Analyzes ActivityWatch data to calculate focus scores, detect repetitive app switching, and generate actionable insights. Benefits operations teams by identifying productivity patterns and areas for improvement. Integrates with ActivityWatch and Claude Code.
git clone https://github.com/BayramAnnakov/activitywatch-analysis-skill.gitAnalyzes ActivityWatch data to calculate focus scores, detect repetitive app switching, and generate actionable insights. Benefits operations teams by identifying productivity patterns and areas for improvement. Integrates with ActivityWatch and Claude Code.
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/BayramAnnakov/activitywatch-analysis-skillCopy 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.
Analyze my ActivityWatch data from [DATE RANGE] and provide a detailed report. Calculate my focus score, identify any repetitive app switching patterns, and suggest actionable improvements. My primary work involves [TASK TYPES] in the [INDUSTRY] sector.
# ActivityWatch Analysis Report ## Focus Score - **Overall Focus Score:** 78/100 - **Peak Focus Period:** 10:00 AM - 12:00 PM (Focus Score: 92) - **Lowest Focus Period:** 2:00 PM - 4:00 PM (Focus Score: 65) ## Repetitive App Switching Patterns - **Most Frequent App Switch:** Slack to Email (18 times) - **Potential Death Loop:** Browser to Notepad (12 times) - **Suggested Improvement:** Use browser bookmarks or a task manager to reduce switching. ## Actionable Insights - **Schedule Deep Work Blocks:** Based on peak focus periods. - **Minimize Distractions:** Consider using focus apps during low focus periods. - **Batch Similar Tasks:** Group email and Slack tasks to reduce switching.
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