Debug Error Prompt: Fix Code Fast

This debug error prompt diagnoses any error message with root cause, fix, and prevention steps. Paste the error and code, run in any AI tool.

The prompt

Role:
Act as a senior software engineer debugging production code.

Context:
Language/framework: [LANGUAGE]. Full error message: [ERROR_MESSAGE]. Relevant code: [CODE_SNIPPET]. Surrounding context (what was attempted, environment): [CONTEXT].

Task:
1. Identify the root cause of the error in one paragraph.
2. Explain the exact line or logic that triggers it.
3. Provide the corrected code in a code block, with comments marking each change.
4. List 2 alternative fixes with trade-offs.
5. Suggest one prevention: a test, linter rule, or pattern that catches this earlier.
6. Rate fix confidence 1-10 and state what extra information would raise it.

Format:
- Root cause
- Triggering line explained
- Fixed code (code block)
- Alternative fixes (2 with trade-offs)
- Prevention
- Confidence rating

Constraints:
- Do not rewrite unrelated parts of the snippet.
- If the error is ambiguous, state the assumption explicitly before the fix.
- Keep explanations precise; no beginner-tutorial filler.
- Never suggest disabling security features as a fix.

Variables to fill in

Replace each [variable] in the prompt with your own details:

[LANGUAGE] [ERROR_MESSAGE] [CODE_SNIPPET] [CONTEXT]

Example input

LANGUAGE: Python 3.12 / pandas; ERROR_MESSAGE: KeyError: 'user_id'; CODE_SNIPPET: df.groupby('user_id').sum(); CONTEXT: CSV loaded with pd.read_csv, column may be named 'userId'

How to use this prompt

Copy the prompt. Paste the full error message and minimal code that reproduces it. Run in any AI tool, then test the fix before committing.

Tips for the best results

Tip: Include the full stack trace — the fix quality depends on it.
Tip: Reduce the snippet to the smallest reproducing case first; the AI diagnoses faster.
Tip: Ask a follow-up: explain why the fix works, to prevent repeat mistakes.