Summarize per-model AI costs from CodexBar CLI output.
npx skills add https://github.com/loveoplay2023-hue/OpenMehdi --skill model-usage-loveoplay2023-hue
Please help me install this Agent Skill. Skill: model-usage Source: https://github.com/loveoplay2023-hue/OpenMehdi/tree/main/skills/model-usage Command: npx skills add https://github.com/loveoplay2023-hue/OpenMehdi --skill model-usage-loveoplay2023-hue
This Skill helps you understand and manage the local costs associated with using different AI models, providing a clear breakdown of expenses.
Run the model usage script to get a summary of all model costs for the codex provider.
High-intent search queries and answers about installing and using this skill.
To track local AI model costs, you can use this Skill to summarize per-model expenses from CodexBar CLI output. It automatically identifies the most recently used model and provides a clear breakdown of costs for Codex and Claude.
Getting a per-model cost breakdown involves running the model usage script to analyze CLI output data. This provides a summary of all expenses incurred by each specific AI model, such as comparing 'gpt-4o' versus 'claude-3-opus' spending.
Yes, analyzing AI cost usage requires the CodexBar CLI tool to be installed and accessible in your system's PATH. The Skill processes the output generated by this CLI to summarize and identify your model expenses.
Yes, you can check your spending on the most recently used AI model by running the analysis script. It automatically identifies the current model and extracts its associated costs from the local usage data.
Historical usage analysis tracks AI spending trends by analyzing usage data over time from the CLI output. This allows developers to monitor their local costs and understand spending patterns across different models.
The main limitation for tracking AI model usage locally is the strict dependency on the CodexBar CLI tool. If the CLI is not installed or accessible in the system PATH, the Skill cannot summarize or analyze the cost data.
me2DocParse CodexBar JSON logs to summarize local AI model costs.
THUYRanAggregate hours, expenses, and forecasted costs to plan and track litigation budgets.
ReefBytes-OwnerAggregate agent efficiency metrics from local logs into markdown summaries.
EwallywRoute queries to Claude, Codex, or Gemini and capture results as artifacts.
