Summarize per-model costs from CodexBar JSON logs.
npx skills add https://github.com/Clawdi-AI/openclaw --skill model-usage-clawdi-ai
Please help me install this Agent Skill. Skill: model-usage Source: https://github.com/Clawdi-AI/openclaw/tree/main/skills/model-usage Command: npx skills add https://github.com/Clawdi-AI/openclaw --skill model-usage-clawdi-ai
This Skill helps you understand and manage the costs associated with using different AI models by summarizing usage data from CodexBar.
Run the model-usage skill to see the current model's cost breakdown for Codex.
High-intent search queries and answers about installing and using this skill.
To track AI model costs, this Skill parses CodexBar cost JSON output to summarize local usage expenses for Codex and Claude models. It provides a detailed breakdown to help you analyze spending and optimize your budget.
Yes, you can get a per-model cost breakdown for Claude and Codex. The Skill summarizes local usage data to show expenses for individual models, helping you compare costs across different AI services.
The best way to analyze historical AI expenses is by viewing total costs across all models over time. The Skill processes CodexBar JSON logs to deliver a comprehensive historical analysis of your spending.
To identify the most expensive AI model for the current period, run the Skill to focus on current model costs. It evaluates CodexBar logs to highlight your highest-spending models during the active cycle.
No specific dependencies are required to track costs. The Skill operates independently using scripts and references to parse existing CodexBar JSON output for your AI budget analysis.
You need to parse CodexBar JSON output to extract accurate cost metrics for budget optimization. This process transforms raw local usage logs into structured per-model summaries, enabling precise expense tracking.
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