jay-code/src/ui/console/README-analysis-tools.md

Streamlined AI CLI orchestration engine with mathematical rigor and enterprise-grade reliability

# Analysis & Monitoring Tools - Claude Flow Web UI

**Agent 2 - Analysis & Monitoring Tools Developer**

## Overview

This implementation provides a comprehensive suite of 13 analysis and monitoring tools for the Claude Flow Web UI, featuring real-time dashboards, interactive visualizations, and export capabilities.

## 🛠️ Implemented Tools

### 1. Performance Report (`performance_report`)

- **Purpose**: Generate comprehensive performance metrics and reports
- **Features**: Response time tracking, throughput analysis, error rate monitoring
- **API Endpoint**: `/api/analysis/performance-report`

### 2. Bottleneck Analysis (`bottleneck_analyze`)

- **Purpose**: Detect and analyze system bottlenecks
- **Features**: Component analysis, severity assessment, impact evaluation
- **API Endpoint**: `/api/analysis/bottleneck-analyze`

### 3. Token Usage (`token_usage`)

- **Purpose**: Track and analyze token consumption patterns
- **Features**: Cost analysis, efficiency metrics, usage trends
- **API Endpoint**: `/api/analysis/token-usage`

### 4. Benchmark Run (`benchmark_run`)

- **Purpose**: Execute performance benchmarks and comparisons
- **Features**: Multi-metric benchmarking, baseline comparisons, scoring
- **API Endpoint**: `/api/analysis/benchmark-run`

### 5. Metrics Collection (`metrics_collect`)

- **Purpose**: Collect comprehensive system metrics
- **Features**: System info, resource usage, performance indicators
- **API Endpoint**: `/api/analysis/metrics-collect`

### 6. Trend Analysis (`trend_analysis`)

- **Purpose**: Detect trends and forecast future patterns
- **Features**: Performance trends, usage patterns, predictions
- **API Endpoint**: `/api/analysis/trend-analysis`

### 7. Cost Analysis (`cost_analysis`)

- **Purpose**: Analyze resource costs and optimization opportunities
- **Features**: Cost breakdown, trend analysis, optimization recommendations
- **API Endpoint**: `/api/analysis/cost-analysis`

### 8. Quality Assessment (`quality_assess`)

- **Purpose**: Assess system quality across multiple dimensions
- **Features**: Performance, reliability, security, maintainability metrics
- **API Endpoint**: `/api/analysis/quality-assess`

### 9. Error Analysis (`error_analysis`)

- **Purpose**: Analyze error patterns and provide resolution guidance
- **Features**: Error categorization, pattern identification, resolution recommendations
- **API Endpoint**: `/api/analysis/error-analysis`

### 10. Usage Statistics (`usage_stats`)

- **Purpose**: Generate comprehensive usage statistics and insights
- **Features**: User analytics, session analysis, feature usage tracking
- **API Endpoint**: `/api/analysis/usage-stats`

### 11. Health Check (`health_check`)

- **Purpose**: Monitor system health across all components
- **Features**: Component health scoring, alert generation, status monitoring
- **API Endpoint**: `/api/analysis/health-check`

### 12. Load Monitor (`load_monitor`)

- **Purpose**: Monitor system load and generate alerts
- **Features**: Real-time load tracking, trend analysis, alert generation
- **API Endpoint**: `/api/analysis/load-monitor`

### 13. Capacity Planning (`capacity_plan`)

- **Purpose**: Plan future capacity requirements
- **Features**: Resource projections, timeline planning, scaling recommendations
- **API Endpoint**: `/api/analysis/capacity-plan`

## 📊 Dashboard Features

### 4-Tab Interface

1. **Metrics**: Real-time performance and token usage metrics
2. **Reports**: Report generation and export functionality
3. **Analysis**: Advanced analysis tools and visualizations
4. **Health**: System health monitoring and alerts

### Interactive Charts

- **Performance Chart**: Line chart showing response time and throughput trends
- **Token Usage Chart**: Doughnut chart displaying token distribution
- **System Health Chart**: Radar chart showing component health scores
- **Load Monitor Chart**: Bar chart tracking system load over time

### Real-time Features

- **WebSocket Integration**: Live data updates every 5 seconds
- **Connection Status**: Visual indicator of WebSocket connection state
- **Auto-refresh**: Automatic data refresh with manual refresh options
- **Live Alerts**: Real-time system alerts and notifications

## 🔧 Technical Implementation

### Frontend Components

- **JavaScript**: `/src/ui/console/js/analysis-tools.js`
- **CSS**: `/src/ui/console/styles/analysis-tools.css`
- **HTML**: `/src/ui/console/analysis-tools.html`

### Backend API

- **Router**: `/src/api/routes/analysis.js`
- **WebSocket**: Real-time data streaming
- **Metrics Storage**: In-memory storage with database integration ready

### Key Features

- **Responsive Design**: Mobile-friendly interface
- **Export Functionality**: JSON and CSV export options
- **Dark Mode Support**: Automatic dark theme detection
- **Print Styles**: Print-optimized layouts
- **Error Handling**: Comprehensive error handling and user feedback

## 🚀 Getting Started

### Prerequisites

- Node.js 16+
- Express.js server
- Chart.js library
- WebSocket support

### Installation

1. Copy the files to your Claude Flow project
2. Install dependencies:
   ```bash
   npm install express ws chart.js
   ```

