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A local token-cost auditor for coding agents ships quietly

`tokentab` is a free CLI that reads local session logs from Claude Code, Codex, Cursor, and Gemini CLI and reports token cost by model, project, and.

Enterprise DNA |
A local token-cost auditor for coding agents ships quietly

AI Pulse · Under the Radar

The play

Track token costs with a local auditor before renewing subscriptions or expanding agent use, separating model, project, and daily spend.

If you’ve got developers or yourself running Claude Code, Codex, Cursor, or Gemini CLI, you’ve probably wondered what those sessions actually cost you versus what you’re paying for the subscription. A small tool called tokentab just showed up to answer exactly that question, quietly and without any fuss.

It’s a free command line tool that reads the local session logs those coding agents already keep on your machine. No account, no API key, nothing to sign up for. It just parses what’s already there and tells you token cost broken down by model, by project, and by day. In two days on GitHub it picked up 212 stars and 12 forks, which for a small utility like this is a fast, real signal that people needed it. You can see the project here: tokentab on GitHub.

Why this matters to you as an owner. There’s a growing conversation right now, especially on X, about whether flat $20 or $30 a month AI subscriptions actually cover what heavy users are burning in real compute. Most business owners have no visibility into this. You get a bill, you get a usage cap warning, and that’s it. A tool like tokentab gives you an actual paper trail. If you’ve got a few developers on paid coding assistant plans, you can finally see which projects are burning the most tokens and which model is driving the cost, instead of guessing.

It won’t tell you whether your subscription price is fair. That debate is still unsettled and mostly anecdotal right now. But knowing your own usage patterns puts you in a much better spot to make that call yourself. This kind of cost visibility across tools and projects is exactly the kind of thing we build into an AI command centre, so it lives in one place instead of scattered log files.

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