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.
A full quality review of a single prompt across clarity, ambiguity, specificity, and structure — what a well-built prompt looks like when it scores well.
It helps to see what good looks like. This loads a well-built prompt — a role, a stated objective, headed requirements, a length limit, a named format — and reviews it at strict setting, where it still scores high. The review shows why: clear objective, no ambiguity flags, strong specificity, real structure. Used on your own prompts, the same review surfaces what is missing. It reviews and reports a single prompt; it neither rewrites it nor ranks it against another.
Paste a prompt to review
Yours, or a strong example to study.
Review all four axes
A full quality read-out, strict if you choose.
See what good looks like
A well-built prompt scores high for visible reasons.
It only diagnoses; the report states "This is a read-only diagnosis — the prompt is not modified." Prompt Readability Checker scores four axes (Clarity, Ambiguity, Specificity, Structure) and lists observations, then points elsewhere for changes: Prompt Cleaner for redundancy, Prompt Rewriter for strength, Prompt Formatter to reshape. Producing the improved version is not what this does.
How many of six concrete anchors are present: number, length limit, format, audience, examples, and criteria. In the loaded well-built example it reads "5 of 6" for an 83/100 specificity score, showing which anchor is missing. Run on your own prompt at the Strict strictness setting, the same six-anchor check surfaces which specificity slots you left empty.
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.