Transcribe Summarize
Description
Claude Code / Codex skill for local-first meeting transcription. Runs Whisper on your own machine across macOS, Windows and Linux, filters the segments Whisper invents over silence, and writes the result up as factual meeting notes and a PDF. Hosted APIs are opt-in and disclose what they will send and cost before sending it.
Installation
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open the source below and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
README
transcribe-summarize
**This repository is generated.** `transcribe-summarize` is developed in [kevin-burns/claude-skills](https://github.com/kevin-burns/claude-skills) and mirrored here on every merge, so that anyone with recorded meetings who would rather not upload them can find and install it on its own. **Please raise issues and pull requests [in the source repository](https://github.com/kevin-burns/claude-skills/issues)** — changes made here would be overwritten by the next build.
Transcribe audio on your own machine, on macOS, Windows or Linux. Optionally turn the result into meeting notes and a PDF.
Nothing leaves your computer unless you name a network backend in the command, and when you do, the tool tells you what it is about to send and what it will cost before it sends it.
What it does
| in | what happens | out |
|---|---|---|
audio — .mp3, .m4a, .wav, .flac, .opus |
normalise, trim silence, decode, filter inventions | transcript .md + .srt + .json |
video — .mp4, .mov, .mkv, .webm |
ffmpeg takes the audio track; the video is ignored | same as above |
an existing transcript — .vtt, .srt from Teams or Zoom |
cues rejoined, timecodes dropped, speakers attributed | readable .md, no transcription at all |
| any of the above | you review, then Claude writes it up | meeting notes .md + .pdf |
A Teams or Zoom download is an `.mp4` and works as-is — you do not extract the audio first. And if the platform already transcribed the meeting, skip the audio entirely: `normalise_transcript.py` turns the `.vtt` into prose and the notes step is identical.
# transcribing needs a backend, and the backend comes from --with
uv run --with 'mlx-whisper>=0.4.2' --script scripts/transcribe.py meeting.mp4
# everything else is Related Skills
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