Model usage linux

Skill aAAaqwq/AGI-Super-Team/skills/model-usage-linux

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.From its SKILL.md

Install

npx -y skills add aAAaqwq/AGI-Super-Team --skill model-usage-linux

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

SKILL.md

0.9 KB, 147 tokens by cl100k_base, as published. Nobody here has run it

Model Usage (Linux)

Parse OpenClaw session files to summarize token usage and cost per model.

Quick start

python3 {baseDir}/scripts/usage.py

Options

# 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

What ships with it: 3 files

4.4 KB alongside SKILL.md, 1 of them executable

.clawhub/

origin.json149 B

scripts/

usage.pyruns4.1 KB

_meta.json136 B

Gives 0 of the 12 instructions most token cost skills give in 147 tokens

Counted across 84 of the 95 authors here whose files we hold, read 2026-09-06

Set explicit budget limits before processing batchesin 14 of 84, across 9 files
Define model names as constants or configin 14 of 84, across 9 files
Route simple tasks to cheaper modelsin 14 of 84, across 9 files
Log model selection decisionsin 14 of 84, across 9 files
Retry only transient errorsin 14 of 84, across 9 files
Track spend with immutable cost recordsin 13 of 84, across 8 files
Cache system prompts over 1024 tokensin 12 of 84, across 7 files
Check the budget before each API callin 12 of 84, across 7 files
Start with the cheapest modelin 9 of 84, across 8 files
Back off exponentially between retriesin 9 of 84, across 8 files
Review costs weeklyin 8 of 84, across 6 files
Use reserved capacity for steady workloadsin 8 of 84, across 6 files

Said here and by no other author read

run the usage script with python3
pass --format json for JSON output
pass --sessions-dir to override the sessions directory
report turns, token counts, and cost per model

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.