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I finally counted my tokens before they hatched

↗ Quelle (dev.to)
🗣️ Stimme:
📑 Inhaltsübersicht

Hello, I'm Maneshwar. I'm building git-lrc, a Micro AI code reviewer that runs on every commit. It is free and source-available on Github. /




A high-performance CLI tool and visualization dashboard for tracking token usage and costs across multiple AI coding agents.




Tip


v2 is here — native Rust TUI, cross-platform support, and more.

I drop new open-source work every week. Don't miss the next one.













on GitHub for more projects. Hacking on AI, infra, and everything in between.
— and surround yourself with the world's top-tier vibers.







| |


to submit your usage data to the leaderboard and create your public profile!




Overview



Tokscale helps you monitor and analyze your token consumption from:



























Logo Client Data Location Supported

~/.local/share/opencode/opencode.db (1.2+, all channels including opencode-stable.db) or/and ~/.local/share/opencode/storage/message/ (legacy/unmigrated)		 ✅ Yes

~/.claude/projects/ and ~/.claude/transcripts/
 ✅ Yes

~/.openclaw/agents/ (+
…




All these tools already write logs to your machine.



tokscale just reads what's sitting there, prices it against live rates, and hands you the damage in a terminal UI.



No account required to see your own numbers.



Here's the flow, because I think it's cooler than it has any right to be:



, the astrophysics idea that ranks a civilization by how much energy it can harness.



Type I bends a whole planet's energy. Type II captures an entire star. Type III commands a galaxy.



The pitch is that in AI-assisted dev, tokens are the new energy. So tokscale ranks you on the same idea:



I opened the tool fully expecting to be a humble Type I. A polite, energy-conscious little developer.



Reader, I was not.





Was it worth knowing?



Honestly, yes. Not because the number was scary (okay, it was a little scary), but because I finally had a real number instead of a vibe.



I could see that most of my spend came from one specific "just one more prompt" habit late at night, and that one model was doing the heavy lifting while I paid premium rates for another out of pure muscle memory.



That's the actual value here. It turns "eh, probably fine" into a receipt you can act on.



A token of appreciation, if you will, for your own bank account.



If you're pair-programming with AI every day like I am, spend the sixty seconds.



Run it, poke around the dashboard, and find out which Kardashev type you really are.



Worst case, you learn something.



Best case, you save enough to justify the subscription that got you here.



You can grab it on



AI agents write code fast. They also silently remove logic, change behavior, and introduce bugs — without telling you. You often find out in production.



git-lrc fixes this. It hooks into git commit and reviews every diff before it lands. 60-second setup. Completely free.



Any feedback or contributors are welcome! It's online, source-available, and ready for anyone to use.



⭐ Star it on GitHub:





GitHub logo



Free, Micro AI Code Reviews That Run on Git Commit






| | | | | |



git-lrc





Free, Micro AI Code Reviews That Run on Commit






  






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