> ## Documentation Index > Fetch the complete documentation index at: https://docs.heygarth.ai/llms.txt > Use this file to discover all available pages before exploring further. # Claude metrics ## Overview The Claude Code Metrics Dashboard provides visibility into Claude-powered development activity, token consumption, cost efficiency, developer adoption, and AI-assisted coding productivity across engineering teams. It enables organizations to monitor how effectively Claude is being used, optimize AI spending, and measure the impact of AI-assisted software development. The dashboard is designed for engineering leaders, platform administrators, and development teams who need to monitor AI coding adoption, usage efficiency, and return on investment. ## Executive Overview ### What is it? A high-level summary section displaying key performance indicators and overall health metrics for Claude Code usage across the organization. ### Why is it important? Provides an immediate understanding of Claude adoption, usage costs, productivity levels, and operational efficiency without requiring detailed analysis. ### Where does it exist? Top section of the Claude Code Metrics Dashboard. ### Metrics Included **Total Tokens** Displays the total number of tokens consumed through Claude interactions during the selected reporting period. **Total Cost** Displays the total spend associated with Claude usage. **Sessions** Displays the total number of Claude coding sessions initiated by users. **Tool Acceptance** Displays the percentage of Claude-generated suggestions that were accepted by developers. **Active Developers** Displays the number of developers actively using Claude. **Cost per User** Displays the average Claude-related cost per active developer. **Completions per Dollar** Displays the average number of AI completions generated for every dollar spent. ### Use Cases * Monitor Claude adoption across teams * Track AI spending and usage trends * Measure AI coding effectiveness * Evaluate return on investment * Identify opportunities for optimization ## Daily Cost vs Completions per Session ### What is it? A comparative trend chart showing daily Claude spending alongside completions generated per session. ### Why is it important? Helps organizations understand the relationship between AI investment and developer productivity. ### Where does it exist? Lower-left section of the Executive Overview page. ### Metrics Included **Daily Cost (\$)** Tracks the amount spent on Claude usage each day. **Completions per Session** Tracks the average number of completions generated during each Claude session. ### Use Cases * Monitor spending efficiency * Measure productivity output * Identify high-cost periods * Evaluate AI value generation ## Cost Efficiency Trend ### What is it? A trend chart displaying cost efficiency metrics over time. ### Why is it important? Provides visibility into how effectively Claude resources are being utilized and whether costs are scaling appropriately with usage. ### Where does it exist? Lower-right section of the Executive Overview page. ### Metrics Included **Cost per User (\$)** Displays the average cost incurred by each active user. **Cost per Session (\$)** Displays the average cost associated with each Claude session. ### Use Cases * Monitor operational efficiency * Track cost optimization initiatives * Identify spending anomalies * Evaluate usage patterns ## Navigation Sections ### What is it? A collection of analytical views that provide deeper insights into Claude usage, productivity, efficiency, and adoption. ### Why is it important? Allows users to drill into specific aspects of Claude performance and usage across the organization. ### Where does it exist? Directly below the dashboard header. ### Available Sections **Executive Overview** Provides a high-level summary of Claude usage, spending, and productivity metrics. **Token Consumption** Analyzes token usage trends and consumption patterns. **Cost Optimization** Identifies opportunities to improve spending efficiency and reduce unnecessary AI costs. **Tool Efficiency** Measures how effectively Claude-generated outputs are utilized by developers. **Adoption & Usage** Tracks user adoption, engagement, and platform utilization metrics. **Productivity** Measures productivity improvements generated through Claude-assisted development. **Model Utilization** Analyzes usage distribution across Claude models and capabilities. **Top Performers** Highlights developers and teams achieving the highest productivity and adoption levels. **Low Performers** Identifies users or teams with low engagement or utilization. **Waste Detection** Identifies inefficient usage patterns, unused generations, and cost leakage opportunities. **Efficient Developers** Highlights users achieving strong productivity outcomes with efficient AI utilization. **Operational Efficiency** Measures overall efficiency of Claude adoption relative to organizational objectives. **Inactive Developers** Identifies licensed or enabled users who are not actively utilizing Claude. ### Use Cases * Analyze AI adoption patterns * Monitor developer engagement * Identify optimization opportunities * Improve cost efficiency * Measure productivity impact ## Controls and Filters ### What is it? Interactive controls used to customize dashboard data and reporting views. ### Why is it important? Allows users to analyze Claude metrics across different time periods and reporting scopes. ### Where does it exist? Top-right section of the dashboard. ### Features **Time Range Filters** Provides predefined reporting windows such as: * 7 Days * 15 Days * 90 Days ### Use Cases * Compare short-term and long-term trends * Analyze recent adoption changes * Monitor spending over time * Evaluate productivity improvements ## Key Use Cases ### AI Adoption Monitoring Track how widely Claude is being used across engineering teams. ### Cost Management Monitor spending, cost per user, and cost efficiency trends. ### Productivity Measurement Measure engineering output and AI-assisted development effectiveness. ### Usage Optimization Identify inefficient usage patterns and optimization opportunities. ### Executive Reporting Provide leadership with visibility into AI adoption, spending, and business impact.