classnotes pro

University lectures are messy. Audio is muffled, slides move too fast, and crucial exam hints get lost in the noise. Taking manual notes while trying to listen is a losing battle that leaves you with gaps and no clear revision path.

This skill automates the entire lecture-to-study-guide pipeline on macOS. It captures system audio and slides, generates local transcripts using whisper.cpp, and cross-references everything to build high-fidelity notes. Beyond simple summaries, it identifies "Exam Signals" where lecturers emphasize testable material and maintains a running Synthesis file that updates after every class. All processing happens locally on your machine to ensure privacy and offline availability.

What it does

• Local Transcription converts lecture audio to text using whisper.cpp without cloud uploads.
• Visual Capture grabs and deduplicates slides from meeting windows or browser tabs.
• Exam Signal Detection greps transcripts for specific phrases that indicate testable content.
• Automated Synthesis rebuilds a master course guide from scratch after every new lecture.
• Study Tool Generation produces Anki-ready flashcards, mock exam papers, and cheat sheets.
• Deadline Tracking extracts assignments and dates into a centralized schedule.

How it works

1. Initialize the environment by running the install script to fetch models and set up the local directory structure.
2. Capture live sessions by selecting the class window; the tool records audio and snaps slides in the background.
3. Process recordings or raw transcripts to generate cleaned, timestamped text files.
4. Verify outputs using automated gates that flag unsourced numbers, proper nouns, or missing slide references.
5. Rebuild the course synthesis to provide an up-to-date exam prep file that links concepts across the whole term.

Frameworks & tools

Built for macOS environments utilizing whisper.cpp for local inference and ffmpeg for audio handling. It uses Python scripts for data processing, BlackHole for system audio routing, and shell scripts to orchestrate the pipeline.

Why this beats prompting it yourself

Generic AI summaries often hallucinate facts or miss subtle verbal cues about exams. This skill uses a strict verification gate against local transcripts and deduplicated slide frames to ensure every claim is grounded. It also manages the state of an entire semester, linking notes into a single synthesis file that manual prompting cannot track over time.

Use cases

• Live Class Capture for remote or hybrid lectures where you need to focus on listening.
• Exam Prep for generating a comprehensive study guide from a full semester of notes.
• Catching Up by identifying missing sessions and open questions from missed classes.
• Active Recall through automated generation of Anki cards and mock exam questions.

Known limitations

Requires macOS. Live audio capture requires one-time manual setup of Multi-Output devices. Transcription speed depends on local CPU/GPU resources and lacks speaker diarization.