Advanced Optimization
Master advanced webMCP optimization techniques. Achieve maximum token reduction with sophisticated strategies and enterprise-grade features.
Advanced Optimization Strategies
Sophisticated techniques for maximum token reduction and performance
Aggressive Token Reduction
Maximum token reduction with semantic preservation
Key Techniques:
- Semantic structure compression
- Redundant attribute removal
- Smart whitespace optimization
- Context-aware element merging
Multi-Model Optimization
Target multiple AI models simultaneously
Key Techniques:
- Cross-model compatibility analysis
- Model-specific optimizations
- Universal token patterns
- Adaptive compression strategies
Dynamic Context Optimization
Runtime optimization based on usage patterns
Key Techniques:
- Usage pattern analysis
- Runtime element prioritization
- Adaptive compression levels
- Context-sensitive optimization
Hierarchical Structure Optimization
Advanced DOM tree restructuring
Key Techniques:
- DOM tree flattening
- Semantic grouping optimization
- Nested structure compression
- Parent-child relationship optimization
Enterprise Features
Advanced capabilities for large-scale optimization deployments
Custom Optimization Rules
Define domain-specific optimization patterns
- Rule-based optimization engine
- Custom attribute handling
- Business logic preservation
- Industry-specific templates
Performance Profiling
Deep analysis of optimization performance
- Token reduction analytics
- Processing time metrics
- Memory usage tracking
- Bottleneck identification
A/B Testing Framework
Compare optimization strategies scientifically
- Split testing configurations
- Statistical significance testing
- Performance comparison
- Automated winner selection
Enterprise Integration
Scale optimization across large organizations
- Centralized configuration management
- Team collaboration tools
- Audit logging and compliance
- Multi-environment deployment
Advanced Implementation
Production-ready code examples for advanced optimization scenarios
Advanced Configuration
Complex optimization settings for maximum performance
JavaScriptimport { WebMCPProcessor, OptimizationEngine } from '@webmcp/core';
const advancedConfig = {
// Multi-model optimization
models: {
primary: 'gpt-4o',
fallback: 'claude-3.5-sonnet',
comparison: ['gpt-4', 'gemini-pro']
},
// Aggressive optimization settings
optimization: {
level: 'aggressive',
strategies: [
'semantic_compression',
'hierarchical_restructuring',
'dynamic_context_optimization',
'cross_model_compatibility'
],
// Advanced token reduction settings
tokenReduction: {
target: 80,
minimum: 60,
preserveSemantics: true,
allowStructuralChanges: true
},
// Custom optimization rules
customRules: [
{
name: 'form_field_optimization',
pattern: /input[.*data-webmcp.*]/g,
handler: (element) => {
// Custom optimization logic
return optimizeFormField(element);
}
},
{
name: 'redundant_wrapper_removal',
selector: 'div.wrapper:only-child',
action: 'unwrap'
}
],
// Performance optimization
performance: {
parallelProcessing: true,
cacheResults: true,
batchSize: 50,
timeoutMs: 30000
}
},
// Advanced analytics
analytics: {
enabled: true,
detailed: true,
realTime: true,
// Custom metrics
customMetrics: [
'semantic_preservation_score',
'structural_complexity_reduction',
'cross_model_compatibility_score'
],
// A/B testing configuration
abTesting: {
enabled: true,
variants: [
{ name: 'conservative', level: 'moderate' },
{ name: 'aggressive', level: 'aggressive' },
{ name: 'experimental', level: 'experimental' }
],
trafficSplit: [0.4, 0.4, 0.2]
}
},
// Quality assurance
qualityAssurance: {
semanticValidation: true,
functionalityTesting: true,
performanceBaseline: {
tokenReductionMin: 60,
processingTimeMax: 5000,
accuracyMin: 95
}
}
};
// Initialize advanced processor
const processor = new WebMCPProcessor(advancedConfig);
// Custom optimization function
function optimizeFormField(element) {
const attributes = element.attributes;
const optimized = {};
// Intelligent attribute compression
