# Transcribe

Transcribe audio files to text with optional diarization and known-speaker hints.

- Repository: https://github.com/openai/skills (28445 stars)
- Category: Media
- License: see repository
- Last updated: 2026-10-28
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add openai/skills --skill transcribe -g -a claude-code -y`
Codex: `npx skills add openai/skills --skill transcribe -g -a codex -y`
Cursor: `npx skills add openai/skills --skill transcribe -g -a cursor -y`
Gemini CLI: `npx skills add openai/skills --skill transcribe -g -a gemini-cli -y`

## Description

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.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Audio Transcribe

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

## Workflow
1. Collect inputs: audio file path(s), desired response format (text/json/diarized_json), optional language hint, and any known speaker references.
2. Verify `OPENAI_API_KEY` is set. If missing, ask the user to set it locally (do not ask them to paste the key).
3. Run the bundled `transcribe_diarize.py` CLI with sensible defaults (fast text transcription).
4. Validate the output: transcription quality, speaker labels, and segment boundaries; iterate with a single targeted change if needed.
5. 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)

```bash
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`).

The rest: https://github.com/openai/skills/blob/HEAD/skills/.curated/transcribe/SKILL.md