القائمة
Use when the user asks to extract captions, subtitles, or transcribe audio/speech from a video file. Triggers on "extract captions", "transcribe video", "get subtitles", "transcrever vídeo", "legendas do vídeo", or when a video file path is provided alongside a transcription request.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Read HANDOFF.md and continue from where we left off
Use when ending a session, completing a milestone, or stopping mid-task and context must be preserved for the next agent
Use when organizing raw content into slide-ready format, or when the user says "prepare slides", "structure this for a presentation", "brief for pptx".
Use when the user shares a URL or article and asks to extract key learnings, summarize topics, or generate a digest formatted for Google Chat, Slack, Discord, Telegram, or similar messaging tools. Accepts an optional format parameter.
Use when working with Kubernetes clusters, manifests, and related tasks.
Use when writing a CV, bio, LinkedIn post, or talk abstract for Silvio; when calibrating technical recommendations to Silvio's experience ("do I have experience with X?"); or when an introduction or speaker section is needed. Loads timeline, stack, credentials, and preferences on demand via the pointer table.
| name | video-captions |
| description | Use when the user asks to extract captions, subtitles, or transcribe audio/speech from a video file. Triggers on "extract captions", "transcribe video", "get subtitles", "transcrever vídeo", "legendas do vídeo", or when a video file path is provided alongside a transcription request. |
| disable-model-invocation | true |
Extract captions or subtitles from video files using video-captions (Whisper-based CLI).
| Option | Default | Description |
|---|---|---|
--language LANG | en | Source language code (en, pt, es, fr, …) |
--model MODEL | base | Model size: tiny, base, small, medium, large |
--format FORMAT | text | Output: text, srt, vtt, json |
--output FILE | stdout | Save to file instead of printing |
# Plain text to stdout
video-captions video.mp4
# Portuguese audio, small model
video-captions --language pt --model small video.mp4
# SRT file output
video-captions --format srt --output captions.srt video.mp4
# WebVTT with better accuracy
video-captions --model medium --format vtt talk.mkv
tiny / base — fast, good for short clips or clear speechsmall / medium — better accuracy, slower (recommended for accented speech)large — highest accuracy, requires more RAM (~10 GB)The base model is sufficient for most clear English audio. Use small or medium when:
Requires openai-whisper for Python 3.12:
pip install openai-whisper --break-system-packages