Transcribe

Convert a local audio recording into a structured meeting note. Single-pass: Whisper API for the transcript, then synthesize the note inline using the notes skill's schema. This skill does not require any particular recording tool - bring your own recording (any tool that produces an mp3/m4a/wav file works). On Windows, scripts/record-call.ps1 is included as an optional mic-only call recorder that pairs with it (see Recording with record-call below).

Requirements

• An OpenAI API key with Whisper access, available as the environment variable OPENAI_API_KEY. How you load that variable into your shell (a .env file, your OS's secret manager, etc.) is up to you - this skill just expects it to already be set when Claude Code starts, or readable from a file you point it at.
• curl and jq (or PowerShell's JSON parsing) for calling the API and reading the response.
• ffmpeg on PATH if you ever need to chunk a large file (see step 3), or if you use record-call (see below).
• The notes skill installed alongside this one - transcribe writes into ~/work/notes/ using its filename and frontmatter format.

Recording with record-call (optional, Windows only)

scripts/record-call.ps1 starts and stops a mic-only ffmpeg recording in the background and drops finished files straight into the recordings folder this skill reads from. There is no time limit: a recording you forget to stop keeps going until you run record-call stop or the disk fills, so check record-call status if you're not sure. It does not capture system/call audio, only your microphone - so it captures your side of a call, not the other person's, unless your setup routes both into one input device.

record-call start "team sync"   # -> ~/work/recordings/2026-05-21_140530_team-sync.mp3
record-call stop
record-call status
record-call list
record-call devices             # list audio input devices ffmpeg can see

Install: copy record-call.ps1, record-call.cmd, and _record-guard.ps1 (from this skill's scripts/ folder) to a folder on your PATH, keeping all three together - record-call.cmd is a thin wrapper so you can type record-call instead of the full PowerShell invocation, and _record-guard.ps1 is a background helper record-call.ps1 spawns, not something you run directly.

Env overrides:

• RECORD_CALL_DIR - recordings folder (default ~/work/recordings, matching this skill's default).
• RECORD_CALL_FFMPEG - path to ffmpeg.exe if it's not on PATH.
• RECORD_CALL_MIC - a substring to match your preferred input device name (run record-call devices to see what's available). Without it, record-call just uses the first device it finds - set this if you have more than one microphone.

Inputs

• Audio file path (optional). If absent, default to the newest .mp3 / .m4a / .wav in ~/work/recordings/.
• Meeting context (optional). User may pass a meeting name, title, or "for the Tuesday call". If absent, infer from the recording filename slug; if still unclear, ask.

Hard rules

• Never auto-save before showing the proposed filename + frontmatter + summary preview and getting a "go". Same discipline as the notes skill.
• Always use the notes schema for the output file (frontmatter + filename format defined below). Don't invent a new layout.
• Always confirm the meeting if today's calendar has multiple events that could match - present a numbered list and ask. (This step needs a calendar tool wired up; skip it if you don't have one.)
• Preserve the raw transcript. Write it to ~/work/recordings/transcripts/<recording-stem>.txt alongside the structured note. Useful later, cheap to keep.
• Don't chunk silently. If the file is >24 MB, tell the user, then split with ffmpeg into ≤20-minute chunks before uploading.

Procedure

1. Resolve the audio file

• If user passed a path → use it. Confirm it exists.
• Else: Glob ~/work/recordings/*.{mp3,m4a,wav}, sort by mtime, pick newest. Tell the user which file you picked: "Transcribing the latest: 2026-05-21_140530_team-sync.mp3 (12 min, 4.3 MB). Different file?"

2. Pick / confirm the meeting

Parse the filename slug for hints (team-sync, 1on1-with-sam, etc.) and, if you have a calendar tool wired up, check today's calendar for matching events.

Present matches:

Today's meetings near this recording:
1. 2:00 PM - Team sync (Taylor, Jordan)
2. 4:30 PM - Standup (Morgan, Casey)

Which meeting was this? (or 'none' to fill manually)

On a number: prefill title, people, suggested tags from attendee firstnames. On "none": ask the user for title + attendees.

3. Check file size and chunk if needed

size=$(stat -c%s "$file" 2>/dev/null || powershell -c "(Get-Item '$file').Length")

• ≤ 24 MB: upload as-is.

• 24 MB: tell the user the file is too large for a single upload, then chunk with ffmpeg into 20-minute segments at the same encoding:

  ffmpeg -i "$file" -f segment -segment_time 1200 -c copy "$dir/chunk_%03d.mp3"

  Upload each chunk separately, concatenate transcripts in order with a [chunk N] marker between them.

4. Call Whisper

Read the API key from the OPENAI_API_KEY environment variable (or wherever your setup stores it):

key="$OPENAI_API_KEY"

Upload:

curl -s https://api.openai.com/v1/audio/transcriptions \
  -H "Authorization: Bearer $key" \
  -F file=@"$file" \
  -F model=whisper-1 \
  -F response_format=verbose_json \
  -F language=en

verbose_json gives us segments + timestamps. Parse with jq or PowerShell.

If the response is Thanks for watching! / Japanese / something obviously empty: warn the user the recording was likely silent (mic muted, wrong device, no audio).

5. Save the raw transcript

Write the full transcript text to:

~/work/recordings/transcripts/<recording-stem>.txt

With a small header (file, duration, model). Cheap insurance - never re-pay Whisper for the same file.

6. Synthesize the meeting note

Read the transcript inline (use the conversation, not a tool). Produce a structured summary in this shape:

## Summary
1-3 sentence high-level. What was this call actually about?

## Key decisions
- ...

## Action items
- [ ] @who - what - by when (if mentioned)

## Open questions
- ...

## Raw transcript
See `~/work/recordings/transcripts/<stem>.txt`.

Tone: terse, bullet-heavy, no editorializing. If a section has nothing, omit it (don't write "N/A").

7. Confirm and write

Show the proposed:

• Filename (matching notes schema: YYYY-MM-DD_meeting_<slug>.md)
• Full frontmatter block
• The summary body

In one block, then ask: "Save to ~/work/notes/2026-05-21_meeting_team-sync.md? (y / edit / cancel)"

On "y": Write the file. Confirm path back to user. On "edit": ask what to change, redo from step 6. On "cancel": don't write. The raw transcript at step 5 is still saved.

Frontmatter

Match notes exactly:

---
type: meeting
date: 2026-05-21
title: Team sync
tags: [#acme-corp, #taylor, #jordan]
people: [taylor, jordan]
source: recording:<absolute-path-to-mp3>
---

source: carries the recording path so the user can later trace back to the audio. The transcript file is also implied by the recording stem.

When to ASK vs DECIDE

• Ask: which meeting (if multiple plausible matches today), missing attendees, ambiguous title.
• Decide: file picked from latest default, summary structure, tag suggestions from attendee firstnames (then confirm at step 7).

What this skill does NOT do

• No system/call-audio capture - record-call is mic-only, so it gets your side of a call, not the other person's. Bring your own mp3/m4a/wav from another tool if you need both sides.
• No speaker diarization - a single-track recording only captures one side clearly unless your recording setup captures both.
• No automatic Slack/email forwarding of summaries - output is the meeting note file, full stop.
• No real-time transcription - strictly post-call.
• No re-transcription of the same file unless explicitly asked (the raw .txt from step 5 is the cache).