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 youtubegit 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/youtube)<a href="https://agentmods.dev/skills/t4wroot/agentic-seo/youtube"><img src="https://agentmods.dev/badge/skills/t4wroot/agentic-seo/youtube/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/youtube"><img src="https://agentmods.dev/badge/skills/t4wroot/agentic-seo/youtube.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 | $0.00076 | $0.00955 |
| Opus 5 | $0.00038 | $0.00477 |
| Sonnet 5 | $0.00015 | $0.00191 |
| Haiku 4.5 | $0.00008 | $0.00096 |
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 7d 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 youtube-seo — 0 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 — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Platforms: YouTube SEO
Guides YouTube video and channel optimization for search and discovery. Google now prioritizes YouTube video results in search; YouTube + Reddit comprise ~78% of social media citations in AI Overviews. Title, description, and thumbnail form an interconnected system; channels using systematic keyword strategies see 156% longer view durations, 89% better CTR, and 312% higher search discovery. Use this skill when optimizing videos for YouTube search, Google search, and AI citation. For website-embedded video SEO, see video-optimization.
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.
Initial Assessment
Check for project context first: If .claude/project-context.md or .cursor/project-context.md exists, read Sections 6 (Keywords), 11 (Content Strategy).
Identify:
- Video type: Tutorial, review, vlog, Shorts
- Target keyword: Primary and secondary
- Audience: Subscribers vs casual viewers
Video Titles
| Rule | Guideline |
|---|---|
| Length | Under 60 characters; mobile may show partial |
| Keyword | Primary keyword in first 5–55 characters |
| Structure | Social proof/authority + emotional trigger + primary keyword |
| Style | Conversational; avoid keyword stuffing |
| Avoid | ALL CAPS except emphasis |
Video Descriptions
| Rule | Guideline |
|---|---|
| First 2–3 sentences | Primary and secondary keywords naturally; meta description under 160 chars |
| Links | Website, store, relevant resources |
| Readability | Natural flow; help search understand topic |
Tags
- Help YouTube understand content; titles and descriptions matter more
- Use relevant tags; avoid over-optimization
Thumbnails
90% of best-performing videos use custom thumbnails.
| Rule | Guideline |
|---|---|
| Contrast | High contrast; readable fonts; bold colors |
| Composition | Rule of thirds; simple, uncluttered |
| Audience | Consider subscribers vs casual viewers |
| Test | What works evolves; test styles |
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.
- 7d ago First seen · 86 lines · 76 tokens per session scan A 3da4099316a0
youtube-seo is a skill published in the GitHub repository T4wroot/agentic-seo (15 stars, last pushed 7d ago), licensed MIT. It adds 76 tokens to every session and 955 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to youtube-seo, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
fire-your-seo-agency
A procedure for improving how a website appears in search engines and how AI answer systems find and cite it. It covers search, answer-engine, generative-AI, and Naver visibility.
content-thicken
Evidence-driven blog driver. Takes ONE target from the fused search plus AI-answer content library, pulls the real questions it has to answer, drafts a thick long-form guide against a template contract, validates it deterministically, and stops at preview. Two modes, thicken an already-earning post IN PLACE (never…
backlink-outreach
Find, evaluate, pitch and track natural backlink and content partnerships. Prospects come from the GEO citation data rather than a generic blog search: the targets are the pages an AI already cites when answering your category questions. Research runs on the Monid tool layer (web search and scrape, authority metrics…
geo-monitor
Run and read the GEO pipeline, which measures whether AI answer engines mention, recommend and cite your site. Puts a fixed registry of real user questions to an answer engine through the Monid tool layer, detects the three signals plus competitors, and turns "a rival is named and we are not" into a tracked work…
seo-intake
Run and read the SEO intake pipeline. Pulls the organic keyword set for your domain and for each competitor through the Monid tool layer, computes the gap locally, and routes every keyword to the one action that can help it (write-new / striking / build-depth / defend / noise). Use when asked to refresh the SEO queue…
bing-duplicate-content-fix
Audit article groups, WordPress categories, or supplied URLs for copied content, near-duplicate templates, search-intent overlap, and keyword cannibalization; prepare exact SEO/AEO/GEO fixes; apply only approved WordPress changes; verify saved and public results; and request a Bing recrawl when authorized. Use for…