Claude Code usage limits run on two independent counters: a five-hour rolling window that governs bursts, and a weekly cap measured in active compute hours
— hit either one and your access is throttled until that specific window resets.
This pool is not isolated to the CLI. It is a shared bucket across Claude Code, the Claude.ai web interface, and Cowork, so a heavy morning of web chat directly shrinks what your terminal has left in the afternoon. Optimizing is not about typing less.
It is about not paying for context Claude never needed in the first place.
What the quota counts, and why a full context window is not a usage limit
You have to separate two things that fail in completely different ways. The context window is how much text the model can hold in a single conversation — up to 1M tokens on some paid plans. The usage quota is the metered allowance for total work performed over time. You can have plenty of context space left and still be locked out, because the quota tracks cumulative compute across every session you run.
The two counters work differently. The five-hour rolling window limits prompts based on context length and model choice, resetting five hours after your first prompt in a session. The weekly cap is measured in active compute hours — time when the model is genuinely processing tokens or reasoning. Time you spend reading output or browsing files does not count against it.
This is where most people get confused, and Anthropic's documentation states it plainly: a context or auto-compact warning is not a usage limit. When your context window fills, Claude Code summarizes older history to free space and you keep working. When your quota runs out, you stop until the window resets. Different problem, different fix.
One caveat before you trust any number you read online. Anthropic does not publish exact token quotas. It publishes multipliers — Pro at 1x, Max at 5x and 20x. Every "45 prompts per five-hour window" figure in circulation is a community estimate, not a specification, and it shifts with your context length and model choice.
Why your usage drops fast even when you type very little
The primary driver is context accumulation. Every message you send resends the entire conversation history, every file currently loaded, and all tool definitions. The 50th turn in a session is dramatically more expensive than the first, which is why a one-line question late in a long debugging session still draws heavily on your quota. Prompt caching softens this — repeated content bills at the cheaper cache-read rate — but the volume is still traveling with every request.
A few things consume disproportionately. Agent teams use roughly 7x the tokens of a standard session when teammates run in plan mode, because each teammate maintains its own context window and runs as a separate instance. Pasting file contents directly into the terminal is far more expensive than referencing a path, because whatever you paste sits in context in full for the rest of the session. And leaving Opus as your default burns premium compute on work Sonnet handles at a fraction of the cost.
There is also a quiet baseline. Background conversation summarization for the resume feature and status-checking commands consume a small amount even when you are idle — typically under $0.04 per session. Individually trivial; worth knowing about when you are auditing where your week went.