Paste a long article and instantly get back the most important 30% of sentences — preserving the original wording while cutting filler. Powered by classic TF-based extractive summarization.
A summarizer condenses long text into shorter form. Two approaches: extractive (pick the highest-scoring original sentences) and abstractive (rewrite in new words using AI). Extractive is faster, more accurate, and doesn't fabricate facts — making it ideal for research, news consumption, and pre-reading triage.
The tool tokenises sentences, scores each by the frequency of meaningful words it contains (after removing stop-words like 'the' and 'and'), and keeps the top 30% in original order. The result reads naturally because every sentence is real text from your input.
Use it to triage long news articles before reading, to summarise meeting transcripts, to extract key points from research papers, to compress reports for executive summaries, and to brief yourself before reviewing a colleague's draft.
Works best on factual prose (articles, reports, transcripts). Less effective on creative writing where every sentence carries narrative weight. For abstractive (rewritten) summaries, you need a paid LLM API.
TF (term frequency) — sentences with the most repeated topic words score highest.
Paste the text directly. For PDFs, use the PDF To Word tool first to extract the text, then paste here.
30% is the default. Shorter ratios produce tighter summaries; longer preserves more nuance.
Explore more text analysis on the tool hub — or jump straight to the Word Counter.