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 matteotitta/genesys-skills --skill watch-videogit clone --depth 1 https://github.com/matteotitta/genesys-skillsWrote 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/matteotitta/genesys-skills/watch-video)<a href="https://agentmods.dev/skills/matteotitta/genesys-skills/watch-video"><img src="https://agentmods.dev/badge/skills/matteotitta/genesys-skills/watch-video/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/matteotitta/genesys-skills/watch-video"><img src="https://agentmods.dev/badge/skills/matteotitta/genesys-skills/watch-video.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 | $0.00180 | $0.01771 |
| Opus 5 | $0.00090 | $0.00886 |
| Sonnet 5 | $0.00036 | $0.00354 |
| Haiku 4.5 | $0.00018 | $0.00177 |
Grade A, and why
watch-video 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 9d 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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Watch video — transcribe and analyze any video, at the depth you choose
The general, any-source video tool. Point it at a YouTube link, a Loom, a Vimeo, a Riverside export, a Zoom recording, a webinar, or a competitor's ad — it pulls the transcript, marks the key moments with timestamps, and writes a summary that flags action items, decisions, and quotable lines. v1 is transcript-first; the frame-and-vision roadmap sits under Deferred capabilities.
Relationship to /transcripts
watch-video is the general any-source acquisition-to-summary tool: it fetches a transcript from whatever platform the video lives on, then produces transcript + key moments + summary. /transcripts (transcript-analysis, at primitives/social/youtube/transcripts) stays the YouTube-specific deep insight-extraction pipeline — SCQA structure, the verbatim-quote Iron Law, feeding icp-behavioural + tov-guidelines. They compose, they don't compete: when a YouTube job needs deep structured insight extraction, hand the transcript watch-video pulls to /transcripts. Neither is deprecated.
Triggers
Run when the user says: "watch this video", "transcribe this Loom", "analyze this video", "summarize this recording", "key moments from this", "what happened in this video", "video notes from [url]".
Do NOT run for:
- Deep insight extraction from a YouTube transcript →
/transcripts - Sales-call win/loss analysis →
/win-loss - A 2-3 sentence answer the user could get without artifacts → just answer
Inputs
Required: a video URL (any supported source) or a pasted/linked transcript.
Optional: the video's purpose (client call, competitor ad, webinar, talk) — sharpens the summary framing and the capture routing.
Process (v1 — transcript-first)
1. Parse the source
Detect the source from the URL pattern or file extension: YouTube (youtube.com, youtu.be, /shorts/, raw 11-char id), Loom (loom.com/share|embed), Vimeo, Riverside, a Zoom recording, or a local file. If ambiguous, ask.
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.
- 9d ago First seen · 122 lines · 180 tokens per session scan A 4c2b5d1f0a11
watch-video is a skill published in the GitHub repository matteotitta/genesys-skills (36 stars, last pushed 1mo ago), licensed MIT. It adds 180 tokens to every session and 1,771 once invoked, about $0.0009 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 2026-09-03.
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