Muapi Youtube Shorts

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](../../edit/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

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When to Use This vs. AI Clipping

| Use this skill when… | Use [AI Clipping](../../edit/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 |

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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.

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Step 2 — Verify Prerequisites

• muapi-cli installed and authed (muapi auth configure)
• MUAPI_API_KEY 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.

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Step 3 — Run the Pipeline

bash library/social/youtube-shorts/scripts/run-youtube-shorts.sh \
  --source "" \
  --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.

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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.

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Platform Defaults

| Platform | Flag | Aspect | Default clips | Notes | |:---|:---|:---|:---|:---| | YouTube Shorts | --platform shorts | 9:16 | 3 | Hook in first 1s | | TikTok | --platform tiktok | 9:16 | 5 | Higher energy, longer ok | | Instagram Reels | --platform reels | 9:16 | 3 | Hook in first 1s | | Instagram Feed | --platform feed | 1:1 | 3 | Static-feel works well |

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

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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 "" --platform tiktok --view

Square Instagram feed clips:

bash run-youtube-shorts.sh --source "" --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 request_id, poll later):

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

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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.

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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.

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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.

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Done Criteria

The skill is done when:

1. result.shorts has up to num_clips entries, each with a working clip_url.
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.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: SamurAIGPT
• Source: SamurAIGPT/Generative-Media-Skills
• License: MIT
• Homepage: https://muapi.ai?utmsource=github&utmmedium=about&utm_campaign=generative-media-skills

Install and usage instructions live in the source repository linked above.