Claude Analyst is a macOS menu bar app that monitors Claude Code usage in real-time. It tracks token consumption, costs, and usage patterns, helping users optimize their AI interactions without leaving their workflow.
git clone https://github.com/onmyway133/claude-analyst.gitClaude Analyst is a macOS menu bar app that monitors Claude Code usage in real-time. It tracks token consumption, costs, and usage patterns, helping users optimize their AI interactions without leaving their workflow.
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/onmyway133/claude-analystCopy 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 Claude Code usage data from [DATE RANGE] and identify patterns in my interactions. Provide insights on how I can optimize my workflow to reduce costs while maintaining productivity. Focus on [SPECIFIC GOALS] like reducing unnecessary prompts or improving response efficiency.
# Claude Code Usage Analysis ## Usage Summary - **Total Tokens Used**: 12,450 - **Cost**: $18.68 - **Average Tokens per Interaction**: 156 - **Peak Usage Time**: 2:00 PM - 4:00 PM ## Key Insights - **High Token Consumption**: Your interactions related to [COMPANY] data analysis in the [INDUSTRY] sector are consuming significantly more tokens than other topics. - **Inefficient Prompts**: Several prompts could be optimized for brevity without losing context. For example, your prompt on [DATE] used 240 tokens but could be reduced to 120 tokens with minimal impact on the response quality. - **Cost-Saving Opportunity**: By refining your prompts and reducing unnecessary interactions, you could save up to 20% on your monthly Claude Code costs. ## Recommendations 1. **Refine Prompts**: Focus on making your prompts more concise and specific to reduce token usage. 2. **Schedule Interactions**: Consider scheduling high-token interactions during off-peak hours to take advantage of lower usage rates. 3. **Review Usage Patterns**: Regularly review your usage patterns to identify and address any inefficiencies.
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