memory_learning_stats
Retrieve comprehensive learning statistics and knowledge graph data to analyze documentation deployment patterns and repository insights.
Instructions
Get comprehensive learning and knowledge graph statistics
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| includeDetails | No | Include detailed statistics |
Implementation Reference
- src/memory/index.ts:177-190 (schema)Defines the input schema for the 'memory_learning_stats' tool, specifying an optional 'includeDetails' boolean parameter.
{ name: "memory_learning_stats", description: "Get comprehensive learning and knowledge graph statistics", inputSchema: { type: "object", properties: { includeDetails: { type: "boolean", description: "Include detailed statistics", default: true, }, }, }, }, - src/memory/learning.ts:567-624 (helper)IncrementalLearningSystem.getStatistics() method that computes and returns comprehensive learning statistics including patterns count, confidence, and insights.
async getStatistics(): Promise<{ totalPatterns: number; patternsByType: Record<string, number>; averageConfidence: number; learningVelocity: number; insights: string[]; }> { const stats = { totalPatterns: this.patterns.size, patternsByType: {} as Record<string, number>, averageConfidence: 0, learningVelocity: 0, insights: [] as string[], }; let totalConfidence = 0; for (const pattern of this.patterns.values()) { stats.patternsByType[pattern.type] = (stats.patternsByType[pattern.type] || 0) + 1; totalConfidence += pattern.confidence; } stats.averageConfidence = stats.totalPatterns > 0 ? totalConfidence / stats.totalPatterns : 0; // Calculate learning velocity (patterns learned in last week) const weekAgo = new Date(Date.now() - 7 * 24 * 60 * 60 * 1000); stats.learningVelocity = Array.from(this.patterns.values()).filter( (p) => new Date(p.lastUpdated) > weekAgo, ).length; // Generate insights if (stats.totalPatterns > 10) { stats.insights.push( `System has learned ${stats.totalPatterns} patterns with ${( stats.averageConfidence * 100 ).toFixed(0)}% average confidence`, ); } if (stats.learningVelocity > 0) { stats.insights.push( `Learning velocity: ${stats.learningVelocity} new patterns this week`, ); } const topPatternType = Object.entries(stats.patternsByType).sort( ([, a], [, b]) => b - a, )[0]; if (topPatternType) { stats.insights.push( `Most common pattern type: ${topPatternType[0]} (${topPatternType[1]} patterns)`, ); } return stats; } - KnowledgeGraph.getStatistics() method that returns detailed knowledge graph statistics such as node and edge counts by type.
async getStatistics(): Promise<{ nodeCount: number; edgeCount: number; nodesByType: Record<string, number>; edgesByType: Record<string, number>; averageConnectivity: number; mostConnectedNodes: Array<{ id: string; connections: number }>; }> { const nodesByType: Record<string, number> = {}; const edgesByType: Record<string, number> = {}; for (const node of this.nodes.values()) { nodesByType[node.type] = (nodesByType[node.type] || 0) + 1; } for (const edge of this.edges.values()) { edgesByType[edge.type] = (edgesByType[edge.type] || 0) + 1; } const connectivityCounts = Array.from(this.adjacencyList.entries()) .map(([id, connections]) => ({ id, connections: connections.size })) .sort((a, b) => b.connections - a.connections); const averageConnectivity = connectivityCounts.length > 0 ? connectivityCounts.reduce( (sum, { connections }) => sum + connections, 0, ) / connectivityCounts.length : 0; return { nodeCount: this.nodes.size, edgeCount: this.edges.size, nodesByType, edgesByType, averageConnectivity, mostConnectedNodes: connectivityCounts.slice(0, 10), }; } - src/memory/index.ts:90-805 (registration)Exports the memoryTools array which registers the memory_learning_stats tool among other memory-related tools.
