Keyword Extractor
A rule-based keyword extractor that finds the keywords in your text: it tokenizes your content, removes stopwords, counts single words and two-word phrases, and ranks them by frequency. It returns the top 10 keywords as chips with their counts — useful for SEO, tagging, and content analysis. Runs entirely client-side.
Examples
A 600-word blog post about home gardening.
Top keywords like garden bed (7), soil (6), compost (5) as chips.
How it works
The text is lowercased and split into words. Single words are counted after removing common words and anything of one or two letters. Two-word phrases are counted when the words sit next to each other, neither is a common word, and the phrase occurs more than once.
Words and phrases are then ranked together by how often they occur, and the top ten are shown with their counts. When a phrase and a single word are tied, the phrase is listed first.
There is no grouping of word forms, so “garden” and “gardens” are counted separately, and nothing is known about search volume: the list shows what your text talks about most, not what people search for. Copy gives the list as plain text with the counts.
How to use Keyword Extractor
Why use this tool
Frequently asked questions
A density checker reports percentages for chosen terms; this ranks the most frequent meaningful keywords and phrases for you to use directly.
No. It is frequency-based tokenization with stopword removal — fully rule-based.
Found a bug or have an idea?
ToolOrbit is actively developed — feedback directly shapes what gets built next.
Send feedback