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Trim and cut videos by timestamp with precision. Supports both stream copy (fast) and re-encoding (quality) modes. Use when you need to extract specific segments from videos, create clips from highlights, or cut unwanted portions.
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SOC 職業分類に基づく
| name | video-trimmer |
| description | Trim and cut videos by timestamp with precision. Supports both stream copy (fast) and re-encoding (quality) modes. Use when you need to extract specific segments from videos, create clips from highlights, or cut unwanted portions. |
| allowed-tools | Bash(ffmpeg:*) |
| compatibility | Requires FFmpeg |
| metadata | {"version":"1.0"} |
This skill enables AI agents to trim and cut videos with precision using FFmpeg.
scripts/trim.pyTrim video to specified time range.
Usage:
python skills/video-trimmer/scripts/trim.py <video_path> [options]
Options:
--start, -s: Start time (seconds or HH:MM:SS) - required--end, -e: End time (seconds or HH:MM:SS) - required--output, -o: Output video path (default: <video_path>_trimmed.mp4)--reencode: Re-encode video (higher quality, slower)--codec: Video codec for re-encoding (default: libx264)--quality: Quality preset (fast, medium, slow) - default: fast--copy: Use stream copy (faster, no quality loss)Examples:
Trim 10-second segment:
python skills/video-trimmer/scripts/trim.py video.mp4 --start 30 --end 40
Trim with timestamp format:
python skills/video-trimmer/scripts/trim.py video.mp4 --start 00:01:30 --end 00:01:45
Re-encode for better quality:
python skills/video-trimmer/scripts/trim.py video.mp4 --start 30 --end 40 --reencode --quality medium
Fast stream copy:
python skills/video-trimmer/scripts/trim.py video.mp4 --start 30 --end 40 --copy
scripts/trim_multiple.pyTrim multiple segments from one video.
Usage:
python skills/video-trimmer/scripts/trim_multiple.py <video_path> --segments <json_file> [options]
Options:
--segments: JSON file with segment list--output-dir: Output directory (default: ./clips/)--copy: Use stream copy--prefix: Filename prefix for clipsSegments JSON Format:
[
{"start": 30, "end": 45},
{"start": 120, "end": 135},
{"start": 200, "end": 220}
]
Example:
python skills/video-trimmer/scripts/trim_multiple.py video.mp4 --segments segments.json --prefix highlight
Returns trimmed video file:
video_trimmed.mp4
Returns multiple clip files:
clips/
highlight_001.mp4
highlight_002.mp4
highlight_003.mp4
Supported time formats:
30, 45.5, 1201:30, 2:4500:01:30, 01:15:30After trimming, you can use these skills:
portrait-resizer: Convert to 9:16 portrait formatsubtitle-overlay: Add captions to clipsautocut-shorts: Full workflow with all stepshighlight-scannerportrait-resizersubtitle-overlay--copy for fast processing when quality isn't critical--reencode for frame-perfect cutsMain orchestration skill for automatic creation of short-form content (TikTok, YouTube Shorts, Instagram Reels) from long videos. Fully automated workflow: download video, transcribe, detect highlights (transcript + laughter + sentiment + scenes), trim segments, resize to 9:16 portrait, and add subtitles. Finds viral-worthy moments like OpusClip and Vizard.ai.
Combined analysis skill to find viral-worthy highlights from videos. Scans transcripts, detects laughter, analyzes sentiment/emotion, and uses scene changes to identify the most engaging moments for TikTok/Shorts/Reels. Produces ranked list of highlight segments with virality scores.
Download videos from YouTube URLs. Use when user wants to download a YouTube video for processing, editing, or transcription. Supports different quality options, audio-only extraction, and playlist downloads.
Convert videos to 9:16 portrait format (1080x1920) for TikTok, YouTube Shorts, Instagram Reels, and Facebook Reels. Supports smart cropping (face-aware), center cropping, and letterboxing. Maintains aspect ratio and quality.
Add burned-in subtitles/captions to video clips. Supports SRT/VTT/ASS subtitle files, customizable styling (font, size, color, position), and platform-specific presets for TikTok, YouTube Shorts, and Instagram Reels.
Transcribe audio from videos using Whisper (local), OpenAI Whisper API, Google Speech-to-Text, or Gemini API (gemini-flash-lite-latest). Use when you need to convert video/audio to text for further processing, subtitle generation, or content analysis. Supports multiple languages, speaker diarization, and timestamp-accurate transcription. Gemini provides additional features like emotion detection and viral segment analysis.