Being blocked without warning is usually a visibility problem, not a limit problem. Every major tool exposes how much you have used — but they do it in different places, at different granularities, and with different lags. Here is where to look and how to read what you find.
Codex
Two surfaces, and they disagree in a useful way.
The in-product usage view. This is the one to check before starting something expensive. It reflects your position inside the short rolling window. It updates as you work, which makes it feel authoritative — and it is, for what it measures: short-window consumption.
Your account settings page. This is where the longer, outer cap lives. It changes slowly, it is easy to forget about, and it is the one that blindsides people. If the in-product view says you have room but you are still blocked, this is the number to check.
A note on the asymmetry that causes most of the frustration: the short-window display is responsive, so you build a mental model from it. The outer cap is not, so it never enters that model until it is too late.
Claude Code
Claude Code exposes usage both in the terminal session and in the web account view. The terminal one is the more useful of the two because it is where you actually work — checking it costs nothing in context switching.
The thing to understand is that Claude's limits compose the same way Codex's do: a session-scale window plus a longer cap. When you read a single percentage, be clear about which of the two it refers to. "84% used" means something very different at session scale than at weekly scale.
Gemini
Google's tiers are organised by model rather than by a single account-level pool, which means you can be exhausted on one model and unaffected on another. That is genuinely useful if your work can move between models, and it is also why "am I over my limit?" does not have a single answer here.
Check per model, and check which model your current tool is actually routed to. Routing changes silently.
Grok
Limits move with the subscription tier and the product surface, and xAI revises them more often than the others. Rather than memorising a number, memorise where the official page is and check it when it matters.
What not to trust
Community-shared limit tables. They go stale within weeks and there is no signal when they do. Useful for understanding shape; dangerous for making decisions.
Your own memory of last week. Rolling windows mean there is no stable "typical day". Two identical days of work can end in different places depending on the order you did things in.
Anyone's percentage-of-probability estimate for a reset. Resets are vendor decisions, not stochastic processes. A probability implies a model; there is no model.
A routine that costs about twenty seconds
Once a day, before you start the part of your work that is hard to interrupt:
- Check the short-window number.
- Check the outer cap, if your plan has one.
- If either is close, decide now whether today's big task is happening, and reorder accordingly.
The value is not in the numbers. It is in making the go/no-go decision once, deliberately, instead of discovering the answer halfway through a refactor.
Where a reminder fits
This routine handles the predictable half. It cannot help with the other half — a reset landing at 2am your time, or while you are in meetings, or on a day you did not think to check.
That is the narrow, honest job of a reset reminder: it does not tell you what to do, it tells you when the constraint changed. Everything else is still your call.
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