# Knowledge Generation Framework Design

## Overview

The Knowledge Generation framework implements advanced prompting techniques to generate domain-specific architectural knowledge before making decisions. This enhances the accuracy and context-awareness of all MCP ADR Analysis Server tools while maintaining the 100% prompt-driven architecture.

## Core Concept

**Knowledge Generation Prompting** works by:
1. **Domain Analysis**: Identify the architectural domain and context
2. **Knowledge Generation**: Generate relevant domain-specific knowledge
3. **Knowledge Integration**: Combine generated knowledge with task prompts
4. **Decision Making**: Use enhanced prompts for better decision quality

## Architecture Integration

### Existing Components Integration
- **PromptObject Interface**: Knowledge generation returns PromptObject format
- **combinePrompts()**: Combines knowledge prompts with task prompts
- **Cache System**: Caches generated knowledge for performance
- **Security Validation**: Validates generated knowledge content

### Framework Components
```
Knowledge Generation Framework
├── Domain Templates (Web, Mobile, Microservices, etc.)
├── Knowledge Generator (Core generation logic)
├── Knowledge Cache (Persistent knowledge storage)
├── Integration Layer (Tool integration utilities)
└── Configuration (Settings and customization)
```

## Interface Definitions

### Core Knowledge Interfaces
```typescript
export interface DomainKnowledge {
  domain: ArchitecturalDomain;
  knowledge: KnowledgeItem[];
  confidence: number;
  timestamp: string;
  sources: string[];
  metadata: KnowledgeMetadata;
}

export interface KnowledgeItem {
  category: KnowledgeCategory;
  title: string;
  content: string;
  relevance: number;
  evidence: string[];
  tags: string[];
}

export interface KnowledgeGenerationConfig {
  domains: ArchitecturalDomain[];
  depth: 'basic' | 'intermediate' | 'advanced';
  cacheEnabled: boolean;
  cacheTTL: number;
  securityValidation: boolean;
  customTemplates?: DomainTemplate[];
}

export interface KnowledgeGenerationResult {
  knowledgePrompt: PromptObject;
  enhancedPrompt: PromptObject;
  cacheKey: string;
  metadata: GenerationMetadata;
}
```

### Domain Categories
```typescript
export type ArchitecturalDomain = 
  | 'web-applications'
  | 'mobile-applications' 
  | 'microservices'
  | 'database-design'
  | 'cloud-infrastructure'
  | 'devops-cicd'
  | 'security-patterns'
  | 'performance-optimization'
  | 'api-design'
  | 'data-architecture';

export type KnowledgeCategory =
  | 'best-practices'
  | 'design-patterns'
  | 'anti-patterns'
  | 'technology-specific'
  | 'performance-considerations'
  | 'security-guidelines'
  | 'scalability-patterns'
  | 'testing-strategies';
```

## Domain Knowledge Templates

### Web Applications Template
```typescript
const webApplicationsTemplate: DomainTemplate = {
  domain: 'web-applications',
  categories: [
    {
      category: 'best-practices',
      items: [
        'Component-based architecture principles',
        'State management patterns (Redux, Zustand, Context)',
        'Performance optimization techniques',
        'Accessibility (a11y) guidelines',
        'SEO optimization strategies'
      ]
    },
    {
      category: 'design-patterns',
      items: [
        'Model-View-Controller (MVC)',
        'Component composition patterns',
        'Higher-Order Components (HOCs)',
        'Render props pattern',
        'Custom hooks pattern'
      ]
    }
  ]
};
```

### Microservices Template
```typescript
const microservicesTemplate: DomainTemplate = {
  domain: 'microservices',
  categories: [
    {
      category: 'best-practices',
      items: [
        'Service decomposition strategies',
        'API gateway patterns',
        'Service mesh architecture',
        'Event-driven communication',
        'Distributed data management'
      ]
    },
    {
      category: 'anti-patterns',
      items: [
        'Distributed monolith',
        'Chatty interfaces',
        'Shared databases',
        'Synchronous communication overuse'
      ]
    }
  ]
};
```

## Core Functions

### Primary Knowledge Generation Function
```typescript
export async function generateArchitecturalKnowledge(
  context: ArchitecturalContext,
  config: KnowledgeGenerationConfig = {}
): Promise<KnowledgeGenerationResult>
```

### Domain Detection Function
```typescript
export async function detectArchitecturalDomains(
  projectContext: ProjectContext
): Promise<ArchitecturalDomain[]>
```

