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 T4wroot/agentic-seo --skill video-optimizationgit clone --depth 1 https://github.com/T4wroot/agentic-seoWrote 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/t4wroot/agentic-seo/video-optimization)<a href="https://agentmods.dev/skills/t4wroot/agentic-seo/video-optimization"><img src="https://agentmods.dev/badge/skills/t4wroot/agentic-seo/video-optimization/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/t4wroot/agentic-seo/video-optimization"><img src="https://agentmods.dev/badge/skills/t4wroot/agentic-seo/video-optimization.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 | $0.00081 | $0.02378 |
| Opus 5.5 | $0.00032 | $0.00951 |
| Sonnet 5.5 | $0.00016 | $0.00476 |
| Haiku 4.5 | $0.00008 | $0.00238 |
Grade A, and why
video-optimization 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 2mo 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.
This is a copy
100% identical to video-optimization — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 215 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SEO On-Page: Video Optimization
Guides video optimization for Google Search (main results, video mode, Google Images, Discover), video sitemap, VideoObject schema, and indexing. Note: Google now prioritizes YouTube video results in search; YouTube + Reddit comprise ~78% of social media citations in AI Overviews. For YouTube-specific optimization, see youtube-seo; for GEO distribution via YouTube, see generative-engine-optimization. References: Google Video SEO, Semrush YouTube SEO.
When invoking: On first use, if helpful, open with 1–2 sentences on what this skill covers and why it matters, then provide the main output. On subsequent use or when the user asks to skip, go directly to the main output.
Scope
- Discovery & indexing: HTML embed elements, video sitemap
- Metadata: Title, description, thumbnail; stable URLs
- Structured data: VideoObject schema
- Features: Video preview, key moments (Clip, SeekToAction), LIVE badge
- YouTube prioritization: Google favors YouTube in search; embed or host on YouTube for GEO citation
YouTube in Google Search (2025+)
Google prioritizes YouTube video results across search. YouTube receives 48.6B monthly visits (second to Google.com) and is treated as core search infrastructure for AI-driven discovery. Search Engine Land
| Context | Implication |
|---|---|
| AI Overviews | YouTube citations surged 25.21% since Jan 2025; instructional (+35.6%), visual demos (+32.5%); long-form dominates (94%) |
| GEO | YouTube + Reddit = ~78% of social media citations; Perplexity (38.7%) and Google AI Overviews (36.6%) drive most YouTube citations |
| Strategy | Embed YouTube on site pages for dual indexing; or host on YouTube for GEO citation. See youtube-seo, generative-engine-optimization |
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.
- 2mo ago First seen · 215 lines · 81 tokens per session scan A 7971edcd6140
video-optimization is a skill published in the GitHub repository T4wroot/agentic-seo (15 stars, last pushed 2mo ago), licensed MIT. It adds 81 tokens to every session and 2,378 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to video-optimization, differing in 2 lines, and is treated as a copy.
video-optimization compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| video-optimizationT4wroot/agentic-seo | Skill | 15 | 2mo ago | MIT | A | 81 | Claude Code, Codex |
| seodalroot/agentic-seo | Skill | 26 | 3d ago | MIT | A | 105 | Claude Code, Codex |
| githubdalroot/agentic-seo | Skill | 26 | 3d ago | MIT | A | 165 | Claude Code, Codex |
| grokipedia-recommendationsdalroot/agentic-seo | Skill | 26 | 3d ago | MIT | A | 110 | Claude Code, Codex |
| schema-markupdalroot/agentic-seo | Skill | 26 | 3d ago | MIT | A | 181 | Claude Code, Codex |
| brand-visual-generatordalroot/agentic-seo | Skill | 26 | 3d ago | MIT | A | 124 | Claude Code, Codex |
| image-optimizationdalroot/agentic-seo | Skill | 26 | 3d ago | MIT | A | 87 | Claude Code, Codex |