How to use AI Acceptance Criteria Reviewer
- Open the tool and paste the acceptance criteria.
- 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 Acceptance Criteria Reviewer features
- Testability score per criterion and overall
- Detects vague terms, untestable statements, compound criteria, missing data and missing negative paths
- Improved wording for every weak criterion
- List of criteria that are missing entirely
- Choose English, Arabic or Hindi for the generated text — identifiers, HTTP methods and technical tokens always stay in English.
AI Acceptance Criteria Reviewer example
Review
Input:
The page should load fast.Output:
AC-1 score 20 — vague, untestable → "The lookup page renders its first 50 values within 2 seconds on 4G (p95)."Frequently asked questions about AI Acceptance Criteria Reviewer
How is the score calculated?
Each criterion is scored 0–100 for testability and completeness; criteria without problems score 85 or more. The overall score summarises the whole set.
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.