup_analytics.py \
  /path/to/your/project \
  posthog \
  YOUR_API_KEY

Arguments:

project_dir: Path to your project
provider: Analytics provider (posthog, mixpanel, amplitude, segment)
api_key: Your analytics API key

2. Initialize Analytics

Next.js - Add to app/layout.tsx:

import { initAnalytics } from '@/lib/analytics'

export default function RootLayout({ children }) {
  useEffect(() => {
    initAnalytics()
  }, [])
  
  return <html>{children}</html>
}

Python/Flask - Add to app initialization:

from analytics import track_event, identify_user

@app.before_request
def track_page_view():
    if current_user.is_authenticated:
        track_event(current_user.id, 'page_view', {
            'path': request.path
        })

3. Track Events

import { trackEvent } from '@/lib/analytics'

// Track button click
<button onClick={() => trackEvent('signup_clicked', {
  location: 'homepage'
})}>
  Sign Up
</button>

// Track form submission
const handleSubmit = (data) => {
  trackEvent('form_submitted', {
    form_name: 'contact',
    fields: Object.keys(data)
  })
}

// Track conversion
trackEvent('purchase_completed', {
  amount: 99.99,
  currency: 'USD',
  items: 3
})

4. Add Dashboard

Copy the generated dashboard component:

cp /home/ubuntu/skills/analytics-dashboard/templates/dashboard.tsx \
   /path/to/your/project/components/

Use in your app:

import AnalyticsDashboard from '@/components/AnalyticsDashboard'

export default function AdminPage() {
  return <AnalyticsDashboard />
}

Supported Providers

PostHog (Recommended)

Best for: Startups, product analytics
Features: Session replay, feature flags, A/B testing
Pricing: Generous free tier
Setup time: 5 minutes

Mixpanel

Best for: User behavior analysis
Features: Funnels, retention, cohorts
Pricing: Free up to 100k events/month
Setup time: 10 minutes

Amplitude

Best for: Product-led growth
Features: Behavioral analytics, predictions
Pricing: Free up to 10M events/month
Setup time: 10 minutes

Segment

Best for: Multiple analytics tools
Features: Single API for all providers
Pricing: Free up to 1k users/month
Setup time: 15 minutes

Key Metrics to Track

Engagement

Daily Active Users (DAU)
Weekly Active Users (WAU)
Monthly Active Users (MAU)
Session duration
Pages per session

Conversion

Signup conversion rate
Trial-to-paid conversion
Purchase completion rate
Funnel drop-off points

Retention

Day 1, 7, 30 retention
Churn rate
Cohort analysis

Product

Feature adoption rate
User flows
A/B test results

Event Tracking Patterns

Page Views

useEffect(() => {
  trackEvent('page_view', {
    path: window.location.pathname,
    referrer: document.referrer
  })
}, [pathname])

User Actions

trackEvent('button_clicked', {
  button_name: 'signup',
  location: 'homepage_hero'
})

User Identification

identifyUser(user.id, {
  email: user.email,
  plan: user.subscription_plan,
  signup_date: user.created_at
})

Conversions

trackEvent('purchase_completed', {
  amount: total,
  currency: 'USD',
  payment_method: 'stripe'
})

Dashboard Components

The generated dashboard includes:

Key Metrics Cards
- Total events
- Unique users
- Average session duration
- Bounce rate
Charts
- User growth (line chart)
- Top events (bar chart)
- Conversion funnel
Tables
- Top pages by views
- Top events by count
- Recent user activity

Best Practices

Performance

✅ Load analytics asynchronously
✅ Batch events together
✅ Debounce high-frequency events
❌ Don't block page load

Privacy

✅ Get user consent (GDPR)
✅ Provide opt-out mechanism
✅ Anonymize sensitive data
❌ Don't track PII without consent

Data Quality

✅ Include context with events
✅ Use consistent naming
✅ Test in development
❌ Don't track too much

Files Generated

Scripts

scripts/setup_analytics.py - Automated setup script

Templates

templates/dashboard.tsx - Analytics dashboard component

References

references/analytics_patterns.md - Comprehensive guide (300+ lines)

Workflow

Setup → Run script to install and configure
Initialize → Add analytics to app entry point
Track → Add event tracking throughout app
Dashboard → Add dashboard component for viewing
Optimize → Refine based on data

Examples

E-commerce Site

// Product viewed
trackEvent('product_viewed', {
  product_id: product.id,
  category: product.category,
  price: product.price
})

// Added to cart
trackEvent('add_to_cart', {
  product_id: product.id,
  quantity: 1,
  cart_total: cart.total
})

// Purchase completed
trackEvent('purchase_completed', {
  order_id: order.id,
  total: order.total,
  items: order.items.length
})

SaaS Application

// Trial started
trackEvent('trial_started', {
  plan: 'pro',
  trial_days: 14
})

// Feature used
trackEvent('feature_used', {
  feature_name: 'export_data',
  usage_count: user.export_count
})

// Subscription upgraded
trackEvent('subscription_upgraded', {
  from_plan: 'basic',
  to_plan: 'pro',
  mrr_change: 20
})

Troubleshooting

Events not showing up

Check API key is correct
Verify analytics is initialized
Check browser console for errors
Test in production mode

Dashboard not loading

Verify API endpoint exists
Check CORS settings
Ensure data is being tracked
Check network tab for errors

Performance issues

Batch events together
Debounce high-frequency events
Load analytics asynchronously
Use sampling for high-volume

Time Savings

Manual Setup: 2-3 hours

Research providers: 30 min
Install dependencies: 15 min
Write configuration: 45 min
Create dashboard: 60 min
Test and debug: 30 min

With This Skill: 15-20 minutes

Run setup script: 5 min
Configure API keys: 5 min
Add tracking: 5 min
Test: 5 min

Time Saved: ~2 hours per project

Related Skills

deployment-automation - Deploy with analytics configured
user-authentication-system - Identify users after login
feature-flag-system - Track feature flag usage
error-monitoring-setup - Combine with error tracking

Resources

PostHog Documentation
Mixpanel Best Practices
Amplitude Playbook
Analytics Patterns Reference

Built with best practices, privacy-conscious, performance-optimized.

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Download

For Claude Desktop. Download once, then upload the file in the app — no terminal needed.

Need help? View full Cowork setup guide →

Install manually

Choose your platform

# Clone the repo
git clone https://github.com/abcnuts/manus-skills.git

# Copy into Claude Code skills folder (global)
cp -r manus-skills/skills/tier3-advanced/analytics-dashboard ~/.claude/skills/

Claude Code Skills — official skills path docs.

Repository

abcnuts/manus-skills

4 stars

Compatible with

Claude Code

OpenAI Codex CLI

ChatGPT