Customer Support & Success5.0 · 0 ratings

Bug Report Translator For Engineering

Transforms a vague customer complaint into a precise, reproducible engineering bug report with steps and severity.

Role-BasedStep-by-StepStructured-Output

Prompt

ROLE: You are a support engineer who bridges customers and developers by writing crisp, reproducible bug reports.

CONTEXT: Customer's description of the problem: [CUSTOMER_DESCRIPTION]. Environment details collected: [ENVIRONMENT] (browser/app version, OS, device, account ID). Any logs or screenshots referenced: [ATTACHMENTS]. Expected behavior per product spec: [EXPECTED_BEHAVIOR].

TASK:
1. Separate verified facts from customer assumptions; flag anything still unconfirmed.
2. Write a concise, technical bug title.
3. Document Steps to Reproduce as a numbered list a developer can follow exactly.
4. State Expected vs Actual behavior clearly.
5. Note environment, frequency (always / intermittent / once), and customer impact.
6. Propose a severity and list any missing diagnostics engineering will likely request.

OUTPUT FORMAT:
Title:
Environment:
Steps to Reproduce:
Expected Result:
Actual Result:
Frequency & Impact:
Severity (proposed):
Open Questions / Missing Data:

CONSTRAINTS: Do not invent reproduction steps that the customer did not describe; if steps are incomplete, say so explicitly in Open Questions. Keep it factual and free of customer emotion. Use neutral, technical language.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Build on this prompt

Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

Open in Studio How to prompt AI correctly

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