chore: recovery checkpoint - v3.0 API successfully recovered

CRITICAL CHECKPOINT - DO NOT PUSH TO GITHUB

Recovery Status:
- Successfully recovered brainy.ts from compiled JavaScript
- All core v3.0 API methods functional (add, get, update, delete, relate, find, etc.)
- Neural subsystem intact (562KB embedded patterns, NLP working)
- Augmentation pipeline operational (20+ augmentations)
- HNSW clustering system complete
- Triple Intelligence compiled (needs constructor fix)
- Test suite validates functionality

Changes preserved:
- 898 files with changes from last 3 days
- 144,475 insertions
- All augmentation improvements
- All test coverage enhancements
- Complete v3.0 feature set

This is a LOCAL checkpoint only - contains recovered work after corruption incident.
Created backup in .backups/brainy-full-20250910-151314.tar.gz

Branch: recovery-checkpoint-20250910-151433
Date: Wed Sep 10 03:18:04 PM PDT 2025

.recovery-workspace/dist-backup-20250910-141917/augmentations/intelligentVerbScoring.d.ts

@@ -0,0 +1,158 @@
+import { ICognitionAugmentation, AugmentationResponse } from '../types/augmentations.js';
+/**
+ * Configuration options for the Intelligent Verb Scoring augmentation
+ */
+export interface IVerbScoringConfig {
+    /** Enable semantic proximity scoring based on entity embeddings */
+    enableSemanticScoring: boolean;
+    /** Enable frequency-based weight amplification */
+    enableFrequencyAmplification: boolean;
+    /** Enable temporal decay for weights */
+    enableTemporalDecay: boolean;
+    /** Decay rate per day for temporal scoring (0-1) */
+    temporalDecayRate: number;
+    /** Minimum weight threshold */
+    minWeight: number;
+    /** Maximum weight threshold */
+    maxWeight: number;
+    /** Base confidence score for new relationships */
+    baseConfidence: number;
+    /** Learning rate for adaptive scoring (0-1) */
+    learningRate: number;
+}
+/**
+ * Default configuration for the Intelligent Verb Scoring augmentation
+ */
+export declare const DEFAULT_VERB_SCORING_CONFIG: IVerbScoringConfig;
+/**
+ * Relationship statistics for learning and adaptation
+ */
+interface RelationshipStats {
+    count: number;
+    totalWeight: number;
+    averageWeight: number;
+    lastSeen: Date;
+    firstSeen: Date;
+    semanticSimilarity?: number;
+}
+/**
+ * Intelligent Verb Scoring Cognition Augmentation
+ *
+ * Automatically generates intelligent weight and confidence scores for verb relationships
+ * using semantic analysis, frequency patterns, and temporal factors.
+ */
+export declare class IntelligentVerbScoring implements ICognitionAugmentation {
+    readonly name = "intelligent-verb-scoring";
+    readonly description = "Automatically generates intelligent weight and confidence scores for verb relationships";
+    enabled: boolean;
+    private config;
+    private relationshipStats;
+    private brainyInstance;
+    private isInitialized;
+    constructor(config?: Partial<IVerbScoringConfig>);
+    initialize(): Promise<void>;
+    shutDown(): Promise<void>;
+    getStatus(): Promise<'active' | 'inactive' | 'error'>;
+    /**
+     * Set reference to the BrainyData instance for accessing graph data
+     */
+    setBrainyInstance(instance: any): void;
+    /**
+     * Main reasoning method for generating intelligent verb scores
+     */
+    reason(query: string, context?: Record<string, unknown>): AugmentationResponse<{
+        inference: string;
+        confidence: number;
+    }>;
+    infer(dataSubset: Record<string, unknown>): AugmentationResponse<Record<string, unknown>>;
+    executeLogic(ruleId: string, input: Record<string, unknown>): AugmentationResponse<boolean>;
+    /**
+     * Generate intelligent weight and confidence scores for a verb relationship
+     *
+     * @param sourceId - ID of the source entity
+     * @param targetId - ID of the target entity
+     * @param verbType - Type of the relationship
+     * @param existingWeight - Existing weight if any
+     * @param metadata - Additional metadata about the relationship
+     * @returns Computed weight and confidence scores
+     */
+    computeVerbScores(sourceId: string, targetId: string, verbType: string, existingWeight?: number, metadata?: any): Promise<{
+        weight: number;
+        confidence: number;
+        reasoning: string[];
+    }>;
+    /**
+     * Calculate semantic similarity between two entities using their embeddings
+     */
+    private calculateSemanticScore;
+    /**
+     * Calculate frequency-based boost for repeated relationships
+     */
+    private calculateFrequencyBoost;
+    /**
+     * Calculate temporal decay factor based on recency
+     */
+    private calculateTemporalFactor;
+    /**
+     * Calculate learning-based adjustment using historical patterns
+     */
+    private calculateLearningAdjustment;
+    /**
+     * Update relationship statistics for learning
+     */
+    private updateRelationshipStats;
+    /**
+     * Blend two scores using a weighted average
+     */
+    private blendScores;
+    /**
+     * Get current configuration
+     */
+    getConfig(): IVerbScoringConfig;
+    /**
+     * Update configuration
+     */
+    updateConfig(newConfig: Partial<IVerbScoringConfig>): void;
+    /**
+     * Get relationship statistics (for debugging/monitoring)
+     */
+    getRelationshipStats(): Map<string, RelationshipStats>;
+    /**
+     * Clear relationship statistics
+     */
+    clearStats(): void;
+    /**
+     * Provide feedback to improve future scoring
+     * This allows the system to learn from user corrections or validation
+     *
+     * @param sourceId - Source entity ID
+     * @param targetId - Target entity ID
+     * @param verbType - Relationship type
+     * @param feedbackWeight - The corrected/validated weight (0-1)
+     * @param feedbackConfidence - The corrected/validated confidence (0-1)
+     * @param feedbackType - Type of feedback ('correction', 'validation', 'enhancement')
+     */
+    provideFeedback(sourceId: string, targetId: string, verbType: string, feedbackWeight: number, feedbackConfidence?: number, feedbackType?: 'correction' | 'validation' | 'enhancement'): Promise<void>;
+    /**
+     * Get learning statistics for monitoring and debugging
+     */
+    getLearningStats(): {
+        totalRelationships: number;
+        averageConfidence: number;
+        feedbackCount: number;
+        topRelationships: Array<{
+            relationship: string;
+            count: number;
+            averageWeight: number;
+        }>;
+    };
+    /**
+     * Export learning data for backup or analysis
+     */
+    exportLearningData(): string;
+    /**
+     * Import learning data from backup
+     */
+    importLearningData(jsonData: string): void;
+}
+export {};