Track AI coding time and productivity metrics with WakaTime plugin for Claude Code. Developers and operations teams gain insights into AI usage, lines of code generated, and time spent prompting AI. Integrates with WakaTime for metrics and insights.
git clone https://github.com/wakatime/claude-code-wakatime.gitThe claude-code-wakatime skill is designed to help developers and AI practitioners track the time they spend coding with Claude Code. By integrating with your coding environment, this automation skill provides insights into your productivity, allowing you to analyze how effectively you are utilizing your time while developing AI solutions. The skill operates by logging your coding sessions and presenting detailed reports on your usage patterns, enabling you to make informed decisions about your workflow and productivity enhancements. One of the key benefits of using the claude-code-wakatime skill is the ability to gain visibility into your coding habits. While the exact time savings are currently unknown, users can expect to optimize their workflow by identifying time-consuming tasks and areas for improvement. This skill is particularly useful for developers, product managers, and AI practitioners who are looking to refine their coding efficiency and enhance their project management capabilities. By understanding how much time is spent on various tasks, users can streamline their processes and allocate resources more effectively. The skill is suitable for anyone involved in software development, particularly those who work with AI automation and workflow automation. Whether you are a solo developer or part of a larger team, the insights provided by claude-code-wakatime can help you refine your approach to coding. Practical use cases include tracking the time spent on specific features or projects, allowing teams to assess the feasibility of deadlines and improve project planning. For instance, a developer can analyze their time spent on debugging versus feature development, leading to better time management and prioritization. Implementing the claude-code-wakatime skill is straightforward, with a moderate difficulty level that typically requires around 30 minutes to set up. Users will need to ensure they have the necessary permissions and access to their coding environment for seamless integration. This skill fits perfectly into AI-first workflows, as it allows teams to leverage data-driven insights to enhance their development processes. By incorporating this skill into your routine, you can foster a culture of continuous improvement and efficiency within your coding practices.
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/wakatime/claude-code-wakatimeCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
I'm using the WakaTime plugin for Claude Code. Please track my coding time and productivity metrics for [PROJECT_NAME] in [PROGRAMMING_LANGUAGE]. I want to monitor my AI usage, lines of code generated, and time spent prompting AI. Ensure the data is synced with my WakaTime account.
# AI Coding Productivity Report ## Project Overview - **Project Name**: Quantum Leap - **Language**: Python - **Total Time**: 2 hours 30 minutes - **Total Lines Generated**: 450 ## AI Usage Metrics - **Prompt Sessions**: 12 - **Average Session Duration**: 10 minutes 15 seconds - **Code Generation Rate**: 37.5 lines per hour ## Key Insights - Peak productivity between 2:00 PM and 4:00 PM - Most frequent prompts related to data processing and API integrations - Suggested improvement: Reduce prompt frequency for repetitive tasks by using code snippets
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