Product
Study Flashcards Maker
For students staring at a textbook chapter, a lecture transcript, or a dense PDF the night before a test. Paste the source text plus subject area and target level (intro / advanced / med-school / bar / MCAT), and get back a clean deck of 20-40 spaced-repetition flashcards, an opinionated mix of basic recall, cloze deletions in Anki's canonical {{c1::text}} syntax, and "why does this happen" cards, every card anchored to a verbatim quote from your source so nothing is invented, plus a coverage-gap panel that flags topics the source text was too vague to card responsibly. Comes with paste-ready plaintext for Anki and TSV for Quizlet in the exact import formats each tool expects. Zero add-ons, zero API-key setup, zero copy-paste fiddle.
About this tool
What does study flashcards maker do?
For students staring at a textbook chapter, a lecture transcript, or a dense PDF the night before a test. Paste the source text plus subject area and target level (intro / advanced / med-school / bar / MCAT), and get back a clean deck of 20-40 spaced-repetition flashcards, an opinionated mix of basic recall, cloze deletions in Anki's canonical {{c1::text}} syntax, and "why does this happen" cards, every card anchored to a verbatim quote from your source so nothing is invented, plus a coverage-gap panel that flags topics the source text was too vague to card responsibly. Comes with paste-ready plaintext for Anki and TSV for Quizlet in the exact import formats each tool expects. Zero add-ons, zero API-key setup, zero copy-paste fiddle.
How do I turn a lecture PDF or textbook chapter into Anki flashcards?
Paste the source text (a chapter, a lecture transcript, or your notes, up to about 10,000 words) into the form, name the subject area (Organic Chemistry, Constitutional Law, Cardiology, and so on), pick your target level (intro undergrad, grad school, medical school, bar exam, MCAT, USMLE Step 1), tell it how many cards you want, and pick which card types to include (basic, cloze, why). One AI pass returns a 20 to 40 card deck, every card anchored to a verbatim quote from your text, plus a pre-assembled Anki import file and a Quizlet TSV you paste straight into either tool. There is no file upload step and no PDF parsing; you paste the actual study text as plain text so the tool can only card what you actually gave it.
Are AI-generated flashcards actually accurate?
Usually not, and that is exactly the failure mode this tool is built against. Freeform AI decks fabricate numbers, invent mechanism steps, and produce cards on topics the source never covered. Study Flashcards Maker enforces a hard no-invention rule: every card must include a 5 to 15 word verbatim source_span lifted from the text you pasted, and if a defensible span cannot be found the card is simply not emitted. Numbers, dates, drug doses, statutory citations, and mechanism steps cannot be upgraded or invented. The source_span appears on every card in the deck view as a small receipt line ('from source: ...') so you can spot-check any card in one second before you commit it to spaced repetition.
Which flashcard types actually work for spaced repetition?
Three, and they are not interchangeable. Basic Q/A for bare facts, definitions, named entities, units, dates, and drug doses (front is a specific question, back is the short specific answer, answerable in fewer than 10 words). Cloze deletions with Anki-canonical {{c1::text}} syntax for sentences where the surrounding context is itself a teaching signal (up to 3 deletions per card when they group naturally). Why-questions for causal mechanisms and how-something-works concepts (front is a why or how question, back is a 1 to 3 sentence mechanism explanation). The tool routes each card to the right type based on the source sentence, following Wozniak's Twenty Rules of Knowledge Formulation: atomic single-concept cards only, no yes/no, no true/false, no vague open-ended prompts, no bloated multi-fact answers.
Can I import the deck straight into Anki or Quizlet?
Yes, both, no fiddling. The deck view has two Copy buttons at the top. Copy Anki export gives you a pre-assembled tab-delimited file with a 3-line commented import header, one card per line, tabs and newlines inside content escaped correctly, and Anki-canonical {{c1::text}} cloze syntax preserved verbatim. In Anki you import once with Type = Basic for the basic and why cards, and once with Type = Cloze for the cloze cards; both passes use tab separator with Allow HTML enabled. Copy Quizlet export gives you the raw TSV Quizlet accepts (term tab definition, one card per line, no header). Paste, import, done. There is no CSV cleaning step, no manual column re-mapping, and no post-processing.
What if my source text does not cover a topic well enough to build a card on?
The tool refuses to invent, and on the Deep tier it tells you exactly which topics it refused on. The coverage_notes panel returns up to 4 entries, each naming a topic the source discusses but treats too vaguely to card defensibly, plus one line explaining why. Example: topic 'detailed enzyme kinetics of isocitrate dehydrogenase', reason 'Source names Km and Vmax but never gives the actual values or the substrate-activation curve, cards would need invented numbers.' That way you finish the run knowing exactly what to go read next, instead of ending up with a memorized card that is quietly wrong. Quick tier skips this analysis to keep the token cost down.
How is this different from just asking ChatGPT to make me flashcards?
A freeform ChatGPT prompt invents numbers, hallucinates cards on topics your source never covered, defaults to bloated multi-fact answers, produces yes/no cards the Twenty Rules explicitly warn against, and hands you unformatted prose you then have to reformat by hand before Anki or Quizlet will accept it. Study Flashcards Maker runs one structured pass with four hard rules: every card carries a verbatim source_span receipt (no invention), each card is routed deliberately by source-sentence type (basic vs cloze vs why), Twenty-Rules discipline is enforced on every card (atomic single-concept, no yes/no, no vague open-ended, no bloated answers), and the Anki import file and Quizlet TSV are pre-assembled with correct escaping so you paste and import instead of reformatting.
Which tier should I pick, Quick or Deep?
Pick Quick (15 tokens) for a lecture recap, a chapter you already broadly know, or a low-stakes quiz where you just want about 20 opinionated cards fast. Quick skips the coverage-gap analysis and runs the lighter model, but you still get the source_span receipts, the basic vs cloze vs why routing, and the pre-assembled Anki and Quizlet exports. Pick Deep (50 tokens) for anything you will actually memorize for weeks (medical school, bar exam, MCAT, USMLE Step 1, hard undergrad finals): 30 to 40 cards, difficulty precisely calibrated to your target level, richer why-question explanations, 1 to 3 topical tags per card so you can filter by subtopic inside Anki, and the full coverage-gap panel that names exactly which topics the source did not explain well enough to card responsibly.
How much does it cost per deck, and do I need a subscription?
No subscription. Quick is 15 tokens per deck, Deep is 50 tokens. Tokens are a prepaid platform credit you buy once and spend across any produde tool, so you pay per deck instead of a monthly study-app fee. If a run fails, the full token cost is refunded to your wallet automatically. Most students building a deck per chapter through a term will spend far less on tokens than they would on a single month of a study-app subscription.
What does it cost?
From 15 tokens. Pick a tier on the form above. Produde tokens are a prepaid platform credit; buy them once and spend on any tool.
Do I pay if a run doesn't complete?
No. You only pay for results. If a run can't finish, its full token cost stays in your wallet automatically.
Is my data stored?
Your input and the run output are saved to your account so you can browse history. They are not sold, shared with advertisers, or used to train shared models. See privacy for details.