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model-usage

Summarize per-model AI cost usage from CodexBar logs.

375|38|Updated Dec 2, 2025
Search Tags:#ai#llm#billing#cost#model usage#codexbar
One-click install
npx skills add https://github.com/CraftOS-dev/CraftBot --skill model-usage-craftos-dev
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: model-usage
Source: https://github.com/CraftOS-dev/CraftBot/tree/main/skills/model-usage
Command: npx skills add https://github.com/CraftOS-dev/CraftBot --skill model-usage-craftos-dev

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 local costs associated with using different AI models (Codex, Claude) by summarizing their usage from CodexBar's logs.

Core Features & Use Cases

  • Per-Model Cost Summary: View the total cost incurred by each AI model.
  • Current Model Identification: Identify the most recently used model and its associated costs.
  • Data Export: Output summaries in human-readable text or structured JSON format.
  • Use Case: If you're running multiple AI tasks and want to know which model is consuming the most budget locally, this skill provides that insight.

Quick Start

Run the model_usage script to see the current model's cost summary for Codex.

Frequently Asked Questions about model-usage

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

FAQPage Schema
How do I track local AI model usage costs from CodexBar logs?▼

You can track local AI model costs by summarizing usage data from CodexBar logs, which provides a per-model cost breakdown for Codex and Claude. This allows you to see exactly how much budget each model is consuming locally.

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

Getting a per-model cost breakdown involves parsing local AI model usage logs to aggregate total costs by model. It summarizes expenses specifically for Codex and Claude, helping you identify which model incurs the most budget.

Do I need CodexBar installed to monitor AI model spending?▼

Yes, you need the CodexBar CLI installed and properly configured for local cost tracking. The tool functions by reading usage logs directly generated by the CodexBar environment to calculate model costs.

Can I export AI billing summaries to JSON?▼

Yes, you can export AI billing summaries in structured JSON format or human-readable text. This allows you to output the total cost aggregation and recent model usage data for integration into other analytics pipelines.

How do I identify the most recently used AI model and its associated cost?▼

Identifying the most recently used model involves analyzing local AI usage logs to find the latest entry and calculating its associated cost. This helps you track current model consumption and recent budget impact.

What are the limitations of summarizing local AI costs with this approach?▼

This approach is limited to summarizing local costs for Codex and Claude models and requires the CodexBar CLI. It focuses strictly on local usage logs and does not inherently track cloud-based API billing or models outside this scope.

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