Generative-Media-Skills is a toolkit that lets AI agents generate, edit, and display images, videos, and audio through the muapi command-line interface. It is for users of Claude Code, Cursor, Gemini CLI, and OpenCode who need multimodal media-generation workflows. The catalogue entries are the skills that expose these media capabilities to coding agents.
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 SamurAIGPT/Generative-Media-Skills --skill youtube-shortsgit clone --depth 1 https://github.com/SamurAIGPT/Generative-Media-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/samuraigpt/generative-media-skills/youtube-shorts)<a href="https://agentmods.dev/skills/samuraigpt/generative-media-skills/youtube-shorts"><img src="https://agentmods.dev/badge/skills/samuraigpt/generative-media-skills/youtube-shorts/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/samuraigpt/generative-media-skills/youtube-shorts"><img src="https://agentmods.dev/badge/skills/samuraigpt/generative-media-skills/youtube-shorts.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 | $0.00085 | $0.01605 |
| Opus 5 | $0.00043 | $0.00803 |
| Sonnet 5 | $0.00017 | $0.00321 |
| Haiku 4.5 | $0.00009 | $0.00161 |
Grade A, and why
muapi-youtube-shorts 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 13d 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 muapi-youtube-shorts — 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 — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
YouTube Shorts Generator
Long video → ranked vertical short clips, tuned for short-form social.
This skill is a platform-aware preset over the AI Clipping primitive. It picks the right aspect ratio and clip count for the target platform and delegates highlight extraction, dedupe, and face-tracked auto-crop to muapi.ai's managed /ai-clipping endpoint.
Reference implementation: https://github.com/SamurAIGPT/AI-Youtube-Shorts-Generator Underlying API: https://muapi.ai/playground/ai-clipping
When to Use This vs. AI Clipping
| Use this skill when… | Use AI Clipping directly when… |
|---|---|
| Target is YouTube Shorts / TikTok / Reels | You want full control over aspect / count |
| You want platform-tuned defaults | You want raw timestamps (--coords-only) |
You'd rather pass --platform tiktok than think about ratios |
You're integrating into a custom renderer |
Agent Execution Protocol
Step 1 — Collect Inputs
| Input | Default | Notes |
|---|---|---|
--source |
— | YouTube URL, hosted mp4 URL, or local file |
--platform |
shorts |
shorts | tiktok | reels | feed (sets ratio + count defaults) |
--num-clips |
platform default | Override clip count |
--aspect-ratio |
platform default | Override aspect ratio |
If the user gave only a URL, run with platform defaults — don't block.
Step 2 — Verify Prerequisites
muapi-cliinstalled and authed (muapi auth configure)MUAPI_API_KEYavailable
That's it. Transcription, highlight ranking, dedupe, and cropping all run server-side — no ffmpeg, no Python, no Whisper, no LLM keys needed locally.
Step 3 — Run the Pipeline
bash library/social/youtube-shorts/scripts/run-youtube-shorts.sh \
--source "<YOUTUBE_URL>" \
--platform shorts \
--num-clips 5 \
--view
The script:
- Resolves the source (uploads local files to muapi CDN if needed).
- Picks platform defaults if
--aspect-ratio/--num-clipsaren't passed. - Calls
muapi edit clipping(the/ai-clippingendpoint) with the chosen params. - Polls until done, prints a ranked summary, optionally downloads / opens clips.
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.
- 13d ago First seen · 174 lines · 85 tokens per session scan A 4d8c374199c9
muapi-youtube-shorts is a skill published in the GitHub repository SamurAIGPT/Generative-Media-Skills (4,263 stars, last pushed 3d ago), licensed MIT. It adds 85 tokens to every session and 1,605 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 muapi-youtube-shorts, differing in 0 lines, and is treated as a copy.
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