Track OpenClaw AI token usage and cost per model on Linux by parsing session JSONL files. Use when asked about: token usage, API cost, how much has been spent, which model was used most, usage summary, billing, cost breakdown. Linux replacement for the macOS-only model-usage/CodexBar skill.
Scanned 9/5/2026
Install to Claude Code
Skills Directorynpx -y skills add aAAaqwq/AGI-Super-Skills --skill model-usage-linux --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: model-usage-linux
description: "Track OpenClaw AI token usage and cost per model on Linux by parsing session JSONL files. Use when asked about: token usage, API cost, how much has been spent, which model was used most, usage summary, billing, cost breakdown. Linux replacement for the macOS-only model-usage/CodexBar skill."
---
# Model Usage (Linux)
Parse OpenClaw session files to summarize token usage and cost per model.
## Quick start
```bash
python3 {baseDir}/scripts/usage.py
```
## Options
```bash
# JSON output
python3 {baseDir}/scripts/usage.py --format json
# Custom sessions dir
python3 {baseDir}/scripts/usage.py --sessions-dir ~/.openclaw/agents/main/sessions
```
## Output
Shows per-model breakdown:
- Turns (assistant replies)
- Input / output tokens
- Cache read / write tokens
- Cost in USD
Sessions live at: `~/.openclaw/agents/main/sessions/*.jsonl`
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Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.
