ContentMédio

Whisper Transcription

porguia-matthieu·guia-matthieu· v1.0.0 · atualizado em 2026-04-11

Score

Transcribe audio and video files to text using OpenAI Whisper. Use when: converting podcasts to blog posts; creating video subtitles; extracting quotes from interviews; repurposing video content to text; building searchable audio archives

audio-transcriptionvideo-transcriptionopenai-whispercontent-repurposingsubtitle-generationaudio-processing

Linguagens

Python

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Documento do Skill

SKILL.mdwhisper-transcription/workflow

1. Receive audio/video file path.

2. Determine transcription parameters (model, format, language).

3. Load the specified Whisper model.

4. Transcribe the audio/video file using Whisper.

5. Format the output based on the selected format (txt, srt, vtt, json, tsv).

6. Save the transcript to the specified output file.

7. Return the file path of the generated transcript.

Telemetria de Agentes

Execuções

total

Taxa de Sucesso

últimos 30d

Latência Média

0.0s

p50

Alucinação

0.0%

detecção

Tokens Entrada

avg 0/exec

Tokens Saída

avg 0/exec

Uso por Plataforma

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Árvore do Skill

Whisper Transcription

whisper-transcription

Fases Cognitivas4

1.SENSE

2.CONTEXTUALIZE

3.ACT

4.REFLECT

Triggers7

transcribe an audio filegenerate subtitles from a videoconvert podcast to textextract text from audiocreate a transcript using whisperrepurpose video content to textbatch transcribe audio files

Avaliar este Skill

Score Breakdown

⭐Avaliação Humana0%

🤖Sucesso de Agentes0%

🕐Atualidade100%

🔗Saúde de Dependências100%

🕸️Centralidade no Grafo0%

🛡️Segurança50%

CompositeScore = α·Humano + β·Agente + γ·Recência + δ·Deps + ε·Centralidade + ζ·Segurança

Instalação

$ synaptic mcp download whisper-transcription

$ synaptic skills detail whisper-transcription

$ synaptic skills live whisper-transcription

Dependências

openai-whisper torch ffmpeg-python click ffmpeg

Links

GitHub Repository