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-seo-optimizegit 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-optimize)<a href="https://agentmods.dev/skills/deeployco/youtube-seo-skills/youtube-seo-optimize"><img src="https://agentmods.dev/badge/skills/deeployco/youtube-seo-skills/youtube-seo-optimize/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-optimize"><img src="https://agentmods.dev/badge/skills/deeployco/youtube-seo-skills/youtube-seo-optimize.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 | $0.00087 | $0.02474 |
| Opus 5 | $0.00044 | $0.01237 |
| Sonnet 5 | $0.00017 | $0.00495 |
| Haiku 4.5 | $0.00009 | $0.00247 |
Grade A, and why
youtube-seo-optimize 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 11d 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 — 281 lines — stays where its author put it; the contents beside it link to each section on GitHub.
YouTube Metadata Optimizer (Advanced)
Produce paste-ready metadata that optimizes for the specific surface the user cares about, not a generic keyword-stuffing pass. Browse and Search require different strategies; generate both when the goal is mixed discovery.
Required Inputs (ask in one batch if missing)
- Video URL or raw topic + video outline/script
- Target surface: Browse (Home feed) / Search / Suggested / Shorts / mixed — this changes the title and thumbnail strategy
- Primary target keyword (or ask for suggestions via
youtube-seo-keywords) - Secondary keywords (2-4) for semantic coverage
- Target audience (beginner / intermediate / expert) and viewer persona if known
- Channel niche + brand voice (serious / playful / contrarian / warm)
- Is this long-form or Shorts? (and length if long-form)
- Top 3 audience countries/languages (for translated metadata)
- Competing videos: 3 URLs or keyword for SERP grid fetch
Optimization Strategy by Surface
| Surface | Title pattern | Thumbnail rule | Description priority |
|---|---|---|---|
| Browse | Emotional hook first, keyword second | Face + emotion + ≤3 words text | Above-fold selling the click |
| Search | Keyword first, hook second | Clarity over drama | Full keyword + entity coverage |
| Suggested | Adjacency to parent video | Same grid style as parent | Cross-link to parent video |
| Shorts | ≤40 chars, visceral hook | Vertical crop, muted-readable text | Minimal — first 2 lines only |
| Mixed | Browse title + Search-heavy description | Browse-style thumbnail | Full entity coverage |
Outputs (deliver all nine blocks)
1. Titles — 5 variants tagged by surface
Deliver as a table with length, surface tag, hook type, and primary keyword position:
| # | Title | Chars | Surface | Hook | KW Pos |
|---|---|---|---|---|---|
| A | ... | 64 | Browse | Curiosity | char 42 |
| B | ... | 68 | Search | Authority | char 1 |
| C | ... | 59 | Browse | Number | char 3 |
| D | ... | 71 | Mixed | Contrarian | char 8 |
| E | ... | 66 | Search | Benefit | char 5 |
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.
- 11d ago First seen · 281 lines · 87 tokens per session scan A b118db725cee
youtube-seo-optimize is a skill published in the GitHub repository deeployCO/youtube-seo-skills (9 stars, last pushed 5mo ago), licensed MIT. It adds 87 tokens to every session and 2,474 once invoked, about $0.0004 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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