transcribe

Name: transcribe
Author: openai

Transcribe audio files to text with optional diarization and known-speaker hints. Use when a user asks to transcribe speech from audio/video, extract text from…

INSTALLATION

npx skills add https://github.com/openai/skills --skill transcribe

Run in your project or agent environment. Adjust flags if your CLI version differs.

SKILL.md

$27

Output conventions

Use output/transcribe/<job-id>/ for evaluation runs.

Use --out-dir for multiple files to avoid overwriting.

Dependencies (install if missing)

Prefer uv for dependency management.

uv pip install openai

If uv is unavailable:

python3 -m pip install openai

Environment

OPENAI_API_KEY must be set for live API calls.

If the key is missing, instruct the user to create one in the OpenAI platform UI and export it in their shell.

Never ask the user to paste the full key in chat.

Skill path (set once)

export CODEX_HOME="${CODEX_HOME:-$HOME/.codex}"

export TRANSCRIBE_CLI="$CODEX_HOME/skills/transcribe/scripts/transcribe_diarize.py"

User-scoped skills install under $CODEX_HOME/skills (default: ~/.codex/skills).

CLI quick start

Single file (fast text default):

python3 "$TRANSCRIBE_CLI" \

  path/to/audio.wav \

  --out transcript.txt

Diarization with known speakers (up to 4):

python3 "$TRANSCRIBE_CLI" \

  meeting.m4a \

  --model gpt-4o-transcribe-diarize \

  --known-speaker "Alice=refs/alice.wav" \

  --known-speaker "Bob=refs/bob.wav" \

  --response-format diarized_json \

  --out-dir output/transcribe/meeting

Plain text output (explicit):

python3 "$TRANSCRIBE_CLI" \

  interview.mp3 \

  --response-format text \

  --out interview.txt

Reference map

references/api.md: supported formats, limits, response formats, and known-speaker notes.