What changes
The result contains selected source sentences in their original order. It does not paraphrase, answer questions or invent bridging text.
Summarize PDF locally
Create an extractive PDF summary by ranking source sentences locally. Choose a length, review the result and download without a generative AI service.
Runs locallyNo uploadYou control saved copies
OCR runs only on pages with fewer than 20 useful native characters. Scanned text blocks on other pages can be missed. Compare the result with the original, including names and numbers.
Select important PDF sentences locally
The analysis worker scores original sentences by useful word coverage and document position, then removes repetitive choices. It never calls a generative AI service.
For a reliable result
- Choose a PDF, select a summary length and enable OCR for scanned pages.
- Let the local worker rank sentences and select a non-repetitive set.
- Compare every statement with the source before sharing or making decisions.
Check the download
Treat the summary as a navigation aid. Important exceptions, definitions or conclusions can be missed by frequency-based ranking.
Know before processing
This extractive method is strongest on English prose and is not equivalent to an LLM summary. It cannot reason about images, charts or implied meaning.
Quick answers
- Does this rewrite the PDF like an AI chatbot?
- No. It is an extractive summary: the local worker selects original sentences and keeps their source order. It does not paraphrase or create connecting claims.
- Can I rely on the summary without reading the PDF?
- No. Use it to locate likely important passages. Frequency-based ranking can miss exceptions, definitions, charts and context that changes a conclusion.
Find selected source passages for a first reading
This tool creates an extractive summary: it ranks sentences from recovered PDF text, chooses a limited set and presents them in source order. It uses local text analysis rather than a generative AI service. It does not paraphrase, answer questions or reason about the document's conclusions.
Use the result to guide a first reading, then return to the source for context. Selecting real sentences can still omit an exception, qualification or definition that changes their meaning. The ranking does not establish that the chosen passages are the author's most important points.
Choose a useful reading aid
| Your situation | Recommended approach |
|---|---|
| You want a quick entry point into ordinary prose. | Start with Short, review the selected passages and locate them in the source. Increase the length when the first selection leaves too little context, without assuming a longer result is complete. |
| The PDF is a scan or mixes scanned and digital content. | English OCR can run on pages with little readable native text. Check OCR and skipped-page notices first; the summary cannot select information that was not recovered. |
| You need all wording, section structure or interpretation. | Extract text for a fuller draft, create an outline for heading structure, or read the relevant source sections for interpretation. This summariser does not explain charts, infer meaning or resolve contradictory statements. |
Create a short selection from the research notes
The two-page research-notes.pdf contains English prose about browser privacy and checking document outputs. This example demonstrates sentence selection, not a measured test of summary accuracy.
- Choose research-notes.pdf. Set Summary length to Short · about 4 sentences.
- Clear Use local English OCR on pages with little or no native text, because this sample already contains digital text.
- Select Create local summary. Check that the result reports two input pages and zero OCR pages.
- Read each selected passage beside the source and identify the surrounding text. Select Download summary to save the .md file, or Copy result to copy the same Markdown content.
Expected result. The output should be a Markdown document headed Local summary with a short selection of extracted source passages. The selected passages remain in source order. Line breaks are normalised before sentence detection, so a heading can be joined to the sentence following it.
Check the downloaded result
- Locate each passage in the source and read the sentences immediately before and after it. Pay particular attention to negation, conditions, exceptions and what pronouns refer to.
- Compare coverage across sections. A summary can favour early or distinctive wording and still miss the main conclusion or a rarely repeated qualification.
- Check OCR-derived names and numbers against the page image. Sentence selection preserves recognition mistakes; it does not correct them.
- Read the output's limits correctly. The displayed Source words count describes recovered source text, not the length of the generated summary, and the page count does not prove that every page contributed usable sentences.
Troubleshooting
- The summary is almost as long as a short source.
When there are no more eligible sentences than the selected target, the tool includes those sentences rather than compressing or rewriting them.
Try this: Choose Short or edit the downloaded notes yourself. Use the source to decide which wording can be omitted without changing its meaning.
- A key point is missing or a heading is attached to a sentence.
The algorithm ranks recovered text and normalises line breaks. It does not understand document semantics, and headings or complex layouts can affect sentence boundaries.
Try this: Compare the source section and edit the downloaded Markdown as reading notes. Try a longer selection if helpful, but check the missing point directly rather than relying on ranking.
- The output omits scanned material or contains recognition errors.
OCR is English-only, page-limited and used only when there is too little native text. Pages with enough native text may still contain unread image-based material.
Try this: Extract and inspect the text first, or recognise relevant page images separately. Do not rely on a summary until its source text is adequate for the task.
Limits and compatibility
- Selection limits
- Short, Medium and Long aim for about 4, 8 and 14 sentences. The algorithm considers at most the first 4,000 eligible sentence segments, excludes very short or very long segments, and ranks a bounded candidate set. Long-document coverage is therefore limited.
- Local analysis
- Processing stays in the browser and creates a separate Markdown file. File, page, character and OCR limits apply. The method is tuned to English text and cannot validate claims, supply reliable source citations or substitute for reviewing the original document.
Your files and form values are processed on this device. Downloaded copies remain wherever you save them. See how to check local processing and our privacy policy for site data and optional services.
Common questions
- Is this a chat or generative AI summary?
- No. It selects passages from extracted text using local scoring and a similarity penalty. It does not generate explanations or respond to questions about the PDF.
- Can I edit the result on this page?
- The result box is read-only. Download the Markdown or copy it into your editor, make reviewed changes there, and retain the source so context remains available.
Continue your document workflow
Maintained by Shakti Prasad Ram. Found a mismatch? Report the tool, browser and steps without sending a sensitive document. Back to the tool