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 AlekseiUL/sprut-agent-kit --skill youtube-seogit clone --depth 1 https://github.com/AlekseiUL/sprut-agent-kitWrote 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/alekseiul/sprut-agent-kit/youtube-seo)<a href="https://agentmods.dev/skills/alekseiul/sprut-agent-kit/youtube-seo"><img src="https://agentmods.dev/badge/skills/alekseiul/sprut-agent-kit/youtube-seo/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/alekseiul/sprut-agent-kit/youtube-seo"><img src="https://agentmods.dev/badge/skills/alekseiul/sprut-agent-kit/youtube-seo.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 | $0.00019 | $0.01541 |
| Opus 5 | $0.00010 | $0.00771 |
| Sonnet 5 | $0.00004 | $0.00308 |
| Haiku 4.5 | $0.00002 | $0.00154 |
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 10d 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 — 213 lines — stays where its author put it; the contents beside it link to each section on GitHub.
YouTube SEO Generator
Generate click-worthy, SEO-optimized titles, descriptions, timecodes and hashtags for YouTube videos.
✍️ Правила текста (стиль владельца)
Обязательно:
- Дефис (-) вместо длинного тире (—). ВСЕГДА
- Сильные глаголы, короткие предложения
- Личный опыт, метафоры из жизни
- Хук в заголовке, интрига в первых 2 строках описания
Запрещено:
- Длинное тире (—) - заменять на дефис (-)
- "Конечно", "Безусловно", "Стоит отметить", "Является"
- Канцелярит и пассивный залог
- Больше 1 эмодзи в описании
Полные правила:
skills/copywriter/SKILL.md
Workflow
Step 1: Get transcript
If user provides video/audio file:
# Extract audio if needed (video → audio)
ffmpeg -i video.mp4 -vn -acodec libmp3lame audio.mp3
# Transcribe via OpenAI Whisper API
{skillsDir}/openai-whisper-api/scripts/transcribe.sh audio.mp3 --language ru --json --out transcript.json
If user provides transcript text: Use directly.
Step 2: Analyze transcript
- Identify main topic and goal
- Extract key insights, numbers, facts
- Map narrative structure (for timecodes)
- Determine content type:
- Tutorial → focus on value and steps
- Case study / research → focus on results and insights
- Review / comparison → focus on comparison and choice
- Interview → focus on expert and their opinion
Step 3: Generate metadata
Style Guide
- First person (as channel author)
- Tone: sincere, professional, not pushy
- ONE emoji maximum in entire description
- Avoid clichés: "В этом видео я расскажу..."
- Natural keyword integration, no spam
Target Keywords (use contextually)
- Автоматизация, n8n, AI-агент
- Искусственный интеллект / AI
- Промпт / prompt engineering
- Additional keywords from transcript content
Avoid (YouTube demonetization triggers)
- Violence, weapons, drugs, gambling
- Forex/crypto (unless educational)
- Profanity, discrimination
- Misleading clickbait
- Pushy "подпишись/лайкни" — use neutral alternatives
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.
- 10d ago First seen · 213 lines · 19 tokens per session scan A 0c76420bbe9d
youtube-seo is a skill published in the GitHub repository AlekseiUL/sprut-agent-kit (63 stars, last pushed 3mo ago), licensed MIT. It adds 19 tokens to every session and 1,541 once invoked, about $0.0001 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 2026-08-30.
Other skills, from other repositories
weather
Get current weather and forecasts (no API key required).
canvas-design
Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.
therapeutic-ifs
Unified inner work engine: Schema deconstruction (diagnosis) + IFS therapy (treatment). Absorbs: schema-deconstruction.
dashboard-builder
Build self-contained interactive HTML dashboards with charts, filters, and tables. Generates a single browser-openable file — no server or dependencies required.
bionic-decision-engine
Unified mathematical arbitrator for all resource allocation decisions — money, time, energy, relationships. Absorbs 46 decision protocols + 24 strategy protocols into one dense engine.
daemon-loop
Autonomous recurring agent tasks — converts workflows into persistent background daemons that run on intervals. Stolen from Boris Cherny's Claude Code /loop pattern (2026-03-31).