Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Use VLM Run (vlmrun) to generate transcriptions from YouTube videos. Download a video with yt-dlp, then run vlmrun to transcribe with optional timestamps. VLMRUN_API_KEY must be in .env; follow vlmrun-cli-skill for CLI setup and options.
Use VLM Run (vlmrun) to generate transcriptions from YouTube videos. Download a video with yt-dlp, then run vlmrun to transcribe with optional timestamps. VLMRUN_API_KEY must be in .env; follow vlmrun-cli-skill for CLI setup and options.
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Generate transcriptions from YouTube videos using vlmrun for speech-to-text and optional timestamps. This skill: Downloads the YouTube video (or audio) with yt-dlp. Transcribes the video with vlmrun (Orion visual AI). Saves the transcript to a file (plain text or with timestamps). Refer to vlmrun-cli-skill for vlmrun CLI setup, environment variables, and all vlmrun chat options.
Check .env for API key Ensure .env (or .env.local) contains VLMRUN_API_KEY. If missing, instruct the user to set it before running any vlmrun commands. Use vlmrun for transcription only For transcription (and optional timestamps), use the vlmrun CLI with a video file as input (-i <video>). vlmrun accepts video files (e.g. .mp4). For YouTube, the skill first downloads the video with yt-dlp, then passes the file to vlmrun. Workflow User provides a YouTube URL (and optionally output path). Download the video (or audio-only for faster/smaller) with yt-dlp. Run: vlmrun chat "Transcribe this video with timestamps for each section. Output the full transcript in a clear, readable format." -i <downloaded_file> -o <output_dir>. Capture vlmrunโs response and save it as the transcript file (e.g. transcript.txt).
Python 3.10+ VLMRUN_API_KEY (required for vlmrun) vlmrun CLI (vlmrun[cli]) yt-dlp (for downloading YouTube videos) See vlmrun-cli-skill for detailed vlmrun usage and examples (including video transcription).
From the youtube-transcription-generator directory: Windows (PowerShell): cd path\to\youtube-transcription-generator uv venv .venv\Scripts\Activate.ps1 uv pip install -r requirements.txt macOS/Linux: cd path/to/youtube-transcription-generator uv venv source .venv/bin/activate uv pip install -r requirements.txt Copy .env_template to .env and set VLMRUN_API_KEY.
# From youtube-transcription-generator directory, with venv activated python scripts/run_transcription.py "https://www.youtube.com/watch?v=VIDEO_ID" -o ./output This will: Download the video with yt-dlp into the output directory. Run vlmrun to transcribe the video. Save the transcript as output/transcript.txt (and keep artifacts in output/).
# 1) Download with yt-dlp yt-dlp -f "bv*[ext=mp4]+ba/best[ext=mp4]/best" -o video.mp4 "https://www.youtube.com/watch?v=VIDEO_ID" # 2) Transcribe with vlmrun (see vlmrun-cli-skill for options) vlmrun chat "Transcribe this video with timestamps for each section. Output the full transcript in a clear, readable format." -i video.mp4 -o ./output Capture the vlmrun stdout and save it as your transcript, or use --json if you need structured output.
With timestamps: "Transcribe this video with timestamps for each section. Output the full transcript in a clear, readable format." Plain transcript only: "Transcribe everything said in this video. Output only the spoken text, no timestamps." Structured (e.g. JSON): Use --json and ask for a structured format in the prompt (e.g. list of { "time": "...", "text": "..." }).
Confirm vlmrun is installed and VLMRUN_API_KEY is set (see vlmrun-cli-skill). Install dependencies: uv pip install -r requirements.txt (includes vlmrun[cli] and yt-dlp). Run python scripts/run_transcription.py <youtube_url> -o ./output or download + vlmrun manually. Find transcript in the output directory (e.g. output/transcript.txt).
vlmrun not found Activate the venv and run: uv pip install "vlmrun[cli]". See vlmrun-cli-skill. Authentication errors Verify VLMRUN_API_KEY in .env or the current shell. yt-dlp fails Update yt-dlp: uv pip install -U yt-dlp. Check the URL is a valid public YouTube video. Large or long videos Use audio-only download in the script (e.g. -f bestaudio) to reduce size and speed up transcription.
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