Bug Explainer
Turn cryptic errors into plain English
Paste an error message, stack trace, or failing test output and get a clear, actionable explanation of what went wrong, why it happened, and exactly how to fix it — with code examples tailored to your stack.
GPT-6 Luna
for 200K tokens a month · 80% input / 20% output
Why this model
For this workload — 200K tokens a month, 80% of them input — it comes to about $0.04 a month, the lowest of the models suggested here.
Alternative models
Implementation tips
- 1
Always include the surrounding 20–30 lines of code with the stack trace — the model pinpoints the root cause far more accurately when it can see the actual code rather than just the error message.
- 2
Ask for the explanation in three parts: 'What happened', 'Why it happened', 'How to fix it' — this structure ensures junior developers get the full mental model, not just a patch.
- 3
Log which errors are pasted most frequently to your bug explainer — these are your highest-leverage targets for test coverage or refactoring, revealing systemic fragility in your codebase.