QA Agent

Automate website quality assurance and bug detection through AI-powered analysis. Comprehensive website auditing that combines automated crawling, performance testing, and intelligent issue detection.

Features

Automated Website Crawling: Systematic analysis of HTML, CSS, JavaScript, and PHP files
Multi-dimensional Quality Checks: SEO, accessibility, security, performance, and UI evaluation
Performance Analysis: Integration with Google PageSpeed Insights for mobile and desktop metrics
Detailed Reporting: Generates structured reports with actionable recommendations
Real-time Processing: Live streaming of analysis results with progress tracking

How It Works

The QA Agent processes websites through a comprehensive analysis pipeline:

URL Input → Content Scraping → Code Analysis → Performance Testing → Report Generation

Architecture Overview

Processing Pipeline

Content Extraction: Scrapes and parses all website resources
Code Analysis: LLM-powered evaluation against quality checklists
Performance Testing: Google PageSpeed API integration for speed metrics
Report Generation: Combines findings into structured Excel reports
Storage & Delivery: Uploads reports to S3 and provides download links

Core Components

Component	Purpose
Web Scraper	Extracts HTML, CSS, JS, and PHP files
Content Filter	Cleans and optimizes code for analysis
LLM Chain	Processes content against quality checklists
PageSpeed API	Retrieves performance metrics
Report Generator	Creates structured Excel reports
Queue Manager	Handles real-time result streaming

Implementation

Analysis Workflow

def analyze_website(url):
    # 1. Initialize components
    llm = initialize_llm()
    queues = setup_analysis_queues()
    
    # 2. Extract website content
    scraped_content = scrape_url_content(url)
    filtered_content = filter_code_lines(scraped_content)
    
    # 3. Performance analysis
    pagespeed_results = pagespeed_api_call(url, ['mobile', 'desktop'])
    
    # 4. Content analysis
    token_count = count_tokens(filtered_content)
    analysis_chain = initialize_llm_chain(llm)
    
    # 5. Batch processing
    checklist_batches = batch_checklist_items(filtered_content, batch_size=10)
    
    # 6. Execute analysis
    for batch in checklist_batches:
        results = analysis_chain.process(batch)
        stream_to_queue(results, queues['checklist'])
    
    # 7. Generate report
    excel_report = create_excel_report(checklist_results, pagespeed_results)
    s3_url = upload_to_s3(excel_report)
    
    # 8. Return results
    return {
        'pagespeed_data': pagespeed_results,
        'report_url': s3_url,
        'token_usage': calculate_cost(token_count),
        'processing_time': elapsed_time
    }

Key Functions

Function	Purpose
`scrape_url_content()`	Extracts all website files and resources
`pagespeed_api_call()`	Retrieves Google PageSpeed metrics
`batch_checklist_items()`	Organizes analysis tasks into processable chunks
`stream_to_queue()`	Provides real-time progress updates
`create_excel_report()`	Generates formatted analysis reports

API Reference

Analysis Endpoint

POST /api/qa-analysis

Request Body

{
  "url": "https://example.com",
  "analysisType": "comprehensive",
  "options": {
    "includeMobile": true,
    "includeDesktop": true,
    "generateReport": true
  }
}

Response Format

{
  "analysisId": "qa_12345",
  "status": "completed",
  "results": {
    "seoScore": 85,
    "performanceScore": 78,
    "accessibilityScore": 92,
    "bestPracticesScore": 88
  },
  "reports": {
    "excelUrl": "https://s3.amazonaws.com/reports/qa_12345.xlsx",
    "jsonData": { ... }
  },
  "metrics": {
    "tokenUsage": 2500,
    "processingTime": "45s",
    "pagesAnalyzed": 12
  }
}

Streaming Analysis

GET /api/qa-analysis/{analysisId}/stream

Returns Server-Sent Events for real-time progress updates:

data: {"type": "progress", "step": "scraping", "completion": 25}
data: {"type": "result", "category": "seo", "issues": [...]}
data: {"type": "complete", "reportUrl": "https://..."}

Configuration

Analysis Parameters

Parameter	Type	Default	Description
`batchSize`	integer	10	Checklist items per LLM call
`maxPages`	integer	50	Maximum pages to analyze
`includeSubdomains`	boolean	false	Analyze subdomain pages
`performanceThreshold`	integer	70	Minimum acceptable performance score

Supported Check Categories

SEO Analysis: Meta tags, structured data, URL structure
Performance: Load times, resource optimization, Core Web Vitals
Accessibility: WCAG compliance, keyboard navigation, screen reader support
Security: HTTPS usage, security headers, vulnerability scanning
Code Quality: HTML validation, CSS optimization, JavaScript errors

