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 julianobarbosa/claude-code-skills --skill youtube-searchgit clone --depth 1 https://github.com/julianobarbosa/claude-code-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/julianobarbosa/claude-code-skills/youtube-search)<a href="https://agentmods.dev/skills/julianobarbosa/claude-code-skills/youtube-search"><img src="https://agentmods.dev/badge/skills/julianobarbosa/claude-code-skills/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/julianobarbosa/claude-code-skills/youtube-search"><img src="https://agentmods.dev/badge/skills/julianobarbosa/claude-code-skills/youtube-search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 91 Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
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 | $0.00074 | $0.01005 |
| Opus 5 | $0.00037 | $0.00502 |
| Sonnet 5 | $0.00015 | $0.00201 |
| Haiku 4.5 | $0.00007 | $0.00101 |
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 8d 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
YouTubeSearch
Search YouTube by query and return structured, human-readable results with metadata and engagement metrics.
What It Does
Runs a yt-dlp search against YouTube, returning the top N results (default 20) filtered to a recent time window (default 6 months). Each result includes:
- Title and URL
- Channel name and subscriber count
- View count and duration
- Upload date
- Engagement ratio (views / subscribers) — a quick signal for whether a video over- or under-performed relative to the channel's audience
Numbers are human-readable (e.g., 1.2M, 45.3K). Results are separated by dividers for easy scanning.
Requirements
yt-dlpinstalled and in PATHjqinstalled and in PATHbcinstalled (standard on macOS/Linux)
Usage
Run the bundled script:
bash ~/.claude/skills/YouTubeSearch/scripts/yt-search.sh "<search query>" [--count N] [--months N]
Parameters
| Flag | Default | Description |
|---|---|---|
| (positional) | — | Search query (required) |
--count |
20 | Number of results to return |
--months |
6 | Only include videos from the last N months |
Examples
# Basic search — top 20 results from last 6 months
bash ~/.claude/skills/YouTubeSearch/scripts/yt-search.sh "kubernetes security best practices"
# Narrow to 5 results from the last month
bash ~/.claude/skills/YouTubeSearch/scripts/yt-search.sh "rust async tutorial" --count 5 --months 1
# Broader window — last 2 years
bash ~/.claude/skills/YouTubeSearch/scripts/yt-search.sh "home lab setup" --months 24
Interpreting the Engagement Ratio
The views-to-subscribers ratio helps identify standout content:
- > 1.0x — The video got more views than the channel has subscribers. Strong signal that the topic resonated or the algorithm boosted it.
- 0.3x - 1.0x — Typical range for established channels.
- < 0.3x — Below average reach. Could mean the topic is niche, the thumbnail/title underperformed, or the channel's audience has moved on.
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.
- 8d ago First seen · 92 lines · 74 tokens per session scan A b7af83227f6a
youtube-search is a skill published in the GitHub repository julianobarbosa/claude-code-skills (10 stars, last pushed 16d ago), licensed MIT. It adds 74 tokens to every session and 1,005 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 2026-09-03.
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