Paste long text and get the most important sentences extracted instantly — a fast, private, browser-based summarizer.
It uses extractive summarization, scoring each sentence by word frequency and selecting the highest-scoring ones, rather than generating new sentences.
No, this uses a statistical, rule-based approach that runs entirely in your browser, rather than an AI language model generating a new abstractive summary.
This works best on text with at least several sentences — very short text (1-2 sentences) won't benefit much from summarization.
Yes, selected sentences are presented in their original order from the source text, not reordered by importance.
This tool creates a summary of long text by identifying and extracting the most important sentences, using a word-frequency scoring approach that runs entirely in your browser — no external AI service required.
There are two fundamentally different approaches to automatic text summarization. Extractive summarization — what this tool does — selects existing sentences directly from the source text based on how important or representative they seem, and presents them as the summary. Abstractive summarization, by contrast, generates entirely new sentences that paraphrase and condense the original meaning, similar to how a human might summarize in their own words — this typically requires a large language model and is not what this browser-based tool performs. Extractive summarization is faster, fully private (no data leaves your browser), and doesn't risk introducing factual errors through paraphrasing, though it can't rephrase or truly condense ideas the way abstractive summarization can.
This tool first breaks your text into individual sentences, then builds a word frequency count across the entire text (ignoring common "stop words" like "the," "a," and "and," which carry little meaning). Each sentence is then scored based on how many frequently-occurring, meaningful words it contains — sentences packed with the text's most repeated key terms score higher, on the theory that these sentences are more likely to represent the core content. The highest-scoring sentences (however many you've requested) are selected and presented back in their original order.
It works less well on very short text, text without clear sentence structure, or content where every sentence is equally important (like a list of distinct facts rather than a flowing narrative).
All summarization happens directly in your browser using JavaScript — your text is never sent to a server or any external AI service.
The underlying assumption behind frequency-based scoring is simple: words that a writer repeats throughout a piece are usually the words carrying its central ideas, while one-off words tend to belong to supporting detail or examples. By excluding stop words before counting, the tool avoids letting filler words like "the" or "and" (which appear constantly but mean nothing on their own) dominate the frequency table. A sentence that happens to contain several of the text's most-repeated meaningful words is treated as a stand-in for the passage as a whole, which is why dense, topic-heavy sentences tend to surface at the top of the summary.
Because this tool only selects and never rewrites, it cannot merge two related sentences into one, shorten a long sentence by trimming clauses, or resolve pronouns that only make sense next to the sentence they originally followed. If a pulled sentence starts with "This means..." or "However, it also...", the summary can read slightly disjointed since the sentence was written to follow something that didn't make the cut. This is a known trade-off of extractive methods generally, not a bug specific to this implementation, and it's worth skimming the output rather than treating it as polished prose.
A good starting point is roughly 10-20% of the original sentence count. For a short 15-sentence blog post, 2-3 sentences is usually enough to capture the gist. For a longer 60-sentence report, 6-8 sentences will typically read more like a coherent abstract. Setting the slider too low on a long document risks losing supporting context; setting it too high defeats the purpose of summarizing at all.
Pasting text with many short, unrelated sentences (such as a bullet list converted to prose) tends to produce a weaker summary, since the frequency-scoring approach assumes a flowing narrative where ideas build on repeated terms. Similarly, pasting multiple unrelated articles at once dilutes the frequency counts across different topics, so sentences from one topic may crowd out another. For best results, summarize one coherent piece of writing at a time.
Manually summarizing a long article means reading the whole thing, mentally tracking which ideas recur, and then re-reading to pick out the sentences that best represent those ideas — a process that can take several minutes even for a short piece and gets tedious across many documents. This tool performs the same core logic (find repeated important words, find the sentences that contain them) instantly and consistently, without fatigue or the skimming shortcuts a tired reader might take. It won't catch nuance the way a careful human reader would, but it gives a fast, repeatable first pass that's useful before deciding whether the full text is worth your time.
The stats row shows how many words the summary kept compared to the original, expressed as a reduction percentage. A 70-80% reduction is typical when summarizing a multi-paragraph article down to 3-4 sentences. If the reduction percentage comes out low, it usually means the original text was already short relative to the number of sentences you asked the tool to keep — in that case, try lowering the sentence-count slider for a tighter summary.
People land on this page looking for ways to "summarize an article online," "shorten a paragraph automatically," "get the main points of a text," or find a "free summary generator" that doesn't require an account or an API key. This tool covers that need for straightforward extractive summarization without any sign-up, upload limit, or paid tier.