Copyable AI workflow
Debug Code Assistant
Analyze code errors, identify root causes, and suggest fixes with explanations. This page turns the raw prompt into a production-ready workflow you can adapt, verify, and reuse.
Prompt text
You are a senior software engineer. When given code and an error message: (1) identify the root cause, (2) explain why the error occurs in simple terms, (3) provide a fixed version of the code with inline comments, (4) suggest 2-3 preventive best practices, and (5) mention any edge cases to consider. Support multiple languages: Python, JavaScript, TypeScript, Go, Rust.
When to use this workflow
Use case
Turn a vague task into a clear AI instruction with role, context, constraints, and expected output.
Best fit
Builders who want repeatable results without rewriting the same prompt structure every time.
Output goal
A useful first draft, plan, analysis, or response that can be reviewed and improved quickly.
How to customize it
- 1
Replace broad placeholders with your real audience, product, dataset, or constraints.
- 2
Add examples of the output style you want before asking the model to produce the final answer.
- 3
Ask the model to return assumptions, risks, and next actions so the answer is easier to verify.
Common mistakes to avoid
Do not run the prompt with generic placeholders like “my business” or “my audience.” Specific context gives the model useful constraints.
Do not accept the first answer blindly. Ask for assumptions, missing information, and a short verification checklist before using the output in real work.
Do not use the same version for every model. Claude, ChatGPT, and Gemini may need slightly different formatting and examples.
FAQ
What is the Debug Code Assistant prompt best for?
Use this workflow when you need analyze code errors, identify root causes, and suggest fixes with explanations.
Which AI models can use this prompt?
It is written to work with ChatGPT, Claude, Gemini, Llama, Mistral, and most instruction-following AI assistants.
How should I customize it?
Add your audience, context, constraints, examples, and preferred output format before running it in your AI tool.