ryoppippi/ccusage

Features

• Agent Usage Aggregators - Consolidate local log files from multiple coding assistants into a unified report to track token consumption and estimated costs across different tools.
• AI Coding Assistants - Provides analytics and cost tracking for AI coding assistants by parsing local session logs.
• AI Cost Monitoring - Calculates financial expenditure based on token usage and cached pricing data for major AI model providers.
• Token Cost Calculators - Monitors and aggregates token usage data from coding assistants to provide detailed financial and activity reports.
• Data Privacy Tools - Performs all analysis locally on the user machine without transmitting usage data to external servers.
• Local-First Architectures - Processes raw session files directly on the user machine to ensure data privacy and offline availability.
• Token Usage Analytics - Parses local logs to calculate token consumption and estimate costs across various AI models.
• LLM Cost Management - Calculates financial expenditure by mapping token counts to pricing models for recorded activity.
• Local Usage Aggregators - Reads session logs from local databases to track model interactions and token consumption.
• Usage Reporting - Produces structured summaries of activity grouped by day, month, or session with support for compact terminal views.
• Local Data Processing Tools - Ensures data privacy by processing sensitive session logs and usage telemetry entirely on the local machine.
• Pricing Engines - Calculates financial expenditure by applying model-specific cost multipliers to token counts independently of data ingestion.
• Log Aggregation - Consolidates token usage and activity data from local session and message files.
• Conversation Cost Aggregators - Parses local session files from coding assistants to calculate total token consumption and estimate costs.
• Usage Monitoring - Computes financial expenditure using offline pricing caches and per-model breakdown modes.
• Usage Analytics - Organizes consumption data by individual interaction sessions to provide granular insight.
• Model Pricing Managers - Updates and maintains a database of current model costs to ensure accurate financial analysis.
• Model Pricing Overrides - Supplies custom token costs for specific models to ensure accurate financial tracking.
• Schema-Agnostic Aggregators - Normalizes disparate log formats from multiple coding assistants into a unified internal representation for consistent analysis.
• Log Aggregators - Parses structured local log files to extract token counts and session metadata for unified analysis.
• Local - Processes local session files and logs to generate usage metrics without transmitting data to external servers.
• Project Usage Categorizers - Groups consumption metrics by project instance with support for custom naming aliases.
• Offline Analysis Engines - Uses locally cached pricing information to perform cost calculations and usage analysis when offline.
• Conversational Session Management - Breaks down aggregated data into specific conversation logs to review performance and cost.
• Usage Grouping - Organizes flat log entries into nested structures by session, project, or timeframe to enable granular reporting.
• API Usage Analytics - Groups AI coding assistant activity by session and project to identify usage patterns and trends.
• Reporting Default Configurations - Defines shared settings for consumption reports, including options to hide cost data or apply consistent formatting.
• Embedded Cost Extractors - Reads pre-calculated cost values directly from session logs to provide accurate financial reporting.
• Session Activity Monitors - Displays hierarchical session activity to track complex multi-agent interactions.
• Trend Analysis - Visualizes changes in token consumption and model adoption over time to monitor shifts in activity.
• Session - Groups token consumption data by individual interaction sessions to identify high-cost workflows.
• Service Tier Selectors - Applies pricing models based on service tiers and model-specific multipliers to estimate expenses.
• Usage-Based Billing - Calculates usage patterns within specific time-based billing blocks to help monitor and optimize service costs.
• Weekly Usage Aggregators - Summarizes token consumption and costs on a weekly basis for project activity tracking.
• Gemini Usage Aggregators - Parse local log files from specific directories to extract token consumption and session data for unified analysis.
• Kimi Usage Aggregators - Parse local wire logs from specific command line tools to extract token consumption and cost data for unified analysis.
• Data Path Configurations - Provides settings to define custom file paths and directories for log ingestion.
• Usage Report Renderers - Displays consumption data in tables or structured formats with customizable cost metric inclusion.
• Source Filters - Isolates usage data for a specific assistant to generate detailed performance and cost metrics.
• Command Line Configuration - Customizes reporting through local configuration files, environment variables, or command-line arguments.
• Developer Productivity - Analyzes coding workflow patterns and session activity to provide insights into development productivity.
• Path Mapping Configurations - Provides configurable mapping of log file paths and pricing overrides for accurate usage analysis.
• Reporting Timezone Configurations - Adjusts temporal references for date-based calculations to ensure logs align with local time zones.
• Agent Log Path Overrides - Allows users to specify custom directories where coding assistant logs are stored for parsing.
• Metrics Visualizers - Displays token consumption and spending data through graphical dashboards and terminal interfaces.
• Real-Time Monitoring - Renders a compact summary of current token consumption directly within the command line interface for immediate feedback.
• Usage Period Analyzers - Groups consumption data into daily, weekly, or monthly intervals to identify trends and patterns in development activity.

Star history