Orchestrator MCP

/** * Context Engine Workflows * * Predefined workflows that leverage large context capabilities * to achieve context engine functionality through AI orchestration */ import type { WorkflowDefinition } from '../config/workflows.js'; /** * Intelligence Layer Analysis Workflow * Replicates the query: "Show me the current intelligence layer implementation" */ export const INTELLIGENCE_ANALYSIS_WORKFLOW: WorkflowDefinition = { id: 'intelligence_layer_analysis', name: 'Intelligence Layer Analysis', description: 'Analyze intelligence layer implementation vs placeholders using large context', category: 'analysis', timeout: 120000, // 2 minutes steps: [ { id: 'check_memory', tool: 'memory_search', action: 'search', parameters: { query: 'intelligence layer analysis implementation placeholder', entityTypes: ['analysis', 'codebase'] } }, { id: 'discover_files', tool: 'filesystem_search', action: 'search', parameters: { patterns: [ 'src/intelligence/**/*.ts', 'src/ai/**/*.ts', 'src/context/**/*.ts', '**/quality*.ts', '**/analysis*.ts', '**/codebase*.ts' ], maxResults: 50 } }, { id: 'load_context', tool: 'context_loader', action: 'load_large_context', parameters: { files: '{{discover_files.result}}', maxTokens: 800000, query: 'intelligence layer implementation analysis' } }, { id: 'analyze_with_gemini', tool: 'ai_analysis', action: 'large_context_analysis', parameters: { model: 'google/gemini-pro-1.5', context: '{{load_context.result}}', query: 'Show me the current intelligence layer implementation, specifically the codebase analysis, quality assessment, and any existing context management or indexing capabilities. I want to understand what\'s already implemented vs what\'s placeholder code.', analysisType: 'implementation_vs_placeholder' } }, { id: 'store_insights', tool: 'memory_create_entity', action: 'create', parameters: { name: 'intelligence_layer_analysis_{{timestamp}}', entityType: 'analysis', observations: [ 'Analysis type: Intelligence layer implementation review', 'Query: {{original_query}}', 'Summary: {{analyze_with_gemini.summary}}', 'Files analyzed: {{analyze_with_gemini.relevantFiles}}', 'Confidence: {{analyze_with_gemini.confidence}}' ] } } ] }; /** * Codebase Quality Assessment Workflow */ export const QUALITY_ASSESSMENT_WORKFLOW: WorkflowDefinition = { id: 'codebase_quality_assessment', name: 'Codebase Quality Assessment', description: 'Comprehensive quality assessment using large context analysis', category: 'analysis', timeout: 180000, // 3 minutes steps: [ { id: 'get_directory_structure', tool: 'filesystem_list_directory', action: 'list', parameters: { path: '{{working_directory}}', recursive: true, maxDepth: 3 } }, { id: 'sample_key_files', tool: 'filesystem_search', action: 'search', parameters: { patterns: [ 'src/**/*.ts', 'src/**/*.js', 'package.json', 'tsconfig.json', '**/*test*.ts', '**/*spec*.ts' ], maxResults: 100 } }, { id: 'run_security_scan', tool: 'semgrep_scan', action: 'scan', parameters: { path: '{{working_directory}}', rules: ['security', 'best-practices'] }, conditions: [ { type: 'failure', nextStep: 'load_context' } // Continue even if semgrep fails ] }, { id: 'load_context', tool: 'context_loader', action: 'load_large_context', parameters: { files: '{{sample_key_files.result}}', maxTokens: 900000, query: 'code quality assessment' } }, { id: 'quality_analysis', tool: 'ai_analysis', action: 'large_context_analysis', parameters: { model: 'google/gemini-pro-1.5', context: '{{load_context.result}}', securityFindings: '{{run_security_scan.result}}', query: 'Assess the overall code quality of this codebase including maintainability, readability, testability, performance, and security. Provide specific recommendations.', analysisType: 'quality_assessment' } }, { id: 'store_quality_insights', tool: 'memory_create_entity', action: 'create', parameters: { name: 'quality_assessment_{{timestamp}}', entityType: 