Paste long notes and get a shortened, extractive summary of the key sentences.
The Note Summarizer condenses a long block of pasted notes into its most important sentences using an extractive summarization method — meaning it selects and reorders existing sentences from your original text rather than generating new sentences, so every word in the summary genuinely appears in your source notes. This is useful for quickly reviewing a long reading passage, lecture transcript, or set of notes before an exam, when you need the gist without re-reading every paragraph.
To use it, paste your notes into the text box, choose how many sentences you want in the summary (short, medium, or long), and press "Summarize." The tool scores every sentence in your notes based on how many frequently occurring, meaningful words it contains — sentences packed with the words that appear most often throughout the passage (excluding common filler words like "the," "and," or "of") are treated as more central to the main ideas, and are more likely to be selected. The highest-scoring sentences are then pulled out and presented in their original order, so the summary still reads coherently as a shortened version of the passage rather than a jumbled list.
This kind of frequency-based extractive summarization works especially well on notes that are already fact-dense and repeat key terms across multiple sentences — textbook excerpts, lecture notes, and structured study guides tend to summarize well this way, since the important concepts are usually mentioned more than once. It works less well on narrative or example-heavy text, where a single crucial sentence might use unique wording that does not repeat elsewhere in the passage and therefore scores lower even though it carries an important idea.
Because of this, treat the output as a fast first-pass summary to identify the likely core sentences of a passage, not a substitute for actually reading and understanding the material. It is most useful as a triage step when you have many pages of notes and limited time: run each section through the summarizer to identify candidate key sentences, then read those sections in full where the summary suggests something important that needs more context.
All summarization happens locally using JavaScript running in your browser — no external AI service is called and no text is uploaded, so you can safely paste unpublished notes, lecture recordings you have transcribed yourself, or draft material without it leaving your device.
Running the same passage through the summarizer at different lengths (short, medium, and long) and comparing what changes between them can also help you identify which sentences are consistently treated as most central across every setting, which is often a useful signal of the passage's true core argument even beyond the summary text itself.
For lecture notes that mix genuinely important definitions with incidental examples or anecdotes the instructor used to illustrate a point, the summarizer will tend to favor the repeated technical vocabulary over the one-off examples, so if the illustrative examples matter for your exam, make sure to review those sections separately rather than relying on the summary alone to capture them.
No. It uses extractive summarization, which selects and reorders the highest-scoring existing sentences from your own text rather than generating new wording.
The scoring is based on how often key words repeat across the passage. A crucial sentence with uniquely worded ideas that don't repeat elsewhere may score lower even though it matters.
Short summaries work well for a quick refresher on a short passage; longer summaries suit dense multi-page notes where more key sentences need to be captured.
No, all processing happens locally in your browser using JavaScript. Nothing is sent to a server or any external AI service.
Yes, though for very long chapters it often works better to summarize section by section, since a single long summary may spread thin across many different sub-topics.