🗂️PDF to Flashcards
Drop a PDF into FixTools PDF to Flashcards and within seconds you get 20 study-ready cards built straight from the source text. Each card has a clear question on the front and a concise answer on the back with a page citation like (p. 14) so you can audit every claim against the original document. The output ships in two formats: a downloadable CSV laid out as. Front,Back with proper quoting so it imports cleanly into Anki or Quizlet, and a plain-text preview you can scroll, copy, or paste anywhere. Text extraction runs entirely in your browser using Mozilla pdf.js, the PDF file never leaves your device, never touches a FixTools server, and never gets retained. Only the extracted text is sent to Anthropic Claude for the card generation step.
Why PDF to flashcards beats highlighting and rereading
Spaced repetition is the most heavily studied learning technique in cognitive psychology, and the evidence is one-sided: testing yourself on material at expanding intervals dramatically outperforms rereading, highlighting, and passive review for long-term retention Anki and Quizlet are the two tools that brought spaced repetition to mainstream learners, Anki for serious vocabulary and medical study, Quizlet for K-12 and language classes. Both run on the same input: a stack of question-answer pairs. The bottleneck has never been the algorithm. It has always been authoring the cards. A pre-med student facing 400 pages of biochemistry, a 1L outlining torts, a language learner working through a literary PDF, all of them know cards work, and all of them stall at the same place, which is the hour it takes to type the first 50.
PDF to Flashcards removes that bottleneck without removing the source material from the loop. The card density is deliberate: 20 cards per run, sized to be the right batch for a single study session and the right granularity for a 10-page free-tier document. Too few cards and the coverage is shallow; too many and the cards start repeating each other or drifting away from the source. Twenty is the sweet spot that emerged from testing across textbook chapters, legal outlines, lecture handouts, and medical formularies. If you need more than 20 cards from a single PDF, split the document with FixTools PDF Splitter and run each section separately, the page citations stay accurate and the cards stay tight to the source.
The page citation on every answer is the feature that separates this from copy-pasting a PDF into ChatGPT and asking for flashcards. Without citations, you have no way to self-audit the cards, you cannot tell which ones the model invented, which ones drift slightly off the source, and which ones are exactly what the textbook said. With citations, you can spot-check the cards you are not sure about in 30 seconds: open the PDF, jump to the cited page, read the surrounding paragraph. This matters for high-stakes study material. A pre-med student memorizing a wrong mechanism for an enzyme reaction will get hammered on the MCAT. A bar prep student internalizing a hallucinated rule will get hammered on the essay. The citation is the audit trail that turns LLM-generated cards from a liability into a tool you can trust.
Privacy was an architectural decision, not a marketing claim. The text extraction step runs entirely client-side using Mozilla pdf.js, the same library Firefox uses to render PDFs natively. The PDF file is parsed in your browser tab, page by page, with page numbers preserved in the prompt that gets sent to Claude. Nothing about the PDF, not the filename, not the bytes, not the extracted text, is stored on a FixTools server. The extracted text is sent to Anthropic only at the moment you click. Run, only for the duration of the card generation, and Anthropic does not train on API inputs. For students working with copyrighted textbooks, attorneys with privileged materials, and medical professionals working with protected documents, this matters. Browser-side extraction is not a feature we added because it sounded good; it is the only architecture that makes the tool safe to use on sensitive PDFs.
How to use PDF to Flashcards
- 1
Upload the PDF
Drop the file onto the upload area or click to browse. Extraction happens locally, the file does not leave your browser. You will see the page count immediately and a notice if the document exceeds your tier limit.
- 2
Wait for text extraction
Page-by-page extraction takes one to three seconds for most documents. Page numbers are preserved alongside the extracted text so the model can cite accurately. Scanned PDFs without an OCR layer produce empty text, run FixTools OCR PDF first if your extraction is blank.
- 3
Click Run PDF to Flashcards
The extracted text is sent to Claude with explicit page markers and a system prompt that targets question-answer card pairs grounded in the document. Card generation takes ten to twenty seconds depending on length.
- 4
Review the 20 cards in the preview
Scroll the plain-text preview to scan all 20 cards. Each card shows the front (a clear question), the back (a concise answer), and the page citation in parentheses. Open the PDF and verify any card whose claim you want to double-check before adding it to your deck.
- 5
Download the CSV and import
Click. Download CSV to grab the Front,Back file with proper quote escaping. In Anki, open. File → Import, select the CSV, set the delimiter to comma, map column 1 to Front and column 2 to Back, and import. In Quizlet, create a new set, use the Import button, paste the CSV contents, and set the delimiters.
Real-world use cases
Pre-med student building biochem vocab from a textbook chapter
A pre-med student opens chapter 7 of their biochemistry textbook, 30 pages on enzyme kinetics, and runs each 10-page section through PDF to Flashcards. They get 60 cards total: enzyme names, Km values, inhibitor mechanisms, regulatory pathways. Every back has a page citation so they can verify against the textbook before adding the cards to their. MCAT Anki deck. What used to take a Saturday afternoon now takes 15 minutes plus a quick review pass.
Language student pulling vocabulary from a Spanish novel PDF
A B2-level. Spanish learner is reading. Cien. Años de. Soledad as a PDF. After each chapter they run the PDF through to extract 20 vocabulary cards, unfamiliar words on the front, definition plus the sentence from the page on the back. Page citations let them flip back to see the word in context when the flashcard alone is not enough. Their Quizlet deck grows by 20 carefully sourced words per chapter without the friction of typing.
