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.
Diagnose a prompt before you send it: explainable scores for clarity, ambiguity, specificity, and structure, with observations that name where it is vague.
A prompt can read fine to its author and still be ambiguous to the model. This checks one before it ships, scoring four axes — clarity, ambiguity, specificity, structure — and explaining each score, then listing observations that point to where clarity may suffer. It loads a reasonably clear prompt so you can see a healthy diagnosis. Crucially, it is read-only: it names the problems and changes nothing. To clean, rewrite, or reshape the prompt, it points you to the right tool.
Paste the prompt
Analyzed in your browser — your prompt is never modified.
Read the four scores
Clarity, ambiguity, specificity, structure — each explained.
Act on the observations
They name where it is vague; the fixing happens elsewhere.
Clarity, ambiguity, specificity, and structure — each scored and explained. The healthy sample here shows Clarity 90, Ambiguity 100, Specificity 50, Structure 65, with the STRUCTURE ANALYSIS reporting 'Specificity anchors present: 3 of 6 (number, length limit, format, audience, examples, criteria)'. The four axes turn a vague feeling into a concrete diagnosis of where a prompt is thin.
In the OBSERVATION NOTES, which name the specific gap rather than just flagging a number. On this otherwise-clear prompt the notes point out 'No explicit output format was detected', so you know exactly where clarity may suffer. The check is read-only and fixes nothing — it hands you off to the Prompt Cleaner, Rewriter, or Formatter for the actual change.
Answer the question directly: a clarity score plus the specific reasons a prompt reads as unclear — vague terms, unstated objective, missing specifics.
Surface the ambiguity a model will exploit: vague quantities, hedges, undefined time, open-ended lists, and conflicting instructions — flagged, not fixed.
Words like "good", "engaging", and "professional" feel like instructions but specify nothing. Find them so you know where the prompt leaves things open.
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.