Summarize per-model usage and cost data from CodexBar cost logs.
npx skills add https://github.com/deepgram/dglabs-deepclaw --skill model-usage-deepgram
Please help me install this Agent Skill. Skill: model-usage Source: https://github.com/deepgram/dglabs-deepclaw/tree/main/skills/model-usage Command: npx skills add https://github.com/deepgram/dglabs-deepclaw --skill model-usage-deepgram
This Skill provides a summary of per-model usage and cost data for Codex or Claude, helping users understand their model-level consumption and costs.
Run the script with the desired provider and mode:
python {baseDir}/scripts/model_usage.py --provider codex --mode current
High-intent search queries and answers about installing and using this skill.
To analyze per-model usage and cost data from CodexBar logs, run the provided Python script to parse local cost JSON files and summarize consumption metrics for Codex or Claude models. The script extracts usage metrics directly from the logs.
Current model usage shows cost data for the active model, while full model breakdowns provide a comprehensive summary across all models. The script supports both modes to help you understand total model-level consumption.
Yes, you need Python installed to execute the analysis scripts, and the CodexBar CLI is required for data retrieval. These dependencies are necessary to access and parse the local cost logs for summary generation.
Yes, the script provides a scriptable per-model summary extracted from CodexBar cost JSON. You can customize the execution through command-line arguments to specify the provider and mode for tailored cost analysis.
The best way to track Codex and Claude model consumption costs is by summarizing CodexBar's local cost logs. This approach provides per-model usage data directly from your existing cost tracking infrastructure.
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