askill
model-usage

model-usageSafety 90Repository

Use CodexBar CLI local cost usage to summarize per-model usage for Codex or Claude, including the current (most recent) model or a full model breakdown. Trigger when asked for model-level usage/cost data from codexbar, or when you need a scriptable per-model summary from codexbar cost JSON.

1 stars
1.2k downloads
Updated 2/21/2026

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SKILL.md

Model usage

Overview

Get per-model usage cost from CodexBar's local cost logs. Supports "current model" (most recent daily entry) or "all models" summaries for Codex or Claude.

TODO: add Linux CLI support guidance once CodexBar CLI install path is documented for Linux.

Quick start

  1. Fetch cost JSON via CodexBar CLI or pass a JSON file.
  2. Use the bundled script to summarize by model.
python {baseDir}/scripts/model_usage.py --provider codex --mode current
python {baseDir}/scripts/model_usage.py --provider codex --mode all
python {baseDir}/scripts/model_usage.py --provider claude --mode all --format json --pretty

Current model logic

  • Uses the most recent daily row with modelBreakdowns.
  • Picks the model with the highest cost in that row.
  • Falls back to the last entry in modelsUsed when breakdowns are missing.
  • Override with --model <name> when you need a specific model.

Inputs

  • Default: runs codexbar cost --format json --provider <codex|claude>.
  • File or stdin:
codexbar cost --provider codex --format json > /tmp/cost.json
python {baseDir}/scripts/model_usage.py --input /tmp/cost.json --mode all
cat /tmp/cost.json | python {baseDir}/scripts/model_usage.py --input - --mode current

Output

  • Text (default) or JSON (--format json --pretty).
  • Values are cost-only per model; tokens are not split by model in CodexBar output.

References

  • Read references/codexbar-cli.md for CLI flags and cost JSON fields.

Install

Download ZIP
Requires askill CLI v1.0+

AI Quality Score

72/100Analyzed 2/25/2026

A reasonably complete skill for summarizing per-model LLM usage costs using CodexBar CLI. Provides clear trigger conditions, structured commands, and good technical depth. Main weaknesses are the Darwin-only support and {baseDir} placeholder which reduces portability. Has proper skill folder structure and actionable CLI examples.

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Metadata

Licenseunknown
Version-
Updated2/21/2026
Publisher7SoKKoS7

Tags

llm