QE Code Intelligence

Purpose

Guide the use of v3's code intelligence capabilities including knowledge graph construction, semantic code search, dependency mapping, and context-aware code understanding with significant token reduction.

Activation

• When understanding unfamiliar code

• When searching for code semantically

• When analyzing dependencies

• When building code knowledge graphs

• When reducing context for AI operations

Quick Start

Index codebase into knowledge graph

aqe kg index --source src/ --incremental

Semantic code search

aqe kg search "authentication middleware" --limit 10

Query dependencies

aqe kg deps --file src/services/UserService.ts --depth 3

Get intelligent context

aqe kg context --query "how does payment processing work"

Agent Workflow

// Build knowledge graph Task("Index codebase", ` Build knowledge graph for the project:

• Parse all TypeScript files in src/
• Extract entities (classes, functions, types)
• Map relationships (imports, calls, inheritance)
• Generate embeddings for semantic search Store in AgentDB vector database. `, "qe-knowledge-graph")

// Semantic search Task("Find relevant code", ` Search for code related to "user authentication flow":

• Use semantic similarity (not just keyword)
• Include related functions and types
• Rank by relevance score
• Return with minimal context (80% token reduction) `, "qe-semantic-searcher")

Knowledge Graph Operations

1. Codebase Indexing

await knowledgeGraph.index({ source: 'src/**/*.ts', extraction: { entities: ['class', 'function', 'interface', 'type', 'variable'], relationships: ['imports', 'calls', 'extends', 'implements', 'uses'], metadata: ['jsdoc', 'complexity', 'lines'] }, embeddings: { model: 'code-embedding', dimensions: 384, normalize: true }, incremental: true // Only index changed files });

2. Semantic Search

await semanticSearcher.search({ query: 'payment processing with stripe', options: { similarity: 'cosine', threshold: 0.7, limit: 20, includeContext: true }, filters: { fileTypes: ['.ts', '.tsx'], excludePaths: ['node_modules', 'dist'] } });

3. Dependency Analysis

await dependencyMapper.analyze({ entry: 'src/services/OrderService.ts', depth: 3, direction: 'both', // imports and importedBy output: { graph: true, metrics: { afferentCoupling: true, efferentCoupling: true, instability: true } } });

Token Reduction Strategy

// Get context with 80% token reduction const context = await codeIntelligence.getOptimizedContext({ query: 'implement user registration', budget: 4000, // max tokens strategy: { relevanceRanking: true, summarization: true, codeCompression: true, deduplication: true }, include: { signatures: true, implementations: 'relevant-only', comments: 'essential', examples: 'top-3' } });

Knowledge Graph Schema

interface KnowledgeGraph { entities: { id: string; type: 'class' | 'function' | 'interface' | 'type' | 'file'; name: string; file: string; line: number; embedding: number[]; metadata: Record<string, any>; }[]; relationships: { source: string; target: string; type: 'imports' | 'calls' | 'extends' | 'implements' | 'uses'; weight: number; }[]; indexes: { byName: Map<string, string[]>; byFile: Map<string, string[]>; byType: Map<string, string[]>; }; }

Search Results

interface SearchResult { entity: { name: string; type: string; file: string; line: number; }; relevance: number; snippet: string; context: { before: string[]; after: string[]; related: string[]; }; explanation: string; }

CLI Examples

Full reindex

aqe kg index --source src/ --force

Search with filters

aqe kg search "database connection" --type function --file "*.service.ts"

Show entity details

aqe kg show --entity UserService --relations

Export graph

aqe kg export --format dot --output codebase.dot

Statistics

aqe kg stats

Coordination

Primary Agents: qe-knowledge-graph, qe-semantic-searcher, qe-dependency-mapper Coordinator: qe-code-intelligence-coordinator Related Skills: qe-test-generation, qe-defect-intelligence