Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/cdeistopened/skill-stack/youtube-clip-extractornpx skills add cdeistopened/skill-stack --skill youtube-clip-extractorgit clone --depth 1 https://github.com/cdeistopened/skill-stackWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00043 | $0.04834 |
| Opus 5 | $0.00022 | $0.02417 |
| Sonnet 5 | $0.00009 | $0.00967 |
| Haiku 4.5 | $0.00004 | $0.00483 |
Grade A, and why
youtube-clip-extractor scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 626 lines — stays where its author put it; the contents beside it link to each section on GitHub.
YouTube Clip Extractor
Overview
This skill downloads YouTube videos, analyzes transcripts for compelling clip moments, extracts clips using ffmpeg, and generates platform-ready on-screen text and captions. It integrates with the existing caption and social content skills to deliver complete, publishable assets.
When to Use This Skill
- You have a YouTube URL and want to extract the best clips
- You want automated clip identification based on hook/coda criteria
- You need clips cut and ready for Descript or other editors
- You want on-screen text hooks and platform-specific captions for each clip
Do NOT use for:
- Full podcast production workflow (use
podcast-productionskill instead) - Text-only social posts (use
social-content-creationskill) - Already-downloaded videos (skip to Phase 2)
Prerequisites
Required Tools (install via Homebrew)
brew install yt-dlp ffmpeg
File Location
All downloads go to your project's transcript folder (customizable).
Structure:
transcripts/
├── {video_id}.mp4 # Full video (H.264 encoded)
├── {video_id}.en.vtt # Timestamped subtitles
└── clips/
└── {video_id}/
├── clip_01_{name}.mp4 # Individual clips
├── clip_02_{name}.mp4
└── {video_id}_Clip_Assets.md # Captions & hooks
The 4-Phase Workflow
Phase 1: Download Video & Transcript
Goal: Get video and subtitles from YouTube URL
Option A: Transcript-First (Recommended)
Download transcript first, identify clips, then download only needed segments. See Phase 1.5.
Option B: Full Download
If you need the entire video, use H.264 format for Descript compatibility (NOT AV1):
# Download video in H.264 format (Descript-compatible)
yt-dlp -f "bestvideo[vcodec^=avc]+bestaudio[ext=m4a]/best[vcodec^=avc]" \
--merge-output-format mp4 \
-o "transcripts/{video_id}.mp4" \
"YOUTUBE_URL"
# If H.264 unavailable, download best quality then re-encode:
yt-dlp -f "bestvideo+bestaudio" --merge-output-format mp4 \
-o "transcripts/{video_id}_temp.mp4" \
"YOUTUBE_URL"
# Re-encode to H.264 for Descript compatibility
ffmpeg -i "{video_id}_temp.mp4" -c:v libx264 -preset fast -crf 22 \
-c:a aac -b:a 128k "{video_id}.mp4"
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 626 lines · 43 tokens per session scan A f117e9ef6763
youtube-clip-extractor is a skill published in the GitHub repository cdeistopened/skill-stack (27 stars, last pushed 1mo ago), licensed MIT. It adds 43 tokens to every session and 4,834 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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