Codex weekly limits are disappearing way too fast for me
If you're using this for a real-world AI workflow, you know that predictability is everything. Having your limits vanish into thin air mid-sprint is a nightmare, especially when you're relying on the LLM agent to handle repetitive boilerplate or complex refactoring. I've tried refreshing the session and checking my API logs, but the math just isn't adding up.
Potential Culprits
Since I can't find a clear explanation in the docs, I've been speculating on what's actually happening here:
- Token Overhead: It's possible that the context window is being filled with massive system prompts or historical logs that I'm not seeing, meaning every "small" question is actually costing thousands of tokens.
- Hidden Retries: If the connection is unstable, the system might be retrying requests in the background. If each retry counts against the quota, a few glitches could wipe out a day's worth of limits in minutes.
- Indexing Processes: Some tools index your entire codebase to provide better context. If Codex is re-indexing files every time I save, that could be triggering massive hidden consumption.
How to Audit Your Usage
For anyone else worried about their limits, I suggest a few manual checks to see if you're being ghosted by your own quota:
1. Monitor the exact number of tokens returned in the response headers if you have access to the raw API calls.
2. Clear your conversation history frequently to ensure you aren't sending a massive "memory" block with every new prompt.
3. Check if you have any plugins or third-party extensions running that might be polling the API for "autocomplete" suggestions in the background.
If this is a bug, it's a critical one because it makes planning a development cycle impossible. I'm trying to build a practical tutorial for my team on how to integrate this into our pipeline, but I can't recommend a specific tier if the limits are this volatile. I'm going to try a clean reinstall of the CLI and see if the drain persists, but at this point, it feels like a backend accounting error.