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model-usage

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

1|Updated Apr 28, 2026
Search Tags:#python#cli#json#cost#model usage#codexbar#local logs
One-click install
npx skills add https://github.com/seasonmac/Full-Scene-Agents --skill model-usage-seasonmac
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: model-usage
Source: https://github.com/seasonmac/Full-Scene-Agents/tree/main/openclaw/skills/model-usage
Command: npx skills add https://github.com/seasonmac/Full-Scene-Agents --skill model-usage-seasonmac

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill helps teams quickly summarize per-model usage costs from CodexBar’s local cost logs, surfacing the current top model or a complete model breakdown to inform budgeting and model selection.

Core Features & Use Cases

  • Per-model cost summaries from CodexBar: current model or all models, with optional day range filtering.
  • Output formats: human-readable text or JSON for programmatic consumption.
  • Use Case: quickly identify which model is driving the most cost in a given period and export the numbers to a dashboard.

Quick Start

Run the model-usage script with your CodexBar cost JSON to produce a per-model usage summary.

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?▼

You can summarize per-model usage costs by running a script that parses CodexBar local JSON cost logs to aggregate spending for Codex and Claude models. The summary identifies the current top model or provides a full breakdown.

Can I filter model usage costs by a specific date range?▼

Yes, you can filter model usage costs by a specific date range. The script supports optional day range filtering to restrict the cost aggregation to the period you specify.

Does the model-usage script support JSON output for programmatic consumption?▼

Yes, the script supports JSON output for programmatic consumption. It can return either human-readable text or structured JSON data suitable for exporting to dashboards and downstream systems.

Do I need CodexBar installed to extract local cost logs?▼

Yes, you need CodexBar installed and accessible on your system PATH to extract local cost logs. The script works directly with local JSON cost data or the CodexBar CLI output.

What is the best way to identify which model is driving the most cost?▼

The best way to identify the costliest model is to aggregate local JSON cost logs to highlight the current top model. This surfaces the specific model driving the most spending for budgeting and model selection.

Can I use Python to parse CodexBar CLI output for cost tracking?▼

Yes, you can use Python to parse CodexBar CLI output for cost tracking. The script processes the CLI output directly to produce per-model usage summaries for your cost tracking needs.

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