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model-usage

Summarize per-model usage costs from CodexBar local JSON logs.

Updated Feb 3, 2026
Search Tags:#budgeting#codexbar#model-costs#local-logs#python-script#cost-analytics
One-click install
npx skills add https://github.com/Dolonia333/dolo.ai --skill model-usage-dolonia333
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: model-usage
Source: https://github.com/Dolonia333/dolo.ai/tree/main/skills/model-usage
Command: npx skills add https://github.com/Dolonia333/dolo.ai --skill model-usage-dolonia333

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

CodexBar local logs hold detailed per-model usage costs. This Skill consolidates that data to deliver quick, actionable cost visibility at the model level.

Core Features & Use Cases

  • Current-model cost summary: identify the most expensive model in use today.
  • All-model breakdown: compute total costs per model across a date range or entire dataset.
  • Flexible outputs: text or JSON for integration with dashboards or scripts.

Quick Start

Run the script to generate per-model cost summaries from CodexBar local logs.

Frequently Asked Questions about model-usage

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I summarize per-model usage costs from CodexBar local logs?▼

To summarize per-model usage costs from CodexBar local logs, you can run a Python script that reads JSON log files directly from the local CodexBar data directory and calculates total costs per model for budgeting and auditing.

Can I get a cost breakdown for both Codex and Claude models from local logs?▼

Yes, you can get a cost breakdown for both Codex and Claude models. The script processes local JSON logs to provide either a current-model summary or a full all-model breakdown across a specified date range or the entire dataset.

What is the best way to identify the most expensive AI model in use today?▼

The best way to identify the most expensive AI model in use today is to generate a current-model cost summary from your local CodexBar logs, which isolates and calculates today's per-model spending.

Do I need the CodexBar CLI installed to analyze local model costs?▼

Yes, you need the CodexBar CLI installed. The script depends on the CLI environment to correctly locate and read the JSON usage logs from the local CodexBar data directory for cost analysis.

Can I export per-model cost summaries as JSON for dashboard integration?▼

Yes, you can export per-model cost summaries as JSON. The script supports flexible output formats, allowing you to output text or JSON for seamless integration with dashboards or other scripts.

How do I calculate total API costs per model across a specific date range?▼

You calculate total API costs per model across a specific date range by running the all-model breakdown function, which aggregates the JSON data from your local CodexBar logs over your selected timeframe.

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