tokentab: A CLI that reads Claude Code, Codex, and Gemini CLI session logs and works out how much they cost, by model

by wzchav · Claude Skill · ★ 225

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install tokentab

git clone https://github.com/wzchav/tokentab

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 69/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

aiapiclaudeclaude-codeclaude-toolgeminitoken-usage

Quick Facts

Stars225
Forks14
LanguagePython
CategoryClaude Skill
LicenseMIT
Quality Score69/100
Last Updated2026-08-20
Created2026-08-12
Platformsclaude-code, cli, codex, gemini, python
Est. Tokens~14k

About tokentab

tokentab tokentab reads the session logs that Claude Code, Codex, Cursor and Gemini CLI already leave on disk and adds up token usage and cost - broken down by model, by project, by day, and by the kind of work each session was doing. It runs entirely locally: no account, no API key, nothing leaves your machine.

Compatible Skills

These tools work well together with tokentab for enhanced workflows:

  • tokentab — semantic(0.69)+complementary+same_lang+similar_pop+shared_platform (74%)
  • skills — semantic(0.36)+complementary+same_lang+similar_pop+shared_platform (63%)
  • ai-limit — semantic(0.33)+complementary+same_lang+similar_pop+shared_platform (62%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

View on GitHub → Browse Claude Skill tools