Extract the most significant words from any text as ready-to-use hashtags
This tool lowercases your text, strips a standard list of common English stopwords (a, the, for, and, to, of, in, on, is, are, and dozens more), counts how often each remaining word appears, and turns the most frequent ones into hashtags — ranked by frequency, not by any AI judgment of "importance". You can also add your own custom hashtags manually, which get merged into the final list. It's general-purpose and works for captions on any platform, not just YouTube.
Tips: longer, more specific source text tends to produce more useful hashtags than a short caption, since frequency-based ranking needs enough words to find real patterns. Mix a couple of broad terms with a few specific ones for the best reach-vs-relevance balance.
No — it's a straightforward frequency count after stopword removal. It doesn't understand meaning or context, just counts how often each significant word appears.
Common English words that carry little topical meaning on their own — articles, prepositions and conjunctions like "a", "the", "for", "and", "to", "of", "in", "on", "is", "are", "was", "were", "this", "that", and similar. Removing them lets genuinely distinctive words rise to the top of the ranking.
Yes — this tool is general-purpose, not tied to any one platform. It works for Instagram captions, blog posts, tweets, product descriptions, or any text you want hashtags for.
Custom hashtags are always included and deduplicated against the extracted ones — if one seems missing, check for extra spaces or that it's separated by a comma from the others.
No — the entire extraction and ranking process runs locally in your browser with plain JavaScript. Nothing you paste is uploaded or logged.