Is My Prompt Clear Enough?
Answer the question directly: a clarity score plus the specific reasons a prompt reads as unclear — vague terms, unstated objective, missing specifics.
Get a single 0-100 clarity score for a prompt, backed by four sub-scores and the reasons behind them — including conflicting instructions that quietly cut clarity.
A clarity score is only useful if you can trust where it comes from. This produces an overall 0-100 score from four explainable sub-scores, and loads a prompt full of conflicting instructions — "detailed and comprehensive, but brief and concise; formal, but casual" — to show how contradictions tank the ambiguity score even when the wording looks confident. The number is the headline; the sub-scores and observations are the receipts. It scores and explains; it does not rewrite to raise the number.
Paste the prompt
Any prompt you want a clarity score for.
Read the score and receipts
An overall number plus four explained sub-scores.
Catch hidden conflicts
Contradictions cut the score even when wording looks confident.
Contradictions drag the single number down. This sample lands at 'Overall clarity: 47/100 (Needs Clarity)' because the AMBIGUITY ANALYSIS finds 'Possible contradictions (5): concise / comprehensive; concise / detailed; brief / detailed; formal / casual; formal / conversational', pulling the Ambiguity sub-score to 25/100. The wording reads assured, but the checker weighs the conflicts, not the tone.
It does not — it scores and explains, changing nothing. The overview marks it 'a read-only diagnosis — the prompt is not modified', giving the headline number plus the four sub-scores as receipts. To act on a low score, the report itself points elsewhere: the Prompt Cleaner for redundancy, the Prompt Rewriter for strength, the Prompt Formatter to reshape.
Answer the question directly: a clarity score plus the specific reasons a prompt reads as unclear — vague terms, unstated objective, missing specifics.
Diagnose a prompt before you send it: explainable scores for clarity, ambiguity, specificity, and structure, with observations that name where it is vague.
Surface the ambiguity a model will exploit: vague quantities, hedges, undefined time, open-ended lists, and conflicting instructions — flagged, not fixed.
A set of before-and-after examples showing exactly what prompt cleanup removes — and what it deliberately leaves alone.
'Make it good', 'be detailed', 'keep it interesting' — vague prompts get vague output. The fix is mechanical: replace every fuzzy word with a checkable instruction.
Formats fuzzy agent instructions into a structured prompt with objective, available tools, constraints, success criteria, and failure handling.
Diagnose a prompt's clarity before you send it — explainable scores for clarity, ambiguity, specificity, and structure. Read-only; it never rewrites.