PDF to Anki: convert lecture slides into a deck you can check

A standard .apkg file. Download it, open Anki, choose Import, and the deck lands in your collection like any shared deck. It works in Anki desktop, AnkiMobile and AnkiDroid, and you do not need an add-on or a CSV mapping step. That is the literal request from the r/medicalschool thread asking for a tool that takes the lecture files and creates the cards.

Cards come in five shapes, picked by what the slide is doing. A definition becomes a basic question and answer. Two drugs the professor set side by side become a comparison card. A slide that is really a table becomes a table card, a pathway becomes a causal chain card that asks for the next step, and a slide that ends in a clinical consequence becomes a short vignette.

Every card has the source slide image on its back, under the answer, with a one-line note on why the point matters. That slide is what makes the deck checkable. When a card feels off mid-review, the slide it came from is right there. AnKing stays your board deck. This is the lecture layer on top of it, and how the two fit together has its own page.

Text-based slides are the most reliable input. Slides exported from PowerPoint or Keynote, course handouts and typed notes all have a text layer. If you can click and drag to highlight a sentence in your PDF viewer, you have one.

A scanned or image-only PDF still works. Pages with little or no text layer are read as images, so a photocopied handout produces a deck too. Check those cards harder against the slide on the back, because the model is reading a picture of the text.

Diagram-heavy slides are fine, and the diagram lands on the back as the slide image. What the tool does not do is image occlusion. Hiding the labels on an anatomy figure one at a time is still a job for Anki's own tool.

A .pptx or .ppt uploads as it is and is converted on the server. Speaker notes do not come across, and the PowerPoint to Anki page covers that plus Keynote and Google Slides. Pasted plain text works too and is turned into a PDF first.

One upload takes up to 100 pages and 200 MB, which covers almost any single lecture. Where it bites is the merged block PDF, the 240-page course pack, or the textbook chapter someone exported whole.

A longer PDF does not fail. It opens the built-in splitter, and you cut it into lecture-sized sections before anything is generated. Each section is its own upload, its own deck and its own credit. I cut at lecture boundaries, never at page 100. A deck that ends mid-lecture is harder to finish than two decks that each match one class.

Splitting also helps the cards. When a medical student on r/Anki asked for a workflow for 100 to 300 page PDFs, nearly every reply said the same thing: break the document into chapters or the model skips things. Smaller sections mean each slide gets read.

Fewer than you might think, on purpose. The generator stays under roughly three cards per content slide and spends them on the learning objectives first, then on anything the professor repeated or checked with an in-lecture question. Most slides do not need three.

The guardrail exists because of what big decks turn into. A UK medical student on r/medicalschooluk, replying in a thread about how to make fewer flashcards, argued that a smaller deck you will actually review each day beats a monster deck that covers everything and never gets opened. Their test for every lecture was to imagine being allowed only ten cards and ask which ones they would be. The generator asks a version of that so you do not have to.

If the count still feels high, delete before you review. If it feels low, check the objectives slide against the deck before assuming something was missed. How the number shifts between a dense pharmacology lecture and a light intro is in how many Anki cards per lecture.

A card that enters Anki today comes back on a schedule for months, and a wrong card comes back on the same schedule. So the check happens once, before the first review, and it is short. The r/Anki student set the bar about right. They did not expect AI to be perfect, and they planned to "review every card before studying". Open the PDF next to the deck and do four passes, one job each.