Case 02609

Skill knownasnaffy/prompthound/dataset/case_02609

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 knownasnaffy/prompthound --skill case_02609

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

2 things to look at

no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

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: 1 file

4.1 KB alongside SKILL.md, 1 of them executable

scripts/

usage.pyruns4.1 KB

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.