Start with the official views
OpenAI recommends checking Settings or the usage dashboard when you approach a limit. In an active Codex CLI session, the `/status` command is the fastest direct check. Those surfaces tell you which allowance is constrained and when it should recover.
The difficulty is remembering to check while you are deep in a task. A persistent indicator solves the memory problem. Super Notchy reads the local Codex sign-in and keeps the available limit windows beside the work instead of behind another page.
Track work, not messages
A small script may use a fraction of the allowance consumed by a large repository task. Long context, deeper reasoning, tool calls, and extended sessions can all change the rate. That makes a raw message count a weak forecasting tool.
Watch the change before and after representative tasks. Label them mentally as light, medium, or heavy. After a week, you will have a practical map of what your plan can handle, even when exact provider formulas change.
Plan around resets
Reset times turn usage into a scheduling decision. If a limit clears in forty minutes, use that time for review, tests, or documentation. If the constrained window will not reset until tomorrow, route the next task to Claude Code, Cursor, a local model, or another available tool.
The goal is not to maximize every meter. It is to avoid discovering a limit halfway through the one task that needed continuity.