Text Summarizer

How to get a useful extractive summary

Text Summarizer uses an extractive approach: it selects sentences that already appear in your source instead of writing new ones. The tool scores sentences using repeated content words, position in the document, and length, then returns the strongest candidates in their original order. That makes it a practical way to triage a long report, review a research abstract, or decide which section of an article deserves a closer read.

The summary length control selects between 3 and 10 key sentences. If the source has fewer sentences, the result will be shorter than the requested number. We found that the method works best on structured articles, reports, and explainers where important terms repeat naturally. Personal essays, interviews, and highly technical passages can be less predictable because tone and context matter more than word frequency.

Remove navigation text, cookie notices, citations, and repeated headings before pasting when possible; those fragments can look like important sentences to the ranking logic. Treat the result as a map of the source, not as a replacement for it. Before using a summary in notes or a presentation, check the selected sentences against the full document so an important qualification is not lost.

Common ways to use it

• Students reviewing a long reading assignment and making a quick list of the main claims to revisit.
• Researchers and analysts scanning several reports before deciding which documents need a full read.
• Content teams turning a transcript or draft into a short internal brief for comments and planning.

Frequently asked questions

Does the summarizer rewrite the text?

No. It does not paraphrase or generate new language. Every item in the summary is a sentence copied from the text you provide, which preserves the original wording but can sometimes miss nuance.

Why did I get fewer key points than requested?

The requested number is a maximum. If the source contains only five sentences, the tool cannot return ten, and very short text may produce a summary that feels almost identical to the input.

Can I summarize a meeting transcript?

You can, but results depend on clean sentence punctuation. Remove timestamps, speaker labels, and filler lines first so the ranking logic can focus on complete statements rather than transcript noise.