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OpenAI Whisper

Transcribe audio files (≤25 MB) to text via OpenAI-compatible Whisper API.

Skill by lordmacu

IndexedApache-2.0★ 8
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/lordmacu-openai-whisper

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About

Transcribe audio files (≤25 MB) to text via OpenAI-compatible Whisper API.

Use cases: backend

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/openai-whisper

What's inside

Skill name
OpenAI Whisper
Description
Transcribe audio files (≤25 MB) to text via OpenAI-compatible Whisper API.
License
Apache-2.0
Instructions
47 lines in SKILL.md · view on GitHub

Agent Skills spec issues

  • name: only lowercase letters, digits and single hyphens allowed
  • name: "OpenAI Whisper" does not match folder "openai-whisper"

Files (1)

  • SKILL.md

SKILL.md (first lines)

# OpenAI Whisper

Use this skill to transcribe audio files into text. Backed by the
`openai-whisper` extension which calls any OpenAI-compatible
`/audio/transcriptions` endpoint (OpenAI, Groq, local whisper.cpp).

## Use when

- "Transcribe this audio"
- "Convert this voice note to text"
- "Get subtitles from this recording"
- User attaches `.mp3`, `.wav`, `.m4a`, `.webm`, `.ogg` and wants the text

## Do not use when

- Text-to-speech (TTS) — different skill / extension
- Real-time streaming transcription — this is batch only
- Speaker diarization with strict attribution — Whisper does not separate speakers reliably
- Audio > 25 MB — split or compress (downsample to 16 kHz mono) before calling

## Tools

### `status`
No arguments. Returns endpoint, default model, token presence, max file size.

### `transcribe_file`
- `file_path` (string, required) — absolute or relative path, ≤ 25 MB
- `model` (string, optional) — override default (`whisper-1`, `whisper-large-v3`, etc.)
- `language` (string, optional) — ISO 639-1 hint (`en`, `es`, `pt`); improves accuracy
- `prompt` (string, optional) — biases vocabulary/style; useful for technical terms or names
- `response_format` (string, optional) — `text` (default) | `json` | `verbose_json` (with segments+timestamps) | `srt` | `vtt`
- `temperature` (number, optional, 0..1) — 0 for deterministic

Returns `{file_path, bytes, model, language, response_format, transcript: {text, ...}}`.

## Execution guidance

- Default `response_format: "text"` for plain transcripts.
- Use `verbose_json` when the user needs timestamps or segment data (subtitles, alignment, search).
- Use `srt` / `vtt` when the user explicitly wants subtitle files.
- Always pass `language` if the audio language is known — accuracy improves significantly.
- Use `prompt` to feed proper nouns, jargon, or expected style ("Bible reading", "casual Spanish", "medical interview").
- If `-32014` (payload too large) → ask user to compress audio (`ffmpeg -i in.mp3 -ac 1 -ar 16000 out.mp3`).
- If `-32015` (unsupported media) → file format unsupported by provider; convert to `mp3`/`wav`.
- If `-32011` (unauthorized) → `WHISPER_OPENAI_API_KEY` missing or invalid.

From lordmacu/nexo-rs, Apache-2.0.

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Forks
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Open issues
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Last commit (this folder)
Apr 24, 2026 (6 months ago)
Last release
May 11, 2026 (5 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
Apache-2.0
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

More from lordmacu

Cite this page

OpenAI Whisper skill. Agent Mart. https://agentmart.dev/skills/lordmacu-openai-whisper (last updated 2026-10-24)