ingpoc/skills

transcribe

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.

First seen Jun 15, 2026

Installation

$ npx skills add ingpoc/skills --skill transcribe

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 9
Default branch main
Open issues 0
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Declared agents codex

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 2,834 B
  • docs SUMMARY.md 234 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 2 installs

SKILL.md

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 OPENAIAPIKEY 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

  • OPENAIAPIKEY 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.