Normalize the view
Put both tools on the same dashboard with percent used, reset time, and the length of the active window. Do not compare sixty Codex prompts with sixty Claude Code prompts. One agent may inspect more files, reason longer, or call more tools for the same user request.
Instead, compare tasks completed per window. Pick a few recurring jobs such as fixing a failing test, adding a feature, reviewing a pull request, or writing migration notes.
Watch the expensive ingredients
Both providers say task complexity and context affect consumption. Large repositories, long-running sessions, heavy reasoning, and broad instructions tend to cost more capacity than bounded work. Parallel agents can multiply that effect because several contexts are active at once.
Record which tool handled the task, the starting and ending percentages, and whether the result was usable. That is enough to produce your own value comparison without guessing at hidden formulas.
Use both limits as routing signals
If Claude Code is near its weekly boundary and Codex has room, move the next implementation task. If Codex is close to a short reset, give it a small review job and keep the longer task elsewhere.
People increasingly use more than one coding assistant because the strengths and limits are different. A side-by-side tracker turns that overlap into a deliberate workflow instead of a last-minute scramble.