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 AZIO-126/azio-vault-os --skill youtube-searchgit clone --depth 1 https://github.com/AZIO-126/azio-vault-osWrote 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/azio-126/azio-vault-os/youtube-search)<a href="https://agentmods.dev/skills/azio-126/azio-vault-os/youtube-search"><img src="https://agentmods.dev/badge/skills/azio-126/azio-vault-os/youtube-search/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/azio-126/azio-vault-os/youtube-search"><img src="https://agentmods.dev/badge/skills/azio-126/azio-vault-os/youtube-search.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 | $0.00110 | $0.00930 |
| Opus 5 | $0.00055 | $0.00465 |
| Sonnet 5 | $0.00022 | $0.00186 |
| Haiku 4.5 | $0.00011 | $0.00093 |
Grade A, and why
youtube-search 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 — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
YouTube Search Skill
Search YouTube for videos and extract rich metadata including engagement metrics, channel info, and performance data. Perfect for research, content discovery, and feeding data into knowledge bases like NotebookLM.
What this skill does
- Searches YouTube for videos matching your query
- Extracts structured metadata: title, channel, views, subscribers, duration, upload date, URL
- Calculates engagement ratio (views-to-subscribers) to surface high-impact content
- Returns results in beautifully formatted output with human-readable numbers and dividers
- Filters results by date range (default: last 6 months)
- Returns top 20 results by default
How to use
Basic search
youtube-search "your search query"
Search specific date range
youtube-search "your search query" --months 12
Search all time
youtube-search "your search query" --months 0
Limit results
youtube-search "your search query" --limit 10
Output format
Each result displays:
- Title — Video name
- Channel — Creator name
- Views — Total views (human-readable: 1.2M, 543K, etc.)
- Subscribers — Channel subscriber count
- Engagement — Views-to-subscribers ratio (shows video reach relative to channel size)
- Duration — Video length in MM:SS format
- Upload Date — When video was published
- URL — Direct link to video
Results are separated by dividers for easy scanning.
Implementation
The skill uses yt-dlp to search YouTube and parse video metadata. It:
- Searches YouTube with the query
- Filters results by date (last 6 months by default)
- Extracts metadata: title, channel, stats, duration, upload date
- Calculates engagement ratio (views ÷ subscribers)
- Formats output with dividers, human-readable numbers (1.5M, 420K, etc.)
- Sorts by views (descending) by default
Requirements
yt-dlpinstalled (pip install yt-dlp)- Python 3.7+
- Internet connection
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 111 lines · 110 tokens per session scan A 259e5dca5e91
youtube-search is a skill published in the GitHub repository AZIO-126/azio-vault-os (2 stars, last pushed 5mo ago), licensed MIT. It adds 110 tokens to every session and 930 once invoked, about $0.0006 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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