for (const attr of attributes) {
if (attr.name.startsWith('data-webmcp-')) {
// Compress webMCP attributes
optimized[compressAttribute(attr.name)] = attr.value;
} else if (isEssentialAttribute(attr.name)) {
optimized[attr.name] = attr.value;
}
}
return {
tagName: element.tagName.toLowerCase(),
attributes: optimized,
innerHTML: element.innerHTML
};
}
function compressAttribute(attrName) {
const compressionMap = {
'data-webmcp-optimize': 'data-wo',
'data-webmcp-target': 'data-wt',
'data-webmcp-field': 'data-wf',
'data-webmcp-validate': 'data-wv'
};
return compressionMap[attrName] || attrName;
}
function isEssentialAttribute(attrName) {
const essential = ['id', 'name', 'type', 'required', 'class'];
return essential.includes(attrName);
}
// Advanced processing with multiple strategies
async function processWithAdvancedOptimization(htmlContent) {
try {
// Multi-strategy optimization
const strategies = ['conservative', 'aggressive', 'experimental'];
const results = await Promise.all(
strategies.map(strategy =>
processor.optimize(htmlContent, { strategy })
)
);
// Compare results and select best
const bestResult = selectBestOptimization(results);
// Additional post-processing
const finalResult = await postProcessOptimization(bestResult);
return finalResult;
} catch (error) {
console.error('Advanced optimization failed:', error);
throw error;
}
}
function selectBestOptimization(results) {
return results.reduce((best, current) => {
const bestScore = calculateOptimizationScore(best);
const currentScore = calculateOptimizationScore(current);
return currentScore > bestScore ? current : best;
});
}
function calculateOptimizationScore(result) {
const tokenReductionWeight = 0.4;
const semanticPreservationWeight = 0.3;
const performanceWeight = 0.3;
return (
result.tokenReduction * tokenReductionWeight +
result.semanticScore * semanticPreservationWeight +
result.performanceScore * performanceWeight
);
}
async function postProcessOptimization(result) {
// Additional optimization passes
const passes = [
'finalCompressionPass',
'semanticValidation',
'performanceOptimization'
];
let optimized = result;
for (const pass of passes) {
optimized = await processor.runOptimizationPass(optimized, pass);
}
return optimized;
}Custom Rule Engine
Build domain-specific optimization rules
JavaScriptimport { RuleEngine, OptimizationRule } from '@webmcp/advanced';
class AdvancedRuleEngine extends RuleEngine {
constructor() {
super();
this.initializeRules();
}
initializeRules() {
// E-commerce specific rules
this.addRule(new EcommerceFormRule());
this.addRule(new ProductCatalogRule());
this.addRule(new CheckoutOptimizationRule());
// Content management rules
this.addRule(new CMSFormRule());
this.addRule(new BlogOptimizationRule());
// Enterprise application rules
this.addRule(new EnterpriseFormRule());
this.addRule(new DashboardOptimizationRule());
}
}
// E-commerce optimization rule
class EcommerceFormRule extends OptimizationRule {
constructor() {
super('ecommerce_form_optimization');
this.priority = 10;
this.targets = ['form[data-type="checkout"]', 'form[data-type="product"]'];
}
canApply(element) {
return element.hasAttribute('data-ecommerce') ||
element.closest('[data-context="ecommerce"]');
}
apply(element) {
const optimizations = [];
// Optimize product selection fields
if (element.querySelector('[data-product-variant]')) {
optimizations.push(this.optimizeProductVariants(element));
}
// Optimize shipping information
if (element.querySelector('[data-shipping]')) {
optimizations.push(this.optimizeShippingFields(element));
}
// Optimize payment fields
if (element.querySelector('[data-payment]')) {
optimizations.push(this.optimizePaymentFields(element));
}
return {
element: this.applyOptimizations(element, optimizations),
tokenReduction: this.calculateReduction(optimizations),
confidence: 0.95
};
}
optimizeProductVariants(element) {
// Compress product variant selection
const variants = element.querySelectorAll('[data-product-variant]');
return {
type: 'product_variant_compression',
