Cleaning lecture notes with AI almost always introduces a quiet bug: the model fills the gaps with plausible-sounding facts the lecturer never said, and three weeks later you’ve memorized something the exam won’t reward. These prompts force the model to rebuild structure, flag gaps explicitly with [GAP: ...], mark every suggestion as “likely” or “needs verification”, and tie self-test questions back to the source line. Pair with the flashcard prompts to convert the cleaned notes into spaced-repetition cards.
Best for
- Post-lecture cleanup
- Exam revision
- Building course notes from scratch
- Teaching prep
- Sharing notes with peers
1. Structure rebuilder
Below are my raw lecture notes from {course / topic}. Rebuild the structure with headings, sub-headings, and bullet lists. Do not add facts I did not write; flag gaps with [GAP: {what is missing}].
{paste notes}2. Gap-filling pass
Below are my structured lecture notes with [GAP: x] markers. Suggest what should fill each gap based on the surrounding context. Mark each suggestion as "likely" or "needs verification".
{paste}3. Example generator per section
For each section in these notes, add 1 worked example. Use the formula/concept exactly as stated in the notes. Mark which examples are direct from the notes vs my additions.
{paste}4. Self-test question generator
Generate 3 self-test questions per section of these notes: (a) recall, (b) understanding, (c) application. Format: question, answer, the source line in the notes.
{paste}5. Glossary builder
Build a glossary of all technical terms in these notes. For each: 1-sentence definition, the section it first appears in, 1 example of correct usage.
{paste}6. “Confusing line” decoder
In my notes, the following lines are confusing or shorthand. Help me expand each into a clear sentence. Flag any expansion that is not directly justified by the surrounding text.
{paste confusing lines}7. Cross-topic linker
Below are notes from 3 lectures: {lecture A / B / C}. Identify the 5 cross-topic connections that the lectures imply but did not state. Add a "connections" section linking them.
{paste}8. Highlight extractor
From these notes, extract the 10 most important points (formulas, definitions, claims). Format: priority (must-know / should-know / nice-to-know), 1-line statement, the page reference.
{paste}9. Audio-to-notes cleanup
Below is a raw transcript from a lecture recording. Clean it into structured notes: remove filler words, fix grammar, organize by topic, and flag anything the lecturer said as "important" or "on the exam".
{paste transcript}10. Diagram-from-notes prompt
Below is a section of notes describing a process / system. Describe a diagram that captures it. Output: nodes, edges, labels, and the 1 question the diagram should help answer.
{paste section}11. Personal-study summary
Convert these notes into a 1-page personal study summary. Focus on what I struggle with most: {topics}. Use my own vocabulary from the notes. Add 5 self-test questions tied to my weak areas.
{paste}Common mistakes
- Adding facts the lecturer never said — exam ranks the lecturer’s framing, not the model’s
- Removing surrounding context that you’ll need to understand a line later in the term
- No “needs verification” flag, so confident hallucinations sit next to real notes
- Skipping the self-test generation step that turns notes into revision material
- One giant block of text with no headings, so spaced review is impossible
- Cleaning the audio transcript without keeping the lecturer’s “this will be on the exam” callouts
Related
- Theory simplification prompts
- Concept comparison prompts
- Quiz generation prompts
- Flashcard prompts
- Study plan prompts
- Generate Follow-Up Questions for a Lecture With AI
- Clean Up Lecture Notes With AI: From Messy Scratch to Revision-Ready
- How to Use AI to Clean Up Lecture Notes: From Raw Capture to a Reviewable Outline