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Text Summarizer
Summarize an article by automatically picking its most important sentences — extractive summarization that runs entirely in your browser. Choose 1 to 8 sentences.
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Quick Answer
Paste a long passage and get a short summary built from its own most important sentences. The tool scores each sentence by how many frequent keywords it holds, keeps the top few (you choose 1 to 8), and puts them back in their original order. This is extractive summarization — it selects existing sentences rather than writing new ones — and it runs entirely in your browser.
What the Text Summarizer Does
This produces an extractive summary: it picks out the handful of sentences that carry the most weight and joins them, keeping their original order. Nothing is rephrased — the summary is made of your own sentences, word for word.
It is a fast, rule-based tool, not a large language model. It does not understand the text or generate new wording the way an AI writer would. The trade-off is that it is instant, free, repeatable, and your text never leaves your browser.
How It Works
Paste your text and choose how many sentences you want, from 1 to 8.
The tool counts how often each meaningful word appears (ignoring common stop words), then scores every sentence by the combined frequency of its words, divided by the square root of its length so long sentences are not unfairly favoured.
The highest-scoring sentences are selected, put back into their original order, and joined into the summary. It all happens in your browser.
Generation algorithm
- Split into sentences. The text is divided into sentences at full stops, question marks and exclamation marks.
- Score word frequency. Each meaningful word is counted; common stop words are ignored.
- Rank the sentences. Each sentence scores by its words' combined frequency, divided by the square root of its length.
- Select and reorder. The top sentences are kept and restored to their original order to form the summary.
How each sentence is scored
score(sentence) = (sum of its word frequencies) ÷ √(sentence length)
The top N sentences by score are kept, then put back in original order
Words are counted across the whole text; stop words are ignoredWorked example
In a paragraph that repeats compression and image often, the sentence packing the most of those frequent words scores highest and is chosen for the summary.Dividing by the square root of the length stops very long sentences from winning on word count alone. With two or fewer sentences, the text is returned unchanged.
Privacy
Your text is processed entirely in your browser — there is no server, no API call, and nothing is uploaded.
Because it runs locally with no AI model in the cloud, even confidential text stays on your device.
No account, no stored copy; the result is gone when you close the tab.
Technical Details
| Method | Extractive (sentence ranking) |
|---|---|
| Model | None — rule-based |
| Length | 1–8 sentences (default 3) |
| Scoring | Word frequency ÷ √length |
| Output | Your own sentences, reordered |
| Privacy | Runs locally, nothing sent |
| Processing | 100% in-browser |
Standards & references
- Extractive summarization — Selects the most important original sentences unchanged, rather than generating new ones — the simpler, statistics-based family of summarization.
- Not abstractive — Abstractive summaries that rephrase and consolidate ideas need neural networks or a large language model; this tool does not do that.
Accuracy & Limitations
This is extractive, not abstractive. The summary is built from your sentences exactly as written; it never paraphrases, adds transitions, or generates new wording. For a rewritten, flowing summary you need a large language model.
Because whole sentences are pulled out and rejoined, the summary can read a little disjointed — the selected sentences may not flow seamlessly into one another.
Quality depends on the text. Well-structured writing with clear topic sentences summarizes well; loosely organised or very short text gives weaker results. With two or fewer sentences it returns the text unchanged.
It scores by raw word frequency, so it favours sentences full of repeated keywords. It has no understanding of meaning, so an important idea stated only once may be missed.
Real-World Use Cases
Skim an article
Pull the key sentences from a long article before reading it in full.
Shorten notes
Condense meeting notes or research into a few core sentences.
Private summaries
Summarize a confidential document without sending it to any service.
Preview content
Generate a quick gist of a passage to decide if it is worth reading.
When to use it — and when not to
Good for
- Quick, private summaries of well-structured text
- Pulling out the key sentences verbatim
- Offline, repeatable summarizing with no account
Not the best choice for
- A rewritten, flowing summary in new words
- Very short or loosely organised text
- Understanding nuance, tone or implied meaning
For an abstractive summary that rephrases ideas in fresh wording, use a large language model. For sentence and word counts, use the sentence counter.
Frequently Asked Questions
Does it rewrite the text?
No. It is extractive, so it selects your existing sentences word for word and never rephrases them.
Is this AI or a language model?
No. It is a rule-based frequency algorithm, not a large language model, and it does not understand the meaning of your text.
How does it choose sentences?
It scores each sentence by its words' combined frequency divided by the square root of the sentence length, then keeps the top few.
Why divide by sentence length?
So a long sentence does not win simply because it holds more words. It balances keyword importance against length.
How many sentences can I get?
Between 1 and 8, set with the slider. The default is 3.
Why does the summary read a bit choppy?
Because whole sentences are lifted out and rejoined. Extractive summaries can flow less smoothly than ones rewritten by an AI model.
What if my text is very short?
With two or fewer sentences, the tool returns the text unchanged, because there is nothing to rank.
Are stop words counted?
No. Common words such as the, a and and are ignored when scoring, so they do not skew the result.
Will it catch an idea mentioned only once?
Maybe not. It favours sentences with repeated keywords, so a key point stated just once can be missed.
Is my text uploaded?
No. It runs entirely in your browser, with no server and nothing sent.
Does it keep the sentence order?
Yes. The selected sentences are restored to their original order before being joined.
How do I get an abstractive summary?
Use a large language model tool. This one only extracts existing sentences; it does not generate new wording.
References
This is extractive summarization: it scores each sentence by how many frequent keywords it contains, then keeps the top few in their original order. It selects your existing sentences verbatim — it does not rewrite or generate new text, and it is not a large language model. Everything runs in your browser.
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Ready to try the Text Summarizer?
It is free, private and runs entirely in your browser — no sign-up, no uploads, no limits.