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text-summarizer

A text summarizer condenses a long document down to its most important sentences using extractive summarization — scoring each sentence by keyword density, position, and relevance to the document's top terms — so readers get the gist in seconds without losing the source's exact wording. The ZTools Text Summarizer runs entirely in your browser using TextRank-style scoring, lets you choose the summary length (5%, 10%, 25%, 50% of original, or a fixed number of sentences), preserves the original sentence wording (no paraphrasing or hallucination), and works offline once loaded.

Use cases​

Reading-list triage — should I read this article?​

Paste a 3,000-word article, pull a 5-sentence summary. Decide in 30 seconds whether to read in full, save for later, or skip.

Meeting notes and transcripts​

A 10,000-word meeting transcript reduced to 20 key sentences. Captures decisions and action items without re-watching the recording.

Student exam revision​

Textbook chapter shrunk to its core 30 sentences. Combined with the original for full review; summary alone for last-minute cram.

Daily news digest​

Paste 5 morning articles, summarize each to 3 sentences. A 60-second briefing instead of 20 minutes of reading.

How it works​

  1. Paste the article or document — Any size. Plain text or markdown. Multi-paragraph documents work best — short pastes don't leave much to extract.
  2. Choose the summary length — Percentage of original (5%, 10%, 25%, 50%) or fixed number of sentences (3, 5, 10, 20). Shorter = key points only; longer = more nuance.
  3. Algorithm scores every sentence — Each sentence gets a score based on: TF-IDF keyword overlap with the document, position (early sentences score higher in news), length (very short or very long sentences are penalized), and relationship to other sentences.
  4. Top sentences are selected and reordered — Sentences appear in the original document's order — not by score — so the summary reads coherently as a shortened version of the original.

Examples​

Input: 3,000-word article on remote work

Output: 5-sentence summary covering the thesis, the supporting argument, and the conclusion.

Input: Meeting transcript (10k words)

Output: 20-sentence summary with decisions, action items, and key debate points.

Input: Wikipedia article

Output: 10% summary that often matches the article's lede paragraphs in coverage.

Frequently asked questions​

Is this AI-generated?

No — it uses extractive summarization, which selects existing sentences rather than generating new text. No hallucination, no paraphrase errors, but also less natural flow than abstractive AI summarizers.

How is this different from ChatGPT summaries?

ChatGPT (and other LLMs) generate new sentences that paraphrase the source. They're smoother but can hallucinate or distort. Extractive summarizers pull verbatim sentences — preserving source accuracy at the cost of natural flow.

What length should I pick?

5-10% for skimming/triage. 25% for studying or note-taking. 50% if the original is very dense or you want minimal information loss. A 5-sentence fixed length works well for news.

Does it work for non-English text?

Yes — the TextRank algorithm is largely language-agnostic since it relies on word co-occurrence rather than language-specific rules. Best results with English; reasonable results with major European languages.

Can it summarize code or structured data?

No — algorithms are tuned for prose. For code summaries, use a documentation generator. For data summaries, use the Statistics Calculator.

Tips​

  • For news articles, shorter summaries (5%) are more useful — most news has the thesis in the first paragraph.
  • For narrative or story-driven content, summarization often loses the point; read the original.
  • Summaries are best for triage and revision, not for replacing primary research.
  • Long documents (10k+ words) sometimes need section-by-section summarization rather than whole-document.

Try it now​

The full text-summarizer runs in your browser at https://ztools.zaions.com/text-summarizer — no signup, no upload, no data leaves your device.

Open the tool ↗

Last updated: 2026-05-05 · Author: Ahsan Mahmood · Edit this page on GitHub