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 spinnakergit/a0-youtube-transcribe --skill youtube-researchgit clone --depth 1 https://github.com/spinnakergit/a0-youtube-transcribeWrote 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/spinnakergit/a0-youtube-transcribe/youtube-research)<a href="https://agentmods.dev/skills/spinnakergit/a0-youtube-transcribe/youtube-research"><img src="https://agentmods.dev/badge/skills/spinnakergit/a0-youtube-transcribe/youtube-research/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/spinnakergit/a0-youtube-transcribe/youtube-research"><img src="https://agentmods.dev/badge/skills/spinnakergit/a0-youtube-transcribe/youtube-research.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 | $0.00024 | $0.00365 |
| Opus 5.5 | $0.00010 | $0.00146 |
| Sonnet 5.5 | $0.00005 | $0.00073 |
| Haiku 4.5 | $0.00002 | $0.00036 |
Grade A, and why
youtube-research 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 Research Skill
Use YouTube tools to extract knowledge from video content.
Workflow
-
Quick summary of a video:
youtube_summarywithurl: VIDEO_URL -
Detailed study notes with timestamps:
youtube_noteswithurl: VIDEO_URL,section_minutes: 5 -
Full transcript for deep analysis:
youtube_transcribewithurl: VIDEO_URL -
Research a playlist on a topic:
youtube_transcribewithurl: PLAYLIST_URL,action: playlistThenyoutube_summaryon each video of interest
Tips
- Start with
youtube_summaryfor a quick overview - Use
youtube_noteswith smallersection_minutesfor more granular notes - Visual references (charts, graphs) are automatically detected and annotated
- All content auto-saves to memory for future reference
- Chain tools: transcribe first, then summarize or generate notes from the transcript
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 · 50 lines · 24 tokens per session scan A 653abe277472
youtube-research is a skill published in the GitHub repository spinnakergit/a0-youtube-transcribe (5 stars, last pushed 6mo ago), licensed MIT. It adds 24 tokens to every session and 365 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 2026-08-31.
Other skills, from other repositories
youtube-summarizer
Extract transcripts from YouTube videos and generate comprehensive, detailed summaries using intelligent analysis frameworks.
media-fetch
Download video/audio from 1000+ sites (YouTube, Twitter/X, Spotify, TikTok, etc.), extract audio, download subtitles, transcribe speech to text, and search for videos. Use when asked to download, summarize, or transcribe any video/audio URL, or when asked to search YouTube.
youtube-summarizer
Automatically fetch YouTube video transcripts, generate structured summaries, and send full transcripts to messaging platforms. Detects YouTube URLs and provides metadata, key insights, and downloadable transcripts.
youtube-summarizer
Automatically fetch YouTube video transcripts, generate structured summaries, and send full transcripts to messaging platforms. Detects YouTube URLs and provides metadata, key insights, and downloadable transcripts.
video-lens
Fetch a YouTube transcript and generate an executive summary, key points, and timestamped topic list as a polished HTML report. Activate on YouTube URLs or requests like "summarize this video", "what's this about", "give me the highlights", "TL;DR this", "digest this video", "watch this for me", "I watched this and…
video-lens-gallery
Open or rebuild the video-lens gallery index — your personal library of saved video summaries. Use this whenever the user wants to browse, open, or search saved video reports: "show my gallery", "open video library", "browse saved videos", "build gallery", "what videos have I saved", "show my video notes", "my video…