media-processing

Automates image, audio, video batch resizing, conversion and optimization workflows using FFmpeg, ImageMagick, and Python scripts.

Updated Mar 24, 2026
One-click install
npx skills add https://github.com/tkmh04/CoffeeHouse-Management-System --skill media-processing-tkmh04
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: media-processing
Source: https://github.com/tkmh04/CoffeeHouse-Management-System/tree/main/.agents/skills/media-processing
Command: npx skills add https://github.com/tkmh04/CoffeeHouse-Management-System --skill media-processing-tkmh04

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Media processing tasks across images, audio, and video are often manual, error-prone, and hard to reproduce. This Skill provides repeatable, script-driven workflows that orchestrate FFmpeg, ImageMagick, and Python helpers to streamline batch processing.

Core Features & Use Cases

  • Image workflows: batch resizing, thumbnail generation, and format conversions.
  • Media conversion and optimization: automatic handling of video, audio, and image assets with deterministic outputs.
  • Video optimization: resolution control, CRF-based encoding, and before/after summaries for performance improvements.

Quick Start

Batch process a directory of media assets to resize images, convert formats, and optimize videos using the included scripts.

Frequently Asked Questions about media-processing

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate batch resizing and format conversion for images?

Batch resizing and format conversion for images is automated by orchestrating ImageMagick and Python helpers. It processes directories recursively with deterministic, non-destructive defaults to ensure repeatable media workflows.

What is the best way to optimize video resolution and encoding in a pipeline?

Video optimization in a pipeline is handled using FFmpeg with CRF-based encoding and resolution control. It generates before and after summaries to track performance improvements while maintaining deterministic outputs.

Do I need to install FFmpeg and ImageMagick separately to use these batch processing workflows?

FFmpeg and ImageMagick are required as external dependencies for executing the batch processing scripts. The workflows coordinate these tools alongside Python helpers to automate media conversion, resizing, and optimization.

Can I process audio and video assets recursively without losing the original files?

Recursive batch operations across audio and video assets are supported with non-destructive defaults. It orchestrates FFmpeg to convert and optimize media files deterministically without altering the original source assets.

Why should I use script-driven media