elements: variants,
reduction: 0.3
};
}
optimizeShippingFields(element) {
// Smart shipping field grouping
const shippingFields = element.querySelectorAll('[data-shipping]');
return {
type: 'shipping_field_grouping',
elements: shippingFields,
reduction: 0.25
};
}
optimizePaymentFields(element) {
// Secure payment field optimization
const paymentFields = element.querySelectorAll('[data-payment]');
return {
type: 'payment_field_optimization',
elements: paymentFields,
reduction: 0.2,
preserveSecurity: true
};
}
}
// Enterprise application rule
class EnterpriseFormRule extends OptimizationRule {
constructor() {
super('enterprise_form_optimization');
this.priority = 8;
this.targets = ['form[data-enterprise]', '.enterprise-form'];
}
apply(element) {
const context = this.analyzeEnterpriseContext(element);
switch (context.type) {
case 'data_entry':
return this.optimizeDataEntry(element, context);
case 'workflow':
return this.optimizeWorkflow(element, context);
case 'reporting':
return this.optimizeReporting(element, context);
default:
return this.optimizeGenericEnterprise(element, context);
}
}
analyzeEnterpriseContext(element) {
// Analyze form context and purpose
const attributes = Array.from(element.attributes);
const classes = element.className.split(' ');
return {
type: this.detectFormType(attributes, classes),
complexity: this.assessComplexity(element),
businessCriticality: this.assessCriticality(element),
userRole: this.detectUserRole(element)
};
}
optimizeDataEntry(element, context) {
// Optimize for high-volume data entry
const optimizations = [
this.groupRelatedFields(element),
this.optimizeValidationRules(element),
this.compressMetadata(element)
];
return this.applyOptimizations(element, optimizations);
}
optimizeWorkflow(element, context) {
// Optimize for workflow processes
const optimizations = [
this.optimizeWorkflowSteps(element),
this.compressStateInformation(element),
this.optimizeApprovalFields(element)
];
return this.applyOptimizations(element, optimizations);
}
}
// Dynamic rule loading
class DynamicRuleLoader {
constructor(ruleEngine) {
this.ruleEngine = ruleEngine;
this.loadedRules = new Set();
}
async loadRulesForContext(context) {
const rulesToLoad = this.identifyRequiredRules(context);
for (const ruleSpec of rulesToLoad) {
if (!this.loadedRules.has(ruleSpec.name)) {
const rule = await this.loadRule(ruleSpec);
this.ruleEngine.addRule(rule);
this.loadedRules.add(ruleSpec.name);
}
}
}
identifyRequiredRules(context) {
const rules = [];
// Industry-specific rules
if (context.industry) {
rules.push({ name: `${context.industry}_optimization`, type: 'industry' });
}
// Framework-specific rules
if (context.framework) {
rules.push({ name: `${context.framework}_integration`, type: 'framework' });
}
// Custom business rules
if (context.businessRules) {
context.businessRules.forEach(rule => {
rules.push({ name: rule, type: 'business' });
});
}
return rules;
}
async loadRule(ruleSpec) {
try {
// Dynamic rule loading from registry
const ruleModule = await import(`@webmcp/rules/${ruleSpec.type}/${ruleSpec.name}`);
return new ruleModule.default();
} catch (error) {
console.warn(`Failed to load rule ${ruleSpec.name}:`, error);
return null;
}
}
}
// Usage example
const ruleEngine = new AdvancedRuleEngine();
const dynamicLoader = new DynamicRuleLoader(ruleEngine);
// Process with context-aware rules
async function processWithAdvancedRules(htmlContent, context) {
// Load context-specific rules
await dynamicLoader.loadRulesForContext(context);
// Apply optimization with all rules
const result = await ruleEngine.optimize(htmlContent, {
context,
preserveBusinessLogic: true,
validateCompliance: true
});
return result;
}Performance Monitoring
Advanced performance tracking and optimization
JavaScriptimport { PerformanceMonitor, MetricsCollector } from '@webmcp/monitoring';
class AdvancedPerformanceMonitor extends PerformanceMonitor {
constructor(config) {
super(config);
this.metricsCollector = new MetricsCollector();
this.benchmarks = new Map();
this.alerts = new Map();
