Paste any text to see a ranked word frequency table. Check keyword density, spot overused words, and analyse content in seconds.
Paste a draft article and look at the top words. If your target keyword appears more than 2-3% of total words, it may be flagged as keyword stuffing by search engines. A 1-2% keyword density is generally considered natural and safe.
The frequency table quickly reveals if you have used the same adjective, adverb, or phrase repeatedly. Words like 'very', 'really', 'great', or 'amazing' appearing dozens of times are a sign to vary your vocabulary.
Stop words are common connecting words like 'the', 'and', 'of', 'to', 'a', 'in'. The tool filters them out by default so you see meaningful content words. Toggle stop words on to see the full word list.
Use this tool to analyse competitor content. Paste their article text and see which words they use most — these may be the key terms their content is optimised around.
Paste any text to instantly see a ranked table of word frequencies. Useful for checking keyword density in articles, spotting overused words, or analysing competitor content.
500-word article with target keyword appearing 8 times
Keyword density: 8/500 = 1.6% — within safe range
Blog post where 'really' appears 12 times
Immediately visible in the table — a clear signal to vary word choice
Competitor article pasted in
Top 10 words reveal their content's main themes and keyword focus
Calculating keyword density manually
1.67% — within the recommended 1-2% range
The concept of 'term frequency' has deep roots in information retrieval science. The TF-IDF (Term Frequency-Inverse Document Frequency) metric, developed in the 1970s, remains one of the most widely used techniques in search engines and natural language processing. It weights how often a word appears in a document against how common that word is across all documents — rewarding specific, distinctive terms over generic ones.
Frequency shows how often words or phrases appear in the text, which can reveal repeated topics, vocabulary, and possible overuse. It is a descriptive signal, not a score for writing quality or search ranking. Read the surrounding sentences as well: a word may be frequent because it is a necessary term, navigation label, or quoted phrase.
Removing stop words such as “the” and “and” can make topical words easier to spot, while keeping them gives a fuller picture of the text. Use the setting that matches your question and compare results rather than treating a standard stop-word list as universal. Names, domain terms, and spelling variants may need manual grouping.
No. Search systems look at usefulness, relevance, structure, language, and many other signals; repeating a phrase unnaturally can make copy harder to read and may be counterproductive. Use frequency analysis to identify gaps or accidental repetition, then write naturally for readers and support claims with clear, original information.
A basic counter usually matches the exact words or phrases it recognises, so plurals, spelling variants, hyphenation, and synonyms may appear as separate entries. Group variants only when they have the same meaning for your analysis, and document the rule you used. Read the source text to confirm that a combined count is not hiding an important distinction.