Usage Examples

Basic Website Analysis

curl -X POST /api/qa-analysis \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer your-api-key" \
  -d '{
    "url": "https://example.com",
    "analysisType": "comprehensive"
  }'

Custom Analysis with Options

curl -X POST /api/qa-analysis \
  -H "Content-Type: application/json" \
  -d '{
    "url": "https://example.com",
    "analysisType": "performance",
    "options": {
      "includeMobile": true,
      "includeDesktop": false,
      "maxPages": 25
    }
  }'

Python Implementation

import requests

response = requests.post('/api/qa-analysis', json={
    'url': 'https://example.com',
    'analysisType': 'comprehensive',
    'options': {
        'generateReport': True,
        'includeSubdomains': False
    }
})

analysis = response.json()
print(f"Analysis ID: {analysis['analysisId']}")
print(f"Report URL: {analysis['reports']['excelUrl']}")

Performance & Limits

Processing Metrics

Average Analysis Time: 30-90 seconds per website
Concurrent Analyses: Up to 5 websites simultaneously
Page Limit: 50 pages per analysis (configurable)

Rate Limits

API Requests: 50 analyses per hour per API key
Concurrent Jobs: 5 active analyses
Token Usage: Tracked and reported per analysis

File Constraints

Website Size: No explicit limit (processed page by page)
Analysis Depth: Configurable crawl depth (default: 3 levels)
Report Size: Excel reports typically 1-5MB

Error Handling

Common Error Responses

Status Code	Error Type	Description	Solution
`400`	`INVALID_URL`	URL format invalid or unreachable	Verify URL format and accessibility
`429`	`RATE_LIMIT_EXCEEDED`	Too many concurrent analyses	Wait before starting new analysis
`500`	`SCRAPING_FAILED`	Unable to extract website content	Check website accessibility and robots.txt
`503`	`PAGESPEED_UNAVAILABLE`	Google PageSpeed API error	Retry analysis or skip performance metrics

Error Response Format

{
  "error": {
    "code": "SCRAPING_FAILED",
    "message": "Unable to access website content",
    "details": {
      "url": "https://example.com",
      "httpStatus": 403,
      "reason": "Access forbidden by robots.txt"
    }
  }
}

Integration Guide

Authentication

All API requests require Bearer token authentication:

curl -H "Authorization: Bearer your-api-key" \
     -H "Content-Type: application/json"

Webhook Notifications

Configure webhooks for analysis completion:

{
  "webhookUrl": "https://your-app.com/qa-complete",
  "events": ["analysis.completed", "analysis.failed"]
}

Report Processing

Excel reports include multiple worksheets:

Summary: Overall scores and key findings
SEO Issues: Detailed SEO recommendations
Performance: PageSpeed metrics and optimization suggestions
Accessibility: WCAG compliance issues
Security: Security headers and vulnerability findings

Overview

Setup

Your Account

Features

Pro Agents

Policies

Features

How It Works

Architecture Overview

Processing Pipeline

Core Components

Implementation

Analysis Workflow

Key Functions

API Reference

Analysis Endpoint

Streaming Analysis

Configuration

Analysis Parameters

Supported Check Categories

Usage Examples

Basic Website Analysis

Custom Analysis with Options

Python Implementation

Performance & Limits

Processing Metrics

Rate Limits

File Constraints

Error Handling

Common Error Responses

Error Response Format

Integration Guide

Authentication

Webhook Notifications

Report Processing

Overview

Setup

Your Account

Features

Pro Agents

Policies

​Features

​How It Works

​Architecture Overview

​Processing Pipeline

​Core Components

​Implementation

​Analysis Workflow

​Key Functions

​API Reference

​Analysis Endpoint

​Streaming Analysis

​Configuration

​Analysis Parameters

​Supported Check Categories

​Usage Examples

​Basic Website Analysis

​Custom Analysis with Options

​Python Implementation

​Performance & Limits

​Processing Metrics

​Rate Limits

​File Constraints

​Error Handling

​Common Error Responses

​Error Response Format

​Integration Guide

​Authentication

​Webhook Notifications

​Report Processing

Features

How It Works

Architecture Overview

Processing Pipeline

Core Components

Implementation

Analysis Workflow

Key Functions

API Reference

Analysis Endpoint

Streaming Analysis

Configuration

Analysis Parameters

Supported Check Categories

Usage Examples

Basic Website Analysis

Custom Analysis with Options

Python Implementation

Performance & Limits

Processing Metrics

Rate Limits

File Constraints

Error Handling

Common Error Responses

Error Response Format

Integration Guide

Authentication

Webhook Notifications

Report Processing