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LLM & Anki — Exam Preparation Workflow

This guide shows how to turn lecture notes or PDFs into high-quality Anki flashcards with the help of an LLM.
The goal is to reduce time-to-first-deck and increase retention — without over-engineering the process.

1. Inputs and Outputs​

  • Inputs: course slides, past exams, personal notes
  • Output: .csv file for Anki in the format Front;Back;Tags

We focus on these card types:

  • Definition: “What is X?” → one-sentence answer
  • Concept check: “Why/When use X?” → 2–3 bullet points
  • Process: short numbered steps (max 5)
  • Pitfalls/common mistakes: 2–3 bullet points

Tip: split long answers into multiple cards instead of making “monster cards.”

2. Deterministic Prompt​

Use this prompt with ChatGPT or another LLM (temperature 0 for consistency):

You are an teaching assistant. Create Anki cards from the provided text. Rules:

  1. Output CSV lines in the format: Front;Back;Tags
  2. Keep answers concise (1–3 sentences or bullets).
  3. Prefer definitions, concept checks, processes, pitfalls.
  4. No empty lines. One card per line.

💡 Pro Tip:
Beyond flashcards, you can leverage the LLM’s few-shot learning capabilities to create test exams.
For example, by providing a handful of Anki cards as examples (“few shots”), you can ask the LLM to generate a mock multiple-choice exam, short-answer questions, or even scenario-based problems.
This works best if you can also provide old exams or official practice questions, the more high-quality material you feed in, the better and more realistic the generated flashcards and practice exams will become.

3. Example Output​

What is a hash function?;A function mapping input to fixed-size output, designed to be deterministic and collision-resistant.;crypto;definition When to use HMAC instead of plain hash?;When integrity and authenticity are required with a shared secret.;crypto;concept TLS handshake (high-level steps);ClientHello → ServerHello → Certificate/Key exchange → Finished.;network;process