How do I install the Transcribe skill?

Run npx skillmds@latest add lidge-jun/transcribe in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Transcribe safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Transcribe?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Transcribe free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Transcribe?

lidge-jun (@lidge-jun) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Transcribe by lidge-jun — Agent Skill

Name: Transcribe
Author: lidge-jun

File contents

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

uv pip install openai        # preferred
python3 -m pip install openai # fallback

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.

---name: transcribedescription: 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.---# Audio TranscribeTranscribe audio using OpenAI, with optional speaker diarization when requested. Prefer the bundled CLI for deterministic, repeatable runs.## Workflow1. 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```bashuv pip install openai # preferredpython3 -m pip install openai # fallback```## Skill path (set once)```bashexport 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 startSingle 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.

Frequently asked questions

Transcribe