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One-time setup for local Whisper transcription — installs faster-whisper and downloads a default model. Use when the user asks to set up whisper, install whisper, or prepare for local transcription.
デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。
インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
直接コマンドでは確認用 Prompt が省略されます。実行前にソースを確認してください。
npx skills add https://github.com/danielrosehill/Claude-Transcription-Plugin --skill setup-whisperコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
ローカルで確認しますか？SkillsMP が現在取得できるファイルをダウンロードできます。
Export a transcript (or any pipeline output) by emailing it, uploading to Google Drive, or copying to clipboard. Use when the user asks to send, email, upload, save to Drive, or copy a transcript.
Transcribe a podcast episode and produce two outputs in one pass — (1) the raw API transcript exactly as the provider returned it, and (2) a podcast-formatted reading version with filler words removed, section headers added, and speaker labels preserved. Use whenever the user provides a podcast audio file or says "transcribe this podcast".
Diagnose-and-treat workflow for very messy recordings where the standard preprocessor isn't enough. Generates a spectrogram, identifies problematic frequency bands (AC hum, rumble, narrow-band whines, broadband hiss, clipping), and proposes targeted ffmpeg filters. ONLY use when the user explicitly invokes it — the normal pipeline runs `preprocess-for-transcription` directly and skips diagnostic work. Trigger phrases the user might use — "this audio is messy", "transcription failed because of noise", "fix this rough recording", "the audio is bad and the transcript is garbage".
SOC 職業分類に基づく
SKILL.md を表示中
| name | setup-whisper |
| description | One-time setup for local Whisper transcription — installs faster-whisper and downloads a default model. Use when the user asks to set up whisper, install whisper, or prepare for local transcription. |
One-time install for offline transcription.
Ensure uv is available (which uv). If not, install: curl -LsSf https://astral.sh/uv/install.sh | sh.
Install faster-whisper as a tool:
uv tool install faster-whisper
(Or create a dedicated venv if the user prefers — check preference.)
Pre-download the default model (medium) so first real transcription doesn't block:
uv run --with faster-whisper python -c "from faster_whisper import WhisperModel; WhisperModel('medium')"
Write/update ~/.config/claude-transcription/config.json with:
{ "whisper_installed": true, "whisper_model": "medium", "whisper_device": "cpu" }
Confirm with a 5-second synthetic test (optional) — or just tell the user setup is complete.
Ask the user which model they want pre-downloaded:
base — 150 MB, fastestsmall — 500 MB, good for most usemedium — 1.5 GB, default balancelarge-v3 — 3 GB, highest accuracyIf the user wants ROCm acceleration, warn that CTranslate2 ROCm support is experimental and document the extra steps (install ctranslate2 built against ROCm, set whisper_device: "cuda"). Default to CPU.