Mmcp.market

muapi-youtube-shorts skill

by SamurAIGPT·SamurAIGPT/Generative-Media-Skills·4.3k stars·MIT

Auto-generate viral 9:16 YouTube Shorts (or TikTok / Reels clips) from a long-form video. Thin platform-aware wrapper around the AI Clipping skill — picks sensible defaults for short-form social platforms (9:16, 30–60s sweet spot) and delegates the actual highlight extraction + crop to muapi.ai's `/ai-clipping` endpoint.

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Install the muapi-youtube-shorts skill

A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description.

git clone --depth 1 https://github.com/SamurAIGPT/Generative-Media-Skills.git /tmp/Generative-Media-Skills
mkdir -p ~/.claude/skills
cp -r /tmp/Generative-Media-Skills/.opencode/skills/muapi-youtube-shorts ~/.claude/skills/muapi-youtube-shorts
available in every project

In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub

The instructions your agent would load

SKILL.md as published, without the frontmatter. Read it 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

Agent Execution Protocol

Step 1 — Collect Inputs

If the user gave only a URL, run with platform defaults — don't block.

Step 2 — Verify Prerequisites

  • muapi-cli installed and authed (muapi auth configure)
  • MUAPIAPIKEY available

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:

  1. Resolves the source (uploads local files to muapi CDN if needed).
  2. Picks platform defaults if --aspect-ratio / --num-clips aren't passed.
  3. Calls muapi edit clipping (the /ai-clipping endpoint) with the chosen params.
  4. Polls until done, prints a ranked summary, optionally downloads / opens clips.

What Happens Server-Side

The /ai-clipping endpoint runs the full pipeline:

  • Transcribes the audio.
  • Ranks highlights through a virality framework — hook moments, emotional peaks, opinion bombs, revelation moments, conflict, quotable lines, story peaks, practical value.
  • Dedupes overlapping candidates by score.
  • Top-N selects and face-tracks vertical crops.

Each clip ships with score (0–100), opening hook line, and a one-sentence "why it works" reason.

Platform Defaults

Override any default with --aspect-ratio / --num-clips.

Quick Invocation Patterns

Single video, defaults:

bash run-youtube-shorts.sh --source "https://youtube.com/watch?v=VIDEO_ID"

TikTok preset — 5 clips, view in player:

bash run-youtube-shorts.sh --source "<URL>" --platform tiktok --view

Square Instagram feed clips:

bash run-youtube-shorts.sh --source "<URL>" --platform feed --num-clips 3

Batch — urls.txt with one URL per line:

xargs -a urls.txt -I{} bash run-youtube-shorts.sh --source "{}"

Async submit (returns requestid, poll later):**

REQUEST_ID=$(bash run-youtube-shorts.sh --source "<URL>" --async --output-json - | jq -r '.request_id')
muapi predict wait "$REQUEST_ID" --download ./outputs

Output Schema

{
  "source_video_url": "...",
  "shorts": [
    {
      "title": "The one mistake that cost me $50K",
      "start_time": 124.3,
      "end_time": 187.6,
      "score": 92,
      "hook_sentence": "Nobody talks about this, but it killed my first startup...",
      "virality_reason": "Opens with a number + regret, peaks on a contrarian lesson",
      "clip_url": "https://.../short_1.mp4"
    }
  ]
}

When reporting back, surface for each clip: rank, score, time range, title, hook, and clip URL.

Common Mistakes to Avoid

  1. Wrong aspect ratio for the platform — Shorts / TikTok / Reels are 9:16. The platform preset handles this; only override if you know why.
  2. Padding to hit --num-clips — if the API returns fewer survivors, return what you have. Don't ship low-score filler.
  3. Re-running on a 404'd clip URL — re-fetch the same request_id with muapi predict wait rather than re-clipping.

Failure Modes

  • API key missing or rejected — surface the error; don't fabricate a key.
  • Job timed out — bump --poll-timeout and retry.
  • Source URL not reachable — upload the file via muapi upload file and pass the returned URL.
  • Fewer clips returned than requested — source had fewer rankable highlights. Return what came back with a note.

Done Criteria

The skill is done when:

  1. result.shorts has up to numclips entries, each with a working clipurl.
  2. The user has been shown the ranked list (score, time range, title, hook, URL).
  3. If --output-json was set, the file exists and parses.

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