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 skills add cdeistopened/skill-stack --skill youtube-ingestgit clone --depth 1 https://github.com/cdeistopened/skill-stackWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/cdeistopened/skill-stack/youtube-ingest)<a href="https://agentmods.dev/skills/cdeistopened/skill-stack/youtube-ingest"><img src="https://agentmods.dev/badge/skills/cdeistopened/skill-stack/youtube-ingest/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/cdeistopened/skill-stack/youtube-ingest"><img src="https://agentmods.dev/badge/skills/cdeistopened/skill-stack/youtube-ingest.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00014 | $0.00295 |
| Opus 5.5 | $0.00006 | $0.00118 |
| Sonnet 5.5 | $0.00003 | $0.00059 |
| Haiku 4.5 | $0.00001 | $0.00030 |
Grade A, and why
youtube-ingest 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 1mo 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.
What it actually says
YouTube Ingest
Downloads YouTube audio via yt-dlp and produces polished markdown transcripts via Gemini Flash.
When to Use
- User wants to transcribe a YouTube video or playlist
- Building a knowledge base from YouTube content
- Extracting insights from video lectures, interviews, talks
Commands
# Transcribe a single video
bun run youtube-ingest/scripts/ingest.ts --url "https://youtube.com/watch?v=..."
# List videos in a playlist
bun run youtube-ingest/scripts/ingest.ts --playlist "https://youtube.com/playlist?list=..." --list
# Transcribe first 5 videos from playlist
bun run youtube-ingest/scripts/ingest.ts --playlist "https://youtube.com/playlist?list=..." --limit 5
Requirements
GEMINI_API_KEYenvironment variableyt-dlpinstalled (brew install yt-dlp)- Output goes to
output/youtube/by default
Output Format
Each video produces a markdown file with YAML frontmatter containing title, channel, videoId, source URL, and full transcript with sections.
Cost
~$0.005 per hour of audio (Gemini Flash).
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.
- 1mo ago First seen · 44 lines · 14 tokens per session scan A 2e200d3b0294
youtube-ingest is a skill published in the GitHub repository cdeistopened/skill-stack (30 stars, last pushed 3mo ago), licensed MIT. It adds 14 tokens to every session and 295 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-03.
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