Summarize local AI model costs from CodexBar CLI JSON output.
npx skills add https://github.com/syxscott/PaleoClaw --skill model-usage-syxscott
Please help me install this Agent Skill. Skill: model-usage Source: https://github.com/syxscott/PaleoClaw/tree/main/skills/model-usage Command: npx skills add https://github.com/syxscott/PaleoClaw --skill model-usage-syxscott
This Skill helps users understand and manage their AI model expenses by providing detailed breakdowns of usage and cost from local logs.
Run the model_usage.py script to get a summary of current Codex model costs.
High-intent search queries and answers about installing and using this skill.
You can track AI model costs locally by running a script that summarizes usage expenses from CodexBar CLI JSON output. This provides a detailed breakdown of costs per model, enabling budget management and optimization.
Local AI cost tracking summarizes your model usage expenses from local JSON logs. It parses the data to provide a clear view of how much each AI model is costing you, without sending your usage data to external servers.
Yes, you need the CodexBar CLI installed and configured for local cost logging. The tool relies on the JSON output generated by CodexBar to summarize your expenses for various AI models.
To get a per-model cost summary, run the model usage script on your local logs. You can choose to view costs for the most recently used model or a comprehensive summary of all models tracked.
Yes, you can identify your highest budget-consuming AI model by reviewing the per-model cost summary. This breakdown helps you adjust your usage or explore more cost-effective alternatives for your workflows.
Clawdi-AISummarize per-model costs from CodexBar JSON logs.
latestaiagentsTrack token usage, enforce budget limits, and generate cost reports for AI agents.
aresbitAnalyze CodexBar cost logs to report per-model usage and costs.
WellFitCommunityMonitor AI spending and usage across MCP and automation skills.