'quality_analysis', observations: [ 'Analysis type: Code quality assessment', 'Overall score: {{quality_analysis.overallScore}}', 'Key issues: {{quality_analysis.keyIssues}}', 'Recommendations: {{quality_analysis.recommendations}}', 'Security findings: {{run_security_scan.issueCount}}' ] } } ] }; /** * Architecture Analysis Workflow */ export const ARCHITECTURE_ANALYSIS_WORKFLOW: WorkflowDefinition = { id: 'architecture_analysis', name: 'Architecture Analysis', description: 'Analyze system architecture and design patterns using large context', category: 'analysis', timeout: 150000, // 2.5 minutes steps: [ { id: 'find_architectural_files', tool: 'filesystem_search', action: 'search', parameters: { patterns: [ 'src/**/*.ts', 'package.json', 'tsconfig.json', 'README.md', 'docs/**/*.md', '**/index.ts', '**/manager.ts', '**/orchestrator.ts', '**/engine.ts' ], maxResults: 80 } }, { id: 'analyze_dependencies', tool: 'filesystem_read_file', action: 'read', parameters: { path: 'package.json' } }, { id: 'load_architectural_context', tool: 'context_loader', action: 'load_large_context', parameters: { files: '{{find_architectural_files.result}}', maxTokens: 850000, query: 'architecture analysis design patterns' } }, { id: 'architectural_analysis', tool: 'ai_analysis', action: 'large_context_analysis', parameters: { model: 'google/gemini-pro-1.5', context: '{{load_architectural_context.result}}', dependencies: '{{analyze_dependencies.result}}', query: 'Analyze the system architecture, identify design patterns, assess architectural quality, and provide recommendations for improvements.', analysisType: 'architecture_analysis' } }, { id: 'store_architecture_insights', tool: 'memory_create_entity', action: 'create', parameters: { name: 'architecture_analysis_{{timestamp}}', entityType: 'architecture_analysis', observations: [ 'Analysis type: System architecture review', 'Architecture pattern: {{architectural_analysis.pattern}}', 'Strengths: {{architectural_analysis.strengths}}', 'Weaknesses: {{architectural_analysis.weaknesses}}', 'Recommendations: {{architectural_analysis.recommendations}}' ] } } ] }; /** * Semantic Code Search Workflow */ export const SEMANTIC_SEARCH_WORKFLOW: WorkflowDefinition = { id: 'semantic_code_search', name: 'Semantic Code Search', description: 'Search codebase using natural language with large context understanding', category: 'analysis', timeout: 90000, // 1.5 minutes variables: { search_query: '', max_results: 20 }, steps: [ { id: 'check_previous_searches', tool: 'memory_search', action: 'search', parameters: { query: '{{search_query}}', entityTypes: ['search_result', 'analysis'] } }, { id: 'discover_relevant_files', tool: 'ai_file_discovery', action: 'discover', parameters: { query: '{{search_query}}', workingDirectory: '{{working_directory}}', maxFiles: 50 } }, { id: 'load_search_context', tool: 'context_loader', action: 'load_large_context', parameters: { files: '{{discover_relevant_files.result}}', maxTokens: 700000, query: '{{search_query}}' } }, { id: 'semantic_analysis', tool: 'ai_analysis', action: 'large_context_analysis', parameters: { model: 'google/gemini-pro-1.5', context: '{{load_search_context.result}}', query: '{{search_query}}', analysisType: 'semantic_search', maxResults: '{{max_results}}' } }, { id: 'store_search_result', tool: 'memory_create_entity', action: 'create', parameters: { name: 'search_result_{{timestamp}}', entityType: 'search_result', observations: [ 'Search query: {{search_query}}', 'Results found: {{semantic_analysis.resultsCount}}', 'Relevant files: {{semantic_analysis.relevantFiles}}', 'Key findings: {{semantic_analysis.summary}}' ] } } ] }; /** * All available context engine workflows */ export const CONTEXT_ENGINE_WORKFLOWS = { INTELLIGENCE_ANALYSIS_WORKFLOW, QUALITY_ASSESSMENT_WORKFLOW, ARCHITECTURE_ANALYSIS_WORKFLOW, SEMANTIC_SEARCH_WORKFLOW } as const;