Menu
Fetch transcripts from YouTube videos using yt-dlp. Supports any language with auto-generated or manual captions. Use for summarization, analysis, or translation tasks.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
Analyze pi session transcripts to discover patterns that could become AGENTS.md rules, skills, or prompt templates. Mines your usage history for automation opportunities.
Build PR-focused context packs (PR description + git diff + full changed files + related files via Scribe), then budget-fit and token-check with o200k-base.
Review a pull request for bugs, style issues, and guideline compliance. Local review - does not post to GitHub.
Build LLM-ready code dumps with optional docs, then count tokens with tokencount (o200k-base) against a context budget (for example 272k for GPT-5).
Compress images to a target file size using macOS sips. No dependencies required.
Multi-model code review. Runs code-review skill with 3 models in parallel, then synthesizes findings.
| name | youtube-transcript |
| description | Fetch transcripts from YouTube videos using yt-dlp. Supports any language with auto-generated or manual captions. Use for summarization, analysis, or translation tasks. |
Fetch transcripts from YouTube videos using yt-dlp.
brew install yt-dlp jq
{baseDir}/transcript.sh <video-url-or-id> [language]
# English (default)
{baseDir}/transcript.sh "https://youtu.be/dQw4w9WgXcQ"
# Polish
{baseDir}/transcript.sh "https://youtu.be/ksWAT3uqlWA" pl
# German
{baseDir}/transcript.sh "https://www.youtube.com/watch?v=VIDEO_ID" de
# Just video ID works too
{baseDir}/transcript.sh dQw4w9WgXcQ
Timestamped transcript:
[0:00] [Music]
[0:18] We're no strangers to
[0:21] love. You know the rules...
[1:23] Never gonna give you up
Any language code: en, pl, de, es, ja, pt, fr, it, etc.
Use yt-dlp --list-subs <url> to see available languages for a video.