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[ARTICLE · art-71097] src=dev.to ↗ pub= topic=developer-tools verified=true sentiment=↑ positive

I built a terminal tool to see your AI coding limits before they stop you

A developer built quota, a terminal tool that displays remaining usage for AI coding tools like Claude Code and Codex, reading provider state locally to avoid API calls. The tool aims to prevent mid-task rate limit interruptions by showing quota and reset times at a glance.

read1 min views1 publishedJul 23, 2026

The worst moment in a coding session is hitting a rate limit mid-task.

You're deep in a refactor. Claude Code stops. Or Codex resets. And you spend the next 20 minutes switching tools, losing context, or just waiting. The "Codex Resets" thread on Hacker News got 270 points and 175 comments. The pain is widespread.

The problem isn't the limit — it's that you don't know how close you are until you hit it.

I built quota to fix that.

$ quota

  quota — your ai usage, at a glance

  Claude Code   ████████████░░  3h 12m of 5h    reset in 2h 48m
  Codex         ███░░░░░░░░░░░  3 of 40 reqs    reset in 4h 12m
  Cursor        ──────────────  not connected

One command. Shows remaining usage for every AI coding tool you have connected, along with reset times.

You can also run it in watch mode:

quota watch 30   # re-check every 30 seconds

Or pipe it into scripts:

quota --json | jq '.providers.claude_code.percent_remaining'

quota

reads provider state locally — no API calls, no accounts, no telemetry. It reads from ~/.claude

and ~/.codex

directly, the same files the tools themselves write. Everything stays on your machine.

npm install -g @ozperium/quota
quota

Claude Code and Codex don't surface remaining quota prominently. You either have to open a browser dashboard or wait for the error. Neither is useful when you're mid-task in a terminal.

quota

lives where you work — in the terminal, right next to your code.

GitHub: https://github.com/Ozperium/quota

npm: https://www.npmjs.com/package/@ozperium/quota

Also in the stack: AgentSpec for testing AI agent behavior, and AICostTracker for tracking what you're spending on AI APIs.

source & further reading
dev.to — original article Online Reinforcement Learning for Large Language Models Migrating a live x402 service from V1 to V2 on Base mainnet MythX shut down in March and nothing replaced it so I built something
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