claude-usage-tracker/dist/deep-analysis.d.ts

Advanced analytics for Claude Code usage with cost optimization, conversation length analysis, and rate limit tracking

import type { UsageEntry } from "./types.js";
export interface DataQualityReport {
    totalEntries: number;
    validEntries: number;
    invalidEntries: number;
    duplicateEntries: number;
    dateRange: {
        earliest: string;
        latest: string;
        spanDays: number;
    };
    modelDistribution: Record<string, number>;
    conversationDistribution: {
        totalConversations: number;
        avgMessagesPerConversation: number;
        shortConversations: number;
        mediumConversations: number;
        longConversations: number;
    };
    costDistribution: {
        totalCost: number;
        medianCost: number;
        top10PercentCost: number;
        costPerModel: Record<string, number>;
    };
    tokenDistribution: {
        totalTokens: number;
        avgPromptTokens: number;
        avgCompletionTokens: number;
        cacheTokens: number;
        extremeEntries: Array<{
            type: "high_tokens" | "low_tokens" | "high_cost";
            conversationId: string;
            value: number;
        }>;
    };
    anomalies: Array<{
        type: string;
        description: string;
        severity: "low" | "medium" | "high";
        affectedEntries: number;
    }>;
}
export interface UsageHeatmap {
    hourlyHeatmap: Array<{
        hour: number;
        dayOfWeek: number;
        totalCost: number;
        conversationCount: number;
        avgEfficiency: number;
    }>;
    monthlyTrends: Array<{
        month: string;
        totalCost: number;
        totalTokens: number;
        conversationCount: number;
        avgEfficiency: number;
        topModel: string;
    }>;
    efficiencyDistribution: Array<{
        range: string;
        count: number;
        percentage: number;
    }>;
}
export interface ConversationFlowAnalysis {
    conversationJourneys: Array<{
        conversationId: string;
        startTime: string;
        endTime: string;
        messageCount: number;
        totalCost: number;
        efficiency: number;
        modelSwitches: number;
        avgResponseTime: number;
        peakActivity: {
            hour: number;
            burstCount: number;
        };
        conversationType: "sprint" | "marathon" | "interrupted" | "focused";
    }>;
    flowPatterns: Array<{
        pattern: string;
        frequency: number;
        avgCost: number;
        successRate: number;
    }>;
}
export interface CostDriverAnalysis {
    primaryDrivers: Array<{
        factor: string;
        impact: number;
        description: string;
        recommendedAction: string;
    }>;
    modelUsagePattern: {
        opusUsage: {
            percentage: number;
            appropriateUsage: number;
            wastedSpend: number;
        };
        sonnetUsage: {
            percentage: number;
            missedOpportunities: number;
            underutilization: number;
        };
    };
    seasonalPatterns: Array<{
        period: string;
        avgDailyCost: number;
        efficiency: number;
        explanation: string;
    }>;
}
export interface DeepInsights {
    dataQuality: DataQualityReport;
    usageHeatmap: UsageHeatmap;
    conversationFlow: ConversationFlowAnalysis;
    costDrivers: CostDriverAnalysis;
    recommendations: Array<{
        category: "cost" | "efficiency" | "workflow" | "data_quality";
        priority: "high" | "medium" | "low";
        title: string;
        description: string;
        potentialSavings?: number;
        implementationEffort: "low" | "medium" | "high";
    }>;
}
export declare class DeepAnalyzer {
    generateDataQualityReport(entries: UsageEntry[]): DataQualityReport;
    generateUsageHeatmap(entries: UsageEntry[]): UsageHeatmap;
    analyzeConversationFlow(entries: UsageEntry[]): ConversationFlowAnalysis;
    analyzeCostDrivers(entries: UsageEntry[]): CostDriverAnalysis;
    generateDeepInsights(entries: UsageEntry[]): DeepInsights;
    private detectDataAnomalies;
    private countDuplicates;
    private generateRecommendations;
}
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