export const memoryTools = [ { name: "memory_recall", description: "Recall memories about a project or topic", inputSchema: { type: "object", properties: { query: { type: "string", description: "Search query or project ID", }, type: { type: "string", enum: [ "analysis", "recommendation", "deployment", "configuration", "interaction", "all", ], description: "Type of memory to recall", }, limit: { type: "number", description: "Maximum number of memories to return", default: 10, }, }, required: ["query"], }, }, { name: "memory_intelligent_analysis", description: "Get intelligent analysis with patterns, predictions, and recommendations", inputSchema: { type: "object", properties: { projectPath: { type: "string", description: "Path to the project for analysis", }, baseAnalysis: { type: "object", description: "Base analysis data to enhance", }, }, required: ["projectPath", "baseAnalysis"], }, }, { name: "memory_enhanced_recommendation", description: "Get enhanced recommendations using learning and knowledge graph", inputSchema: { type: "object", properties: { projectPath: { type: "string", description: "Path to the project", }, baseRecommendation: { type: "object", description: "Base recommendation to enhance", }, projectFeatures: { type: "object", properties: { language: { type: "string" }, framework: { type: "string" }, size: { type: "string", enum: ["small", "medium", "large"] }, complexity: { type: "string", enum: ["simple", "moderate", "complex"], }, hasTests: { type: "boolean" }, hasCI: { type: "boolean" }, hasDocs: { type: "boolean" }, isOpenSource: { type: "boolean" }, }, required: ["language"], }, }, required: ["projectPath", "baseRecommendation", "projectFeatures"], }, }, { name: "memory_learning_stats", description: "Get comprehensive learning and knowledge graph statistics", inputSchema: { type: "object", properties: { includeDetails: { type: "boolean", description: "Include detailed statistics", default: true, }, }, }, }, { name: "memory_knowledge_graph", description: "Query the knowledge graph for relationships and paths", inputSchema: { type: "object", properties: { query: { type: "object", properties: { nodeTypes: { type: "array", items: { type: "string" }, description: "Filter by node types", }, edgeTypes: { type: "array", items: { type: "string" }, description: "Filter by edge types", }, startNode: { type: "string", description: "Starting node for path queries", }, maxDepth: { type: "number", description: "Maximum path depth", default: 3, }, }, }, }, required: ["query"], }, }, { name: "memory_contextual_search", description: "Perform contextual memory retrieval with intelligent ranking", inputSchema: { type: "object", properties: { query: { type: "string", description: "Search query", }, context: { type: "object", properties: { currentProject: { type: "object", properties: { path: { type: "string" }, language: { type: "string" }, framework: { type: "string" }, size: { type: "string", enum: ["small", "medium", "large"] }, }, }, userIntent: { type: "object", properties: { action: { type: "string", enum: [ "analyze", "recommend", "deploy", "troubleshoot", "learn", ], }, urgency: { type: "string", enum: ["low", "medium", "high"] }, experience: { type: "string", enum: ["novice", "intermediate", "expert"], }, }, }, temporalContext: { type: "object", properties: { recency: { type: "string", enum: ["recent", "all", "historical"], }, timeRange: { type: "object", properties: { start: { type: "string" }, end: { type: "string" }, }, }, }, }, }, }, options: { type: "object", properties: { maxResults: { type: "number", default: 10 }, minRelevance: { type: "number", default: 0.3 }, includeReasoning: { type: "boolean", default: true }, }, }, }, required: ["query", "context"], }, }, { name: "memory_agent_network", description: "Manage multi-agent memory sharing and collaboration", inputSchema: { type: "object", properties: { action: { type: "string", enum: [ "register_agent", "share_memory", "sync_request", "get_insights", "network_status", ], description: "Action to perform", }, agentInfo: { type: "object", properties: { name: { type: "string" }, capabilities: { type: "array", items: { type: "string" } }, specializations: { type: "array", items: { type: "string" } }, trustLevel: { type: "string", enum: ["low", "medium", "high", "trusted"], }, }, }, memoryId: { type: "string", description: "Memory ID for sharing operations", }, targetAgent: { type: "string", description: "Target agent for sync operations", }, options: { type: "object", properties: { anonymize: { type: "boolean", default: false }, requireValidation: { type: "boolean", default: false }, }, }, }, required: ["action"], }, }, { name: "memory_insights", description: "Get insights and patterns from memory", inputSchema: { type: "object", properties: { projectId: { type: "string", description: "Project ID to analyze", }, timeRange: { type: "object", properties: { start: { type: "string", format: "date-time" }, end: { type: "string", format: "date-time" }, }, description: "Time range for analysis", }, }, }, }, { name: "memory_similar", description: "Find similar projects from memory", inputSchema: { type: "object", properties: { analysisId: { type: "string", description: "Analysis ID to find similar projects for", }, limit: { type: "number", description: "Maximum number of similar projects", default: 5, }, }, required: ["analysisId"], }, }, { name: "memory_export", description: "Export memories to JSON or CSV", inputSchema: { type: "object", properties: { format: { type: "string", enum: ["json", "csv"], description: "Export format", default: "json", }, filter: { type: "object", properties: { type: { type: "string" }, projectId: { type: "string" }, startDate: { type: "string", format: "date-time" }, endDate: { type: "string", format: "date-time" }, }, description: "Filter memories to export", }, }, }, }, { name: "memory_cleanup", description: "Clean up old memories", inputSchema: { type: "object", properties: { daysToKeep: { type: "number", description: "Number of days of memories to keep", default: 30, }, dryRun: { type: "boolean", description: "Preview what would be deleted without actually deleting", default: false, }, }, }, }, { name: "memory_pruning", description: "Intelligent memory pruning and optimization", inputSchema: { type: "object", properties: { policy: { type: "object", properties: { maxAge: { type: "number", description: "Maximum age in days", default: 180, }, maxSize: { type: "number", description: "Maximum storage size in MB", default: 500, }, maxEntries: { type: "number", description: "Maximum number of entries", default: 50000, }, preservePatterns: { type: "array", items: { type: "string" }, description: "Pattern types to preserve", }, compressionThreshold: { type: "number", description: "Compress entries older than X days", default: 30, }, redundancyThreshold: { type: "number", description: "Remove similar entries with similarity > X", default: 0.85, }, }, }, dryRun: { type: "boolean", description: "Preview pruning without executing", default: false, }, }, }, }, { name: "memory_temporal_analysis", description: "Analyze temporal patterns and trends in memory data", inputSchema: { type: "object", properties: { query: { type: "object", properties: { timeRange: { type: "object", properties: { start: { type: "string", format: "date-time" }, end: { type: "string", format: "date-time" }, }, }, granularity: { type: "string", enum: ["hour", "day", "week", "month", "year"], default: "day", }, aggregation: { type: "string", enum: ["count", "success_rate", "activity_level", "diversity"], default: "count", }, filters: { type: "object", properties: { types: { type: "array", items: { type: "string" } }, projects: { type: "array", items: { type: "string" } }, outcomes: { type: "array", items: { type: "string" } }, tags: { type: "array", items: { type: "string" } }, }, }, }, }, analysisType: { type: "string", enum: ["patterns", "metrics", "predictions", "insights"], default: "patterns", }, }, }, }, { name: "memory_visualization", description: "Generate visual representations of memory data", inputSchema: { type: "object", properties: { visualizationType: { type: "string", enum: [ "dashboard", "timeline", "network", "heatmap", "distribution", "trends", "custom", ], default: "dashboard", }, options: { type: "object", properties: { timeRange: { type: "object", properties: { start: { type: "string", format: "date-time" }, end: { type: "string", format: "date-time" }, }, }, includeCharts: { type: "array", items: { type: "string" } }, config: { type: "object", properties: { width: { type: "number", default: 800 }, height: { type: "number", default: 600 }, theme: { type: "string", enum: ["light", "dark", "auto"], default: "light", }, exportFormat: { type: "string", enum: ["svg", "png", "json", "html"], default: "svg", }, interactive: { type: "boolean", default: true }, }, }, }, }, customVisualization: { type: "object", properties: { type: { type: "string", enum: [ "line", "bar", "scatter", "heatmap", "network", "sankey", "treemap", "timeline", ], }, query: { type: "object", properties: { filters: { type: "object" }, groupBy: { type: "string" }, aggregation: { type: "string" }, }, }, }, }, }, }, }, { name: "memory_export_advanced", description: "Advanced memory export with multiple formats and options", inputSchema: { type: "object", properties: { outputPath: { type: "string", description: "Output file path" }, options: { type: "object", properties: { format: { type: "string", enum: [ "json", "jsonl", "csv", "xml", "yaml", "sqlite", "archive", ], default: "json", }, compression: { type: "string", enum: ["gzip", "zip", "none"], default: "none", }, includeMetadata: { type: "boolean", default: true }, includeLearning: { type: "boolean", default: true }, includeKnowledgeGraph: { type: "boolean", default: true }, filters: { type: "object", properties: { types: { type: "array", items: { type: "string" } }, dateRange: { type: "object", properties: { start: { type: "string", format: "date-time" }, end: { type: "string", format: "date-time" }, }, }, projects: { type: "array", items: { type: "string" } }, tags: { type: "array", items: { type: "string" } }, outcomes: { type: "array", items: { type: "string" } }, }, }, anonymize: { type: "object", properties: { enabled: { type: "boolean", default: false }, fields: { type: "array", items: { type: "string" } }, method: { type: "string", enum: ["hash", "remove", "pseudonymize"], default: "hash", }, }, }, encryption: { type: "object", properties: { enabled: { type: "boolean", default: false }, algorithm: { type: "string", enum: ["aes-256-gcm", "aes-192-gcm", "aes-128-gcm"], default: "aes-256-gcm", }, password: { type: "string" }, }, }, }, }, }, required: ["outputPath"], }, }, { name: "memory_import_advanced", description: "Advanced memory import with validation and conflict resolution", inputSchema: { type: "object", properties: { inputPath: { type: "string", description: "Input file path" }, options: { type: "object", properties: { format: { type: "string", enum: [ "json", "jsonl", "csv", "xml", "yaml", "sqlite", "archive", ], default: "json", }, mode: { type: "string", enum: ["merge", "replace", "append", "update"], default: "merge", }, validation: { type: "string", enum: ["strict", "loose", "none"], default: "strict", }, conflictResolution: { type: "string", enum: ["skip", "overwrite", "merge", "rename"], default: "skip", }, backup: { type: "boolean", default: true }, dryRun: { type: "boolean", default: false }, mapping: { type: "object", description: "Field mapping for different schemas", }, transformation: { type: "object", properties: { enabled: { type: "boolean", default: false }, rules: { type: "array", items: { type: "object", properties: { field: { type: "string" }, operation: { type: "string", enum: ["convert", "transform", "validate"], }, params: { type: "object" }, }, }, }, }, }, }, }, }, required: ["inputPath"], }, }, { name: "memory_migration", description: "Create and execute migration plans between different memory systems", inputSchema: { type: "object", properties: { action: { type: "string", enum: ["create_plan", "execute_migration", "validate_compatibility"], default: "create_plan", }, sourcePath: { type: "string", description: "Source data path" }, migrationPlan: { type: "object", properties: { sourceSystem: { type: "string" }, targetSystem: { type: "string", default: "DocuMCP" }, mapping: { type: "object" }, transformations: { type: "array" }, validation: { type: "array" }, postProcessing: { type: "array", items: { type: "string" } }, }, }, sourceSchema: { type: "object", description: "Source system schema" }, targetSchema: { type: "object", description: "Target system schema" }, options: { type: "object", properties: { autoMap: { type: "boolean", default: true }, preserveStructure: { type: "boolean", default: true }, customMappings: { type: "object" }, }, }, }, }, }, { name: "memory_optimization_metrics", description: "Get comprehensive optimization metrics and recommendations", inputSchema: { type: "object", properties: { includeRecommendations: { type: "boolean", default: true }, timeRange: { type: "object", properties: { start: { type: "string", format: "date-time" }, end: { type: "string", format: "date-time" }, }, }, }, }, }, ];