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 ai-clippinggit 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/ai-clipping)<a href="https://agentmods.dev/skills/samuraigpt/generative-media-skills/ai-clipping"><img src="https://agentmods.dev/badge/skills/samuraigpt/generative-media-skills/ai-clipping/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/ai-clipping"><img src="https://agentmods.dev/badge/skills/samuraigpt/generative-media-skills/ai-clipping.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 | $0.00096 | $0.01844 |
| Opus 5 | $0.00048 | $0.00922 |
| Sonnet 5 | $0.00019 | $0.00369 |
| Haiku 4.5 | $0.00010 | $0.00184 |
Grade A, and why
muapi-ai-clipping 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-ai-clipping — 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 — 195 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Clipping
One API call: long video in → ranked vertical short clips out.
Each clip ships with a viral score (0–100), an opening hook line, a one-sentence "why it works" reason, and a hosted mp4 URL.
Underlying API: https://muapi.ai/playground/ai-clipping Reference implementation (open source): https://github.com/SamurAIGPT/AI-Youtube-Shorts-Generator
When to Use
- Auto-clip a podcast, interview, lecture, vlog, or stream into TikTok / Reels / Shorts.
- Extract the best 30–75s moments from any hosted video URL.
- Get face-tracked vertical (9:16), square (1:1), or portrait (4:5) crops without running ffmpeg locally.
If you only need raw timestamps for your own renderer, set --coords-only to skip cropping and just get the highlight ranges.
Agent Execution Protocol
Step 1 — Collect Inputs
| Input | Required | Default | Notes |
|---|---|---|---|
--video |
yes | — | Hosted mp4 URL, or local file path (auto-uploaded), or YouTube URL (if backend supports it) |
--num-clips |
no | 3 |
Number of highlights to extract |
--aspect-ratio |
no | 9:16 |
9:16 | 1:1 | 4:5 |
--coords-only |
no | off | Return just the highlight time ranges, skip cropping |
If the user gave only a video URL, run with defaults — don't block on questions.
Step 2 — Verify Prerequisites
muapi-cliinstalled and authed (muapi auth configure)MUAPI_API_KEYavailable (env var ormuapi auth statuspasses)
That's it. No ffmpeg, no Python, no Whisper install, no LLM keys. Everything runs server-side.
Step 3 — Run the Skill
bash library/edit/ai-clipping/scripts/run-ai-clipping.sh \
--video "https://example.com/podcast.mp4" \
--num-clips 5 \
--aspect-ratio 9:16 \
--view
The script:
- Resolves
--videoto a hosted URL (uploads local files viamuapi upload fileif needed). - Calls
muapi edit clippingwith the supported parameters. - Polls until the job is done (or returns the
request_idimmediately under--async). - Prints a ranked summary and, if
--output-jsonis set, writes the full result.
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 · 195 lines · 96 tokens per session scan A df222c2fa2c8
muapi-ai-clipping is a skill published in the GitHub repository SamurAIGPT/Generative-Media-Skills (4,263 stars, last pushed 3d ago), licensed MIT. It adds 96 tokens to every session and 1,844 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to muapi-ai-clipping, differing in 0 lines, and is treated as a copy.
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