Optimize content for voice search queries. Analyze question formats, conversational tone, and featured snippet readiness for smart speakers.
This tool reads a block of text and scores it for voice-search readiness. It checks whether the heading or first line is phrased as a real spoken question, whether a direct answer follows immediately, whether the sentences sound conversational rather than written, and whether the answer is short enough to be read aloud. The output is a scored report with a checklist of what to tighten. The thing most users get wrong: voice search is not a separate index, and assistants usually read back featured snippets, so this score measures snippet-shaped answers, not a reason to build a second, voice-only version of a page.
A concrete input and expected output from the current implementation.
Input
How do I remove a stain from a white shirt? Mix one part white vinegar with two parts cold water. Dab the stain with the mixture. Rinse with cold water and repeat until the stain lifts.
Expected output
Question match: high - the heading 'how do i remove a stain from a white shirt' uses the how-do-i pattern typical of spoken queries. Answer distance: direct - the first sentence (10 words) states the method immediately after the question. Answer length: 26 words across 3 sentences, average 8.7 words per sentence - comfortably under the spoken-answer ceiling. Tone: conversational - imperative instructions, plain vocabulary, no jargon or acronyms. Format: single paragraph; numbered steps would open list-snippet eligibility. Readiness: 85/100 - publish-ready as written.
Every figure follows from the pasted text: the heading matches the how-do-i template, the answer opens in the first sentence and totals 26 words (10 + 6 + 10), averaging 8.7 words per sentence, and the plain imperative phrasing keeps the tone score high. Nothing in the report depends on query volume or competitors.
The analyzer takes the first sentence or heading, lowercases it, and matches it against question templates - 'how do i', 'what is', 'why does', 'can you', 'where can', 'when should' - plus bare interrogatives. It counts the words in the question and checks whether the rest of the text answers within the first sentence or two. Question-shaped phrasing is the signal that content uses the register people actually speak.
It measures the answer block: total word count, sentence count, average sentence length, and structural markers such as numbered steps, bullet lists and transition words. Answers that start immediately after the question, stay under the tool's spoken-answer length ceiling, and use plain vocabulary score higher, because those are the features search engines weigh when they select the short answer a voice assistant reads back.
No. The score means your text has the features assistants look for - a direct, concise, question-matching answer in conversational tone. Whether that answer is actually selected depends on the page's authority, relevance signals, and whatever competing pages offer. Treat the check as an eligibility test, not a ranking prediction.
No. Question-form headings help where real queries take that shape - how-to, comparison and definition searches - but forcing 'how do i' into every heading reads as keyword stuffing and hurts readability. Match the question pattern on pages meant to answer spoken queries, answer directly in the first paragraph, and keep the rest of the page natural.
The example and behavioral notes were checked against the browser implementation. Standards and primary references below define the relevant format, formula, or platform behavior.
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