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 deeployCO/youtube-seo-skills --skill youtube-seogit clone --depth 1 https://github.com/deeployCO/youtube-seo-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/deeployco/youtube-seo-skills/youtube-seo)<a href="https://agentmods.dev/skills/deeployco/youtube-seo-skills/youtube-seo"><img src="https://agentmods.dev/badge/skills/deeployco/youtube-seo-skills/youtube-seo/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/deeployco/youtube-seo-skills/youtube-seo"><img src="https://agentmods.dev/badge/skills/deeployco/youtube-seo-skills/youtube-seo.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 | $0.00108 | $0.03669 |
| Opus 5 | $0.00054 | $0.01835 |
| Sonnet 5 | $0.00022 | $0.00734 |
| Haiku 4.5 | $0.00011 | $0.00367 |
Grade A, and why
youtube-seo 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 12d 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 — 262 lines — stays where its author put it; the contents beside it link to each section on GitHub.
YouTube SEO Orchestrator (Advanced)
Master skill for YouTube SEO work. Detect intent, delegate to the right sub-skill, and provide the shared advanced ranking model that every sub-skill references. If intent is ambiguous, ask once before proceeding.
Routing Table
| User intent / input | Sub-skill |
|---|---|
| "audit my channel", channel URL alone, "full YouTube check" | youtube-seo-audit |
| Single video URL, "analyze this video", "why isn't this ranking" | youtube-seo-video |
| "optimize title/description/tags", "rewrite metadata", "improve CTR copy" | youtube-seo-optimize |
| "channel branding", "about page", "banner", "playlists", "channel trailer" | youtube-seo-channel |
| "YouTube keywords", "topic research", "what should I make a video about" | youtube-seo-keywords |
| "thumbnail review", "CTR thumbnail", "is my thumbnail good" | youtube-seo-thumbnail |
| "competitor analysis", "what are [channel] doing", "competing videos" | youtube-seo-competitor |
Advanced Ranking Model
YouTube's recommender is NOT a keyword-match system. It is a multi-surface reinforcement-learning recommender that optimizes for long-term user satisfaction (the "Reinforce" paper, Covington et al. 2016 + DRL updates). Each surface has its own objective:
| Surface | Primary objective | Dominant signal |
|---|---|---|
| Browse (Home feed) | Session watch time + return rate | CTR-on-impression, persona match, freshness |
| Suggested (sidebar / autoplay) | Next-video watch time | Topical adjacency, session continuation, co-view graph |
| Search | Query satisfaction | Keyword/entity match, APV for that query, click depth |
| Shorts feed | Swipe-through rate + watch loops | Hook in <1s, loopability, audio trend |
| Notifications | Open rate in first hour | Subscriber affinity, bell-on CTR history |
| External | Retention of new viewers | Intro strength, subscribe-from-external rate |
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.
- 12d ago First seen · 262 lines · 108 tokens per session scan A 755d0499ea90
youtube-seo is a skill published in the GitHub repository deeployCO/youtube-seo-skills (9 stars, last pushed 5mo ago), licensed MIT. It adds 108 tokens to every session and 3,669 once invoked, about $0.0005 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 2026-08-31.
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