How to use AI Bug Description Generator
- Open the tool and paste your notes about the bug.
- Optionally add context (feature description, acceptance criteria, environment) — the more concrete the input, the better the result.
- Pick the options (count, output language, focus) and press the action button.
- Review the structured result in the table, then copy or download it as Markdown, CSV or JSON.
AI Bug Description Generator features
- Complete report: title, summary, environment, preconditions, numbered steps, expected vs actual, severity, priority, frequency, workaround
- Attachments checklist and questions for missing details
- Rendered in Markdown or Jira wiki markup
- Never invents facts that are not in your notes
- Choose English, Arabic or Hindi for the generated text — identifiers, HTTP methods and technical tokens always stay in English.
AI Bug Description Generator example
Notes → report
Input:
discount code twice → NaN total, chrome on mac, reload fixes itOutput:
## [Checkout] Order total shows NaN when a discount code is applied twice
**Severity:** Critical · **Priority:** P0
### Steps to reproduce
1. …Frequently asked questions about AI Bug Description Generator
What if I do not know the browser or version?
Leave it out. The report keeps the field minimal and lists the missing details as questions instead of inventing them.
Is my input stored?
No. Your text is sent to the Mutqan AI service and the structured result is returned to your browser. We do not store prompts or outputs — only anonymous usage counters used for daily limits.
How many generations can I run?
Anonymous visitors get a small daily allowance per network address; registered users get a higher daily quota. The remaining count is shown under every result.
Can I get the result in Arabic or Hindi?
Yes — choose the output language. Natural-language fields are written in that language while identifiers, HTTP methods, paths and other technical tokens stay in English.
Technical notes
Your input is sent to the Mutqan AI service over an encrypted connection; prompts and results are never stored — only anonymous usage counters used for rate limiting.
The AI must answer with strict JSON that is validated against a schema on the server before anything is rendered; malformed answers are retried once and then rejected with a clear message.