debug-code · gpt-4o · coding · 90% confidence

Debug code with GPT-4o — optimized prompt

A GPT-4o debugging prompt: terse system spec, fenced code + failure, structured root-cause / minimal-diff / risks output, no preamble or generic advice.

90% confidenceUpdated 9/7/2026debug-code · gpt-4o · coding

Original prompt

Hey GPT-4o, can you help me debug this code? It's not working. [PASTE CODE]

Optimized prompt

Act as a senior engineer doing a focused bug review. I give you a code block and the observed failure; you find the actual cause.

Code:
```
[PASTE CODE]
```
Failure: [ERROR MESSAGE or WRONG BEHAVIOUR vs EXPECTED]
Runtime: [language + version, framework]

Return, in this order:
1. Root cause — one paragraph, name the exact line(s).
2. Fix — the minimal change, as a fenced diff.
3. Why it works — two sentences.
4. Other real risks — bullets, or "none".

Rules: no preamble, do not restate my code back to me, no generic best-practice advice. If the cause is not determinable from what I gave you, state exactly which input you need and stop.

Why this GPT-4o prompt works

Tuned for GPT-4o: a short system-style spec with fenced delimiters and a fixed root-cause / minimal-diff / risks output. GPT-4o follows a terse numbered contract closely and degrades on long, chatty prompts, so this one bans preamble and generic advice outright.

What to check in the output

The 'optimized_prompt' clearly delineates distinct steps for debugging, improving the quality of the output.
The 'optimized_prompt' explicitly requests categorized issues and proposed solutions, which the naive version doesn't guarantee.
The 'optimized_prompt' asks for a refactored code block, ensuring a complete solution.