model-usage

Summarize local cost usage per AI model from CodexBar logs.

1|Updated Feb 21, 2026
One-click install
npx skills add https://github.com/Justicegaines03/OpenClaw_NIST-AI-RMF_Compliance --skill model-usage-justicegaines03
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: model-usage
Source: https://github.com/Justicegaines03/OpenClaw_NIST-AI-RMF_Compliance/tree/main/skills/model-usage
Command: npx skills add https://github.com/Justicegaines03/OpenClaw_NIST-AI-RMF_Compliance --skill model-usage-justicegaines03

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill helps you understand and manage the costs associated with using different AI models by providing a summary of per-model usage from local logs.

Core Features & Use Cases

  • Per-Model Cost Summaries: Get detailed cost breakdowns for individual AI models (Codex, Claude).
  • Current Model Focus: Easily identify the cost of the most recently used model.
  • Full Model Breakdown: View a comprehensive summary of all models used and their associated costs.
  • Use Case: A developer wants to optimize their AI spending. They use this Skill to see which models are consuming the most budget and identify areas for potential cost savings.

Quick Start

Run the model usage script to get a summary of all Codex model costs.

Frequently Asked Questions about model-usage

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

FAQPage Schema
How do I track AI model costs locally from my terminal?

You can track AI model costs locally by running scripts that summarize per-model usage from CodexBar logs. This provides a detailed breakdown of spending for models like Codex and Claude.

Do I need CodexBar installed to get a cost breakdown for Claude and Codex models?

Yes, you need the codexbar CLI installed and configured locally. The Skill retrieves cost data directly from these local logs to analyze usage.

What is the best way to analyze per-model AI spending for optimization?

The best way to analyze AI spending is to review a comprehensive per-model cost summary from local logs. This helps identify which models consume the most budget for potential savings.

Can I view the cost of just the current AI model instead of all models?

Yes, you can view the cost of the current AI model. The Skill analyzes local usage logs to provide a focused cost breakdown for the most recently used model.

Why does my local model usage summary fail to retrieve AI costs?

Local model usage summaries fail when the codexbar CLI is not properly installed or configured. Correct setup is required to retrieve local cost data for per-model tracking.