### Integration

1. Add the analysis router to your Express app:

   ```javascript
   const analysisRouter = require('./src/api/routes/analysis');
   app.use('/api/analysis', analysisRouter);
   ```

2. Include the CSS and JavaScript files in your HTML:
   ```html
   <link rel="stylesheet" href="styles/analysis-tools.css" />
   <script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
   <script src="js/analysis-tools.js"></script>
   ```

### Usage

1. Navigate to `/analysis-tools.html` in your browser
2. Use the tab navigation to switch between different views
3. Click tool buttons to execute analysis functions
4. Export data using the export buttons
5. Monitor real-time updates through the WebSocket connection

## 📈 Data Flow

### Real-time Metrics

1. **Collection**: Server collects metrics from various sources
2. **Processing**: Metrics are processed and stored in memory
3. **Broadcasting**: WebSocket broadcasts updates to connected clients
4. **Visualization**: Charts update automatically with new data

### Tool Execution

1. **Request**: User clicks tool button in UI
2. **API Call**: Frontend makes HTTP request to analysis API
3. **Processing**: Backend processes request and generates results
4. **Response**: Results are returned and displayed in UI
5. **Notification**: Swarm coordination hooks are triggered

## 🔍 Monitoring & Alerts

### Health Monitoring

- **Component Health**: CPU, Memory, Disk, Network, API, Database
- **Health Scores**: 0-100 scale with color-coded indicators
- **Alert Thresholds**: Configurable warning and critical levels

### Performance Monitoring

- **Response Time**: Average, min, max response times
- **Throughput**: Requests per second/minute
- **Error Rate**: Percentage of failed requests
- **Uptime**: System availability metrics

### Alert System

- **Real-time Alerts**: Immediate notification of issues
- **Severity Levels**: Info, Warning, Critical
- **Auto-dismiss**: Configurable auto-dismiss for info alerts
- **Alert History**: Persistent alert logging

## 📊 Export & Reporting

### Export Formats

- **JSON**: Complete data export with metadata
- **CSV**: Tabular data export for spreadsheet analysis

### Report Types

- **Performance Reports**: Comprehensive performance analysis
- **Cost Reports**: Resource cost breakdown and optimization
- **Quality Reports**: System quality assessment
- **Health Reports**: Component health status

## 🎨 Customization

### Styling

- Modify `analysis-tools.css` for custom styling
- Responsive breakpoints for different screen sizes
- Dark mode support with CSS media queries

### Configuration

- Adjust WebSocket update intervals
- Configure alert thresholds
- Customize chart colors and types

### Extension

- Add new analysis tools following the existing pattern
- Implement additional chart types using Chart.js
- Extend API endpoints for custom metrics

## 🔒 Security Considerations

### Data Protection

- Client-side data validation
- Secure WebSocket connections (WSS in production)
- API rate limiting implementation ready

### Error Handling

- Graceful error handling for failed requests
- User-friendly error messages
- Automatic retry mechanisms

## 🚀 Performance Optimization

### Frontend Optimization

- Lazy loading of chart components
- Efficient data update strategies
- Memory management for long-running sessions

### Backend Optimization

- Efficient metrics collection
- Optimized database queries (when integrated)
- Caching strategies for frequently accessed data

## 📱 Responsive Design

### Mobile Support

- Touch-friendly interface
- Responsive chart sizing
- Optimized navigation for small screens

### Tablet Support

- Optimized layout for tablet devices
- Touch gestures for chart interaction
- Efficient space utilization

## 🔧 Development & Testing

### Development Setup

1. Start the development server
2. Open `analysis-tools.html` in browser
3. Monitor console for WebSocket connection status
4. Test all tool functions and exports

### Testing Checklist

- [ ] All 13 tools execute without errors
- [ ] WebSocket connection establishes successfully
- [ ] Real-time updates work correctly
- [ ] Export functions generate valid files
- [ ] Responsive design works on all devices
- [ ] Charts render and update properly
- [ ] Alert system functions correctly

## 📚 API Documentation

### Endpoint Structure

```
GET /api/analysis/{tool-name}
```

### Response Format

```json
{
  "timestamp": 1234567890,
  "summary": "Tool execution summary",
  "data": { ... },
  "recommendations": [...],
  "alerts": [...]
}
```

### WebSocket Messages

```json
{
  "type": "metrics_update",
  "payload": {
    "performance": { ... },
    "tokens": { ... },
    "health": { ... },
    "load": { ... }
  }
}
```

## 🤝 Contributing

### Adding New Tools

1. Add tool button to HTML interface
2. Implement tool logic in JavaScript
3. Create API endpoint in backend router
4. Add styling for new components
5. Update documentation

### Code Style

- Follow existing naming conventions
- Use ES6+ features where appropriate
- Maintain consistent error handling
- Add comprehensive comments

## 📞 Support

For issues or questions regarding the Analysis & Monitoring Tools:

1. Check the console for error messages
2. Verify WebSocket connection status
3. Ensure all dependencies are installed
4. Review API endpoint responses

## 🔄 Future Enhancements

### Planned Features

- Database integration for persistent metrics
- Advanced filtering and search capabilities
- Custom dashboard creation
- Multi-tenant support
- Advanced analytics and ML insights

### Integration Opportunities

- External monitoring tools
- Third-party alert systems
- Business intelligence platforms
- Custom metric sources

---

**Agent 2 - Analysis & Monitoring Tools Developer**  
_Complete implementation of 13 analysis and monitoring tools with real-time dashboards and WebSocket integration_