Before expensive token usage
Large refactors, architecture changes, and multi-file edits are costly to redo if the model is having a bad day.
When to check
When the model feels off
If the same prompt suddenly gives shallow output, misses assumptions, or writes inconsistent code, check the current status signals.
Before long implementation sessions
Keeping the small popup visible makes it easier to notice status changes while you work.
How to read the score
- 99%
- No major official degradation signal is visible for the monitored Code AI services.
- Caution
- Official status signals suggest relevant degradation. Consider postponing expensive tasks.
- When unsure
- Keep work small, avoid irreversible decisions, and delay large generations until the signal returns to normal.