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.
The first step to a more readable prompt is seeing what hurts readability now. Get the diagnosis — long sentences, stacked clauses — then fix it elsewhere.
You cannot improve readability you have not measured. This loads a run-on prompt that stacks a dozen requests into one sentence and diagnoses exactly what drags readability down: a very long average sentence, little structure, requests blurring together. The observations name each issue precisely, which is what makes the next step easy. But the next step is not here: this tool diagnoses, and the actual rewriting belongs to the Prompt Rewriter, the trimming to the Prompt Cleaner. Diagnosis first, treatment there.
Paste the hard-to-read prompt
A run-on or densely packed one.
Get the precise diagnosis
Long sentences and stacked clauses named exactly.
Fix it in the right tool
Rewrite in the Rewriter, trim in the Cleaner.
It only diagnoses — the report states "This is a read-only diagnosis — the prompt is not modified." It names what hurts readability, like an average sentence length of 67.0 words flagged as long and vague quality terms (good, relevant), then routes the rewrite to the Prompt Rewriter and trimming to the Prompt Cleaner. It surfaces issues and scores; it can't catch everything.
It counts how many of six concrete anchors — number, length limit, format, audience, examples, criteria — the prompt includes; here 0 of 6 drives the Specificity score to 0/100, with notes that no length or format constraint was detected. It's an analysis of your pasted prompt, so a low anchor count flags a gap to fill, not a verdict on the wording itself.
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.