What this error means
tokens burning very fast following extension update is a GitHub Copilot failure pattern reported for developers trying to users report that the openai codex desktop extension rapidly depletes token usage after an update — just 1–2 prompts drop usage by 1%. users want to understand why tokens are consumed excessively and how to fix/prevent it. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.
Why this happens
GitHub Issue #14593 on openai/codex (opened 2026-03-13). Reported by cy-ooi88 with 586 comments — extremely high engagement. Labels: bug, rate-limits. Directly affects paying GitHub Copilot/Codex subscribers. Maps to GitHub Copilot category.
Common causes
- GitHub Issue #14593 on openai/codex (opened 2026-03-13). Reported by cy-ooi88 with 586 comments — extremely high engagement. Labels: bug, rate-limits. Directly affects paying GitHub Copilot/Codex subscribers. Maps to GitHub Copilot category.
Quick fixes
- Confirm the exact error signature matches
tokens burning very fast following extension update. - Check the GitHub Copilot account, local tool state, and provider configuration involved in the failing workflow.
- Compare the failing environment with a known working setup, then change one configuration value at a time.
Platform/tool-specific checks
- Verify the command, editor, extension, or API client that produced the error.
- Compare local settings with CI, deployment, or editor-level settings when the error appears in only one environment.
- Avoid deleting credentials, local model data, or project settings until the failing scope is clear.
Step-by-step troubleshooting
- Capture the exact error message and the command, editor action, or request that triggered it.
- Check whether the failure is account/auth, quota/rate, model/provider, local runtime, or deployment configuration.
- Review the source evidence below and compare it with your environment.
- Apply one change at a time and rerun the smallest failing action.
- Keep the working fix documented for the team or deployment environment.
How to prevent it
- Keep provider/tool configuration documented.
- Record non-secret diagnostics such as tool version, provider name, model name, and command path.
- Add a lightweight check before CI or production workflows depend on the tool.