Medical resident memorizing drug names from a hospital formulary PDF
A first-year internal medicine resident needs to know the top 200 drugs on their hospital formulary, brand name, generic name, class, common dose. They run each section of the 80-page formulary PDF through PDF to Flashcards and get 20 cards per section with page citations back to the formulary. Drug-name confusion (metoprolol vs metformin, hydralazine vs hydroxyzine) is the kind of mistake that gets caught by spaced repetition and missed by passive reading.
Bar exam prep from a commercial outline PDF
A 3L studying for the bar uses commercial outlines distributed as PDFs, Civil. Procedure, Evidence, Constitutional. Law, each 100-plus pages. The citation matters when the card asks for a four-prong test and they want to read the surrounding context before committing the rule to memory.
Pro tips
💡 Import the CSV with quoting set to comma and double-quote
Anki and Quizlet both accept CSV but the import dialog needs the right delimiter and quote settings. Set delimiter to comma and quote character to double-quote, our CSV uses RFC 4180 quoting so commas inside card text are escaped properly. If you see cards split across columns after import, the quote setting is wrong.
💡 Verify cards against the cited page before committing them to a deck
LLM-generated cards are usually correct but occasionally drift. Before you add 20 cards to a long-term Anki deck, spend two minutes spot-checking three or four cards against the cited pages. Bad cards in a spaced repetition deck are worse than no cards, you will memorize the wrong answer.
💡 Split textbook chapters into 10-page sections for the free tier
The free tier covers 10 pages, which is one section of most textbook chapters. Use FixTools PDF Splitter to break a 30-page chapter into three 10-page sections, run each separately, and combine the resulting 60 cards into one deck. Citations stay accurate because each section preserves its own page numbering.
💡 Tag the deck in Anki with the PDF filename for traceability
When you import the CSV, set a tag matching the PDF filename or chapter, biochem_ch7 or torts_outline_p1. Six months later when a card surfaces in review and you want context, the tag plus the page citation gets you back to the source PDF in two clicks.
Frequently asked questions
How do I import the CSV into Anki?
Copy or download the CSV section. In Anki desktop, open. File → Import, select the CSV file (or paste contents into a .txt and import that), set. Field separator to Comma, ensure. Fields are quoted is enabled, map column 1 to Front and column 2 to Back, pick the destination deck, and click. Import. The 20 cards land in your deck ready to study Anki ignores duplicate fronts by default, adjust import options if you want duplicates allowed.
How many cards does it generate per PDF?
Twenty cards per run. That number was chosen deliberately as the right batch size for a single study session and the right density for a 10-page free-tier document. If you need more than 20 cards from one PDF, split the document into sections using FixTools PDF Splitter and run each section separately, you can stack the resulting cards into one deck.
Is the PDF uploaded to your server?
No. Text extraction runs entirely in your browser using Mozilla pdf.js. The PDF file never leaves your device. Only the extracted text, with page markers preserved, is sent to Anthropic Claude for the card generation step. Nothing about the PDF, bytes, filename, or extracted text, is stored on a FixTools server, and Anthropic does not train on API inputs.
Does it work with scanned PDFs?
Only if the scan has an OCR text layer. Most modern scanner apps (Adobe. Scan, iOS Files, Genius. Scan) add OCR automatically. Older scans, screenshots saved as PDFs, and photographed pages have no text layer, extraction returns blank. Run the PDF through FixTools OCR PDF first to add a text layer, then come back and generate flashcards.
How is this different from pasting the PDF into ChatGPT and asking for flashcards?
Three concrete differences. First, every card back has a page citation so you can audit the source, ChatGPT page citations are unreliable and often wrong. Second, the PDF does not leave your browser during extraction, ChatGPT requires uploading the file. Third, the output is deterministic CSV with proper RFC 4180 quoting that imports cleanly into Anki and Quizlet, ChatGPT output usually breaks on commas, quotes, or special characters in card text. The two tools are not equivalent for serious study workflows.
Can I import the CSV into Quizlet?
Yes. In Quizlet, create a new study set, click. Import from Word, Excel, Google Docs, etc., paste the CSV contents into the text box, set. Between term and definition to Comma, set. Between rows to New line, and click. Import. The 20 cards appear as terms and definitions Quizlet handles RFC 4180 quoting the same way Anki does.
Will the AI invent facts that are not in the PDF?
The system prompt explicitly instructs Claude to ground every card in the source text and cite the page where the answer appears. Hallucinations are rare but possible, that is why the page citation matters. Before committing cards to a long-term deck, spot-check three or four against the cited pages. If the card matches the source, the rest of the batch is reliable; if a card drifts, regenerate or edit before importing.
Can I edit cards before importing?
Yes. The plain-text preview shows all 20 cards before you download the CSV. Copy the preview into a text editor, edit any card whose phrasing you want to tighten, and save as CSV. Or import the CSV into Anki first and edit cards inline, Anki has a strong card editor and you can adjust front, back, or tags after import.
Does it support languages other than English?
Yes. pdf.js extracts text in any language a modern PDF contains Claude generates cards in the language of the source document by default, a Spanish PDF produces. Spanish-language cards, a Japanese PDF produces. Japanese cards. For language learners who want bilingual cards (target word on the front, English definition on the back) edit the cards in the preview before downloading, or run the output through FixTools. Translate. Text.