Workflow note

How to track AI usage across ChatGPT and Claude

If you switch between ChatGPT and Claude, the hard part is not finding two dashboards. It is remembering which allowance is close to a reset and which reading is current.

Updated 13 August 2026Workflow

Start with the decisions you actually make

Most people do not need a full analytics suite for subscription usage. They need answers such as: “Can I keep this long task in Claude?”, “Should I move this chat to ChatGPT?”, or “When will this window renew?” Build your tracking view around those decisions.

ChatGPT and Claude expose different kinds of allowance information. OpenAI describes plan- and model-specific limits and fallback behavior. Anthropic describes a conversation budget whose shape can change with message length and model. The names and windows do not map one-to-one, so a tracker should preserve the provider label rather than invent a universal unit.

A five-step setup

Connect only sessions you already use. Open each provider in Chrome and confirm you are signed in to the intended account.
Keep provider names visible. “ChatGPT” and “Claude” should never become an anonymous combined meter.
Show every important window. A short session limit and a weekly limit answer different planning questions.
Use reset times as the action signal. When usage rises, the next reset tells you whether waiting or switching is sensible.
Check freshness before acting. A stale reading should prompt a refresh or provider-page check, not false confidence.

What a combined tracker should show

A practical view should keep provider names and windows separate, show the next reset, and make stale data obvious. It should reduce checking without pretending to replace either provider’s account page.

For privacy, check whether a tool reads a provider page, local logs, an API, or copied session cookies. Also check whether it needs an account, cloud sync, or access to message content.

Privacy check: ask whether a tool needs an account, API key, copied session cookie, or access to page content. Those choices are more important than a colorful percentage ring.

When a combined tracker is not enough

If you are debugging token spend from local coding agents, a desktop log reader may be a better fit. If you need team dashboards or cross-device history, you may want a hosted product. This page is about the small, browser-local use case: keeping provider allowance signals visible while you work.