Transcribe Skill for Codex

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 recordings, or label speakers in interviews or meetings.

708 tokens

context cost

SKILL.md, read when the skill is used

files

ships runnable scripts

copies elsewhere

how many repositories repackaged it

24 488

stars on the repo

on the repository, not the skill itself

Install

one command, takes just this skill from the repository

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

What comes with it

22 369 bytes besides the instruction

LICENSE.txt

agents/openai.yaml

assets/transcribe-small.svg

assets/transcribe.png

references/api.md

scripts/transcribe_diarize.py

The instruction itself

9 sections, as written by the author

Audio Transcribe

Transcribe audio using OpenAI, with optional speaker diarization when requested. Prefer the bundled CLI for deterministic, repeatable runs.

Workflow

Collect inputs: audio file path(s), desired response format (text/json/diarized_json), optional language hint, and any known speaker references.
Verify OPENAI_API_KEY is set. If missing, ask the user to set it locally (do not ask them to paste the key).
Run the bundled transcribe_diarize.py CLI with sensible defaults (fast text transcription).
Validate the output: transcription quality, speaker labels, and segment boundaries; iterate with a single targeted change if needed.
Save outputs under output/transcribe/ when working in this repo.

Decision rules

Default to gpt-4o-mini-transcribe with --response-format text for fast transcription.
If the user wants speaker labels or diarization, use --model gpt-4o-transcribe-diarize --response-format diarized_json.
If audio is longer than ~30 seconds, keep --chunking-strategy auto.
Prompting is not supported for gpt-4o-transcribe-diarize.

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.

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How to use it

Copy the folder

Take openai/transcribe from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.

Install what it needs

The instructions reference pip, uv. Without those the skill loads but fails at the first command.