### Knowledge Enhancement Function
```typescript
export async function enhancePromptWithKnowledge(
  originalPrompt: PromptObject,
  domains: ArchitecturalDomain[],
  config: KnowledgeGenerationConfig = {}
): Promise<PromptObject>
```

## Caching Strategy

### Cache Key Generation
```typescript
function generateKnowledgeCacheKey(
  domains: ArchitecturalDomain[],
  context: ArchitecturalContext,
  config: KnowledgeGenerationConfig
): string {
  return `knowledge:${domains.join('+')}-${hashContext(context)}-${hashConfig(config)}`;
}
```

### Cache TTL Strategy
- **Basic Knowledge**: 24 hours (stable architectural principles)
- **Technology-Specific**: 6 hours (evolving best practices)
- **Project-Specific**: 1 hour (context-dependent knowledge)

## Security Validation

### Knowledge Content Validation
1. **Source Verification**: Ensure knowledge comes from trusted sources
2. **Content Sanitization**: Remove potentially harmful content
3. **Relevance Validation**: Verify knowledge relevance to context
4. **Quality Assessment**: Evaluate knowledge quality and accuracy

### Security Checks
```typescript
export interface KnowledgeSecurityCheck {
  contentSafety: boolean;
  sourceReliability: number;
  relevanceScore: number;
  qualityScore: number;
  warnings: string[];
}
```

## Integration Patterns

### Tool Integration Example
```typescript
// In suggest_adrs tool
const knowledgeResult = await generateArchitecturalKnowledge(
  { domains: ['web-applications', 'api-design'], projectContext },
  { depth: 'intermediate', cacheEnabled: true }
);

const enhancedPrompt = combinePrompts(
  knowledgeResult.knowledgePrompt,
  originalAdrPrompt
);
```

### Configuration Integration
```typescript
export interface ToolKnowledgeConfig {
  enableKnowledgeGeneration: boolean;
  domains: ArchitecturalDomain[];
  knowledgeDepth: 'basic' | 'intermediate' | 'advanced';
  cacheStrategy: 'aggressive' | 'moderate' | 'minimal';
}
```

## Usage Patterns

### Pattern 1: Domain-Aware ADR Suggestions
1. Detect project domains from codebase analysis
2. Generate domain-specific architectural knowledge
3. Enhance ADR suggestion prompts with knowledge
4. Cache knowledge for subsequent suggestions

### Pattern 2: Context-Enhanced Analysis
1. Analyze project structure and technologies
2. Generate relevant architectural knowledge
3. Combine knowledge with analysis prompts
4. Provide context-aware recommendations

### Pattern 3: Knowledge-Driven Research Questions
1. Identify knowledge gaps in project context
2. Generate domain expertise knowledge
3. Create research questions based on knowledge
4. Enhance research planning with domain insights

## Performance Considerations

### Optimization Strategies
1. **Lazy Loading**: Load domain templates only when needed
2. **Incremental Generation**: Generate knowledge incrementally
3. **Parallel Processing**: Generate knowledge for multiple domains in parallel
4. **Smart Caching**: Cache at multiple levels (domain, context, config)

### Resource Management
- **Memory Usage**: Limit concurrent knowledge generation
- **Cache Size**: Implement cache size limits and cleanup
- **Generation Time**: Set timeouts for knowledge generation
- **Quality vs Speed**: Balance knowledge depth with generation time

## Future Enhancements

### Planned Features
1. **Custom Domain Templates**: User-defined domain knowledge
2. **Knowledge Learning**: Learn from successful knowledge applications
3. **Knowledge Validation**: Validate knowledge against project outcomes
4. **Knowledge Sharing**: Share knowledge across projects and teams

### Integration Opportunities
1. **APE Integration**: Optimize knowledge generation prompts
2. **Reflexion Integration**: Learn from knowledge effectiveness
3. **External Sources**: Integrate with external knowledge bases
4. **Team Knowledge**: Incorporate team-specific knowledge

## Implementation Roadmap

### Phase 1: Core Framework (Week 1-2)
- Implement basic knowledge generation
- Create domain templates
- Integrate with existing prompt system
- Add basic caching

### Phase 2: Advanced Features (Week 3-4)
- Add security validation
- Implement configuration system
- Create tool integration utilities
- Add performance optimizations

### Phase 3: Enhancement & Testing (Week 5-6)
- Comprehensive testing
- Performance tuning
- Documentation completion
- Integration with priority tools

This framework design provides a solid foundation for implementing Knowledge Generation across the MCP ADR Analysis Server while maintaining architectural consistency and security requirements.
