model-usage

Calculate per-model usage costs from CodexBar local logs.

1|Updated Feb 26, 2026
One-click install
npx skills add https://github.com/zhanbei1/OpenOcta --skill model-usage-zhanbei1
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: model-usage
Source: https://github.com/zhanbei1/OpenOcta/tree/main/src/skills/model-usage
Command: npx skills add https://github.com/zhanbei1/OpenOcta --skill model-usage-zhanbei1

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Organizations need clear, model-level cost visibility from CodexBar's local logs to track spending and optimize prompts.

Core Features & Use Cases

  • Current model cost: identify the most expensive active model from recent logs.
  • All-model breakdown: compute total costs per model across daily entries.
  • Flexible inputs: read from CodexBar JSON or local files; output can feed dashboards or reports.

Quick Start

Run the model_usage.py script with a provider (codex or claude) and an input source to generate a per-model cost summary.

Frequently Asked Questions about model-usage

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

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

You can calculate per-model usage costs from CodexBar local logs by running the model_usage.py script with a provider and input source. It analyzes daily modelBreakdowns to output a per-model cost summary.

What is the best way to get a full per-model cost breakdown for Codex and Claude providers?▼

Getting a full per-model cost breakdown for Codex and Claude providers involves running the model_usage.py script with the --mode parameter. This analyzes daily modelBreakdowns to output total costs per model.

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

Yes, you need the CodexBar CLI installed and access to local cost logs to analyze model usage costs. The script processes these local JSON logs to compute per-model spending.

Can I read CodexBar cost logs from a local file instead of the CLI output?▼

Yes, you can read CodexBar cost logs from a local file by passing the --input parameter to the model_usage.py script. This allows flexible data sourcing for your cost reporting.

How do I identify the most expensive active model from recent usage logs?▼

You identify the most expensive active model from recent logs by executing the model_usage.py script with the appropriate provider. It exposes the current model cost directly from recent local entries.