Summarize local AI model cost usage from CodexBar CLI logs.
npx skills add https://github.com/linuxhsj/openclaw-zero-token --skill model-usage-linuxhsj
Please help me install this Agent Skill. Skill: model-usage Source: https://github.com/linuxhsj/openclaw-zero-token/tree/main/skills/model-usage Command: npx skills add https://github.com/linuxhsj/openclaw-zero-token --skill model-usage-linuxhsj
This Skill helps users understand and manage their AI model costs by providing detailed, per-model usage summaries directly from local logs.
Run the model_usage script to get a summary of the current most expensive model for Codex.
High-intent search queries and answers about installing and using this skill.
To track AI model costs locally, you can use this Skill to summarize per-model usage data parsed directly from your local CodexBar CLI logs. It provides a detailed expense breakdown for Codex and Claude providers.
Yes, you need the CodexBar CLI installed and configured for local cost logging to analyze per-model usage data. This Skill parses the local logs generated by the CLI to calculate expense breakdowns.
The best way to get a cost breakdown for specific AI models like Claude is to run the model usage script, which summarizes local cost logging data to show spending details per provider.
Yes, you can compare expenses by generating a summary of the most recently used model or requesting a comprehensive breakdown of all models to evaluate your spending distribution.
The model usage script applies cost analysis specifically to Codex and Claude providers because it parses local cost logs structured by the CodexBar CLI for these specific AI models.
Local AI cost tracking is the process of summarizing expense data from local logs to manage your budget. You need it when you want to understand how much you are spending per AI model without using external cloud billing dashboards.
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