}
async monitorOptimization(processor, htmlContent, options = {}) {
const sessionId = this.generateSessionId();
const startTime = performance.now();
try {
// Pre-optimization metrics
const preMetrics = await this.collectPreOptimizationMetrics(htmlContent);
// Start monitoring
const monitor = this.startRealTimeMonitoring(sessionId);
// Run optimization with monitoring
const result = await this.monitoredOptimization(processor, htmlContent, options);
// Post-optimization metrics
const postMetrics = await this.collectPostOptimizationMetrics(result);
// Calculate performance insights
const insights = this.generatePerformanceInsights(preMetrics, postMetrics);
// Stop monitoring
monitor.stop();
return {
...result,
performance: {
sessionId,
duration: performance.now() - startTime,
metrics: { pre: preMetrics, post: postMetrics },
insights,
recommendations: this.generateRecommendations(insights)
}
};
} catch (error) {
this.recordError(sessionId, error);
throw error;
}
}
async collectPreOptimizationMetrics(htmlContent) {
return {
// Content analysis
contentSize: htmlContent.length,
elementCount: this.countElements(htmlContent),
complexityScore: this.calculateComplexity(htmlContent),
tokenEstimate: this.estimateTokens(htmlContent),
// Structure analysis
nestingDepth: this.calculateNestingDepth(htmlContent),
attributeCount: this.countAttributes(htmlContent),
redundancyScore: this.calculateRedundancy(htmlContent),
// Performance baseline
memoryUsage: this.getMemoryUsage(),
timestamp: Date.now()
};
}
async collectPostOptimizationMetrics(result) {
return {
// Optimization results
contentSize: result.optimizedHtml.length,
elementCount: this.countElements(result.optimizedHtml),
complexityScore: this.calculateComplexity(result.optimizedHtml),
actualTokens: result.tokenCount,
// Reduction metrics
sizeReduction: result.sizeReduction,
tokenReduction: result.tokenReduction,
complexityReduction: result.complexityReduction,
// Quality metrics
semanticScore: result.semanticPreservationScore,
functionalityScore: result.functionalityScore,
// Performance metrics
processingTime: result.processingTime,
memoryUsage: this.getMemoryUsage(),
timestamp: Date.now()
};
}
startRealTimeMonitoring(sessionId) {
const intervals = [];
// Memory monitoring
intervals.push(setInterval(() => {
this.recordMetric(sessionId, 'memory', this.getMemoryUsage());
}, 1000));
// CPU monitoring
intervals.push(setInterval(() => {
this.recordMetric(sessionId, 'cpu', this.getCPUUsage());
}, 2000));
// Progress monitoring
intervals.push(setInterval(() => {
this.recordMetric(sessionId, 'progress', this.getOptimizationProgress());
}, 500));
return {
stop: () => intervals.forEach(interval => clearInterval(interval))
};
}
async monitoredOptimization(processor, htmlContent, options) {
// Wrap processor methods with monitoring
const originalOptimize = processor.optimize.bind(processor);
processor.optimize = async (content, opts) => {
const stepStart = performance.now();
try {
const result = await originalOptimize(content, opts);
this.recordStep({
step: 'optimization',
duration: performance.now() - stepStart,
success: true,
metrics: this.extractStepMetrics(result)
});
return result;
} catch (error) {
this.recordStep({
step: 'optimization',
duration: performance.now() - stepStart,
success: false,
error: error.message
});
throw error;
}
};
return await processor.optimize(htmlContent, options);
}
generatePerformanceInsights(preMetrics, postMetrics) {
const insights = {
efficiency: {
tokenReductionRate: (preMetrics.tokenEstimate - postMetrics.actualTokens) / preMetrics.tokenEstimate,
processingEfficiency: postMetrics.tokenReduction / postMetrics.processingTime,
memoryEfficiency: (preMetrics.memoryUsage - postMetrics.memoryUsage) / preMetrics.memoryUsage
},
quality: {
semanticPreservation: postMetrics.semanticScore,
functionalityPreservation: postMetrics.functionalityScore,
overallQuality: (postMetrics.semanticScore + postMetrics.functionalityScore) / 2
},
performance: {
speedScore: this.calculateSpeedScore(postMetrics.processingTime),
