media-processing_skill

This skill processes multimedia using FFmpeg and ImageMagick to convert, encode, resize, and filter media for web and apps.
  • Python

2

GitHub Stars

1

Bundled Files

2 months ago

Catalog Refreshed

4 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill mamba-mental/agent-skill-manager --skill media-processing

  • SKILL.md9.4 KB

Overview

This skill processes video, audio, and image files using FFmpeg and ImageMagick to handle conversion, encoding, filtering, streaming, and batch image manipulation. It supports hardware acceleration, 100+ formats, complex filtergraphs, and common streaming workflows (HLS/DASH). It is optimized for tasks like thumbnails, format conversion, codec-specific encoding, and image composition.

How this skill works

The skill constructs and runs FFmpeg commands for video/audio tasks: encoding, transcoding, frame extraction, streaming manifest generation, and hardware-accelerated encoding via NVENC/QSV. For images it uses ImageMagick (magick/mogrify) to convert formats, resize/crop, apply effects, watermark, and batch-process large sets. It also inspects media with ffprobe/identify to drive conditional pipelines.

When to use it

  • Convert or transcode videos and audio between formats and codecs (H.264, H.265, VP9, AV1).
  • Generate thumbnails, previews, or extract audio tracks from video files.
  • Create HLS/DASH manifests and prepare assets for adaptive streaming.
  • Batch resize, optimize, or apply effects to large image collections.
  • Apply overlays, watermarks, or composite images/videos programmatically.
  • Optimize media for web delivery with CRF, presets, and faststart flags.

Best practices

  • Prefer -c copy when no re-encoding is needed to save time and preserve quality.
  • Use CRF for consistent quality control; choose presets to balance speed vs. compression.
  • Test settings on small samples before batch processing large datasets.
  • Enable hardware acceleration (NVENC/QSV) for large encodes to reduce CPU load.
  • Strip metadata and use progressive JPEG/optimized WebP for web delivery.
  • Parallelize independent jobs (GNU Parallel) but cap threads to avoid memory exhaustion.

Example use cases

  • Transcode a set of .mov files to H.264 MP4 with consistent CRF and audio bitrate for web publishing.
  • Generate 4 responsive image sizes from a master image and place them in a CDN-ready folder.
  • Produce HLS renditions with multiple bitrates and an m3u8 playlist for adaptive streaming.
  • Extract a 30-second clip and a thumbnail at 5s for a video preview card.
  • Batch-convert PNG assets to optimized JPEGs and strip metadata for size reduction.

FAQ

Use FFmpeg for video/audio tasks and frame-based thumbnails; use ImageMagick for still-image transformations, effects, and batch in-place edits.

When should I enable hardware acceleration?

Enable NVENC/QSV when encoding many large videos or when CPU usage is a bottleneck; validate output quality vs. software encoders first.

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media-processing skill by mamba-mental/agent-skill-manager | VeilStrat