scalabilityScore: this.calculateScalabilityScore(preMetrics, postMetrics),
reliabilityScore: this.calculateReliabilityScore()
}
};
// Calculate overall performance score
insights.overallScore = (
insights.efficiency.tokenReductionRate * 0.4 +
insights.quality.overallQuality * 0.3 +
insights.performance.speedScore * 0.3
);
return insights;
}
generateRecommendations(insights) {
const recommendations = [];
// Performance recommendations
if (insights.performance.speedScore < 0.7) {
recommendations.push({
type: 'performance',
priority: 'high',
message: 'Consider enabling parallel processing for better speed',
action: 'enable_parallel_processing'
});
}
// Quality recommendations
if (insights.quality.semanticPreservation < 0.8) {
recommendations.push({
type: 'quality',
priority: 'medium',
message: 'Reduce optimization aggressiveness to preserve semantics',
action: 'reduce_aggressiveness'
});
}
// Efficiency recommendations
if (insights.efficiency.tokenReductionRate < 0.5) {
recommendations.push({
type: 'efficiency',
priority: 'medium',
message: 'Enable advanced optimization strategies for better token reduction',
action: 'enable_advanced_strategies'
});
}
return recommendations;
}
// Benchmark comparison
async compareToBenchmark(metrics, benchmarkName) {
const benchmark = this.benchmarks.get(benchmarkName);
if (!benchmark) return null;
return {
performance: metrics.performance.speedScore / benchmark.speedScore,
quality: metrics.quality.overallQuality / benchmark.qualityScore,
efficiency: metrics.efficiency.tokenReductionRate / benchmark.reductionRate
};
}
// Alert system
checkAlerts(metrics) {
const triggeredAlerts = [];
for (const [alertName, alert] of this.alerts) {
if (alert.condition(metrics)) {
triggeredAlerts.push({
name: alertName,
severity: alert.severity,
message: alert.message,
value: alert.getValue ? alert.getValue(metrics) : null
});
}
}
return triggeredAlerts;
}
}
// Usage example
const monitor = new AdvancedPerformanceMonitor({
enableRealTime: true,
collectDetailedMetrics: true,
benchmarkComparison: true
});
// Set up alerts
monitor.addAlert('slow_processing', {
condition: (metrics) => metrics.performance.processingTime > 10000,
severity: 'warning',
message: 'Processing time exceeds 10 seconds'
});
monitor.addAlert('low_token_reduction', {
condition: (metrics) => metrics.efficiency.tokenReductionRate < 0.3,
severity: 'info',
message: 'Token reduction below 30%'
});
// Monitor optimization
async function runMonitoredOptimization(htmlContent) {
const result = await monitor.monitorOptimization(processor, htmlContent, {
enableAdvancedMetrics: true,
compareWithBenchmarks: ['standard', 'aggressive']
});
// Check for alerts
const alerts = monitor.checkAlerts(result.performance.metrics);
if (alerts.length > 0) {
console.warn('Performance alerts:', alerts);
}
// Apply recommendations
if (result.performance.recommendations.length > 0) {
console.log('Optimization recommendations:', result.performance.recommendations);
}
return result;
}Best Practices
Expert recommendations for successful advanced optimization deployments
Configuration
- Use progressive optimization levels for testing
- Enable semantic validation for critical forms
- Configure model-specific optimizations
- Implement proper error handling and fallbacks
Performance
- Enable parallel processing for batch operations
- Use caching for frequently optimized patterns
- Monitor memory usage during large operations
- Implement request throttling for API limits
Quality Assurance
- Validate optimization results against baselines
- Test cross-browser compatibility after optimization
- Verify accessibility standards compliance
- Monitor semantic preservation scores
Production Deployment
- Use staged rollouts for optimization changes
- Implement monitoring and alerting systems
- Maintain optimization result archives
- Set up automatic performance regression testing
Ready for Enterprise Deployment?
Scale your advanced optimizations across your organization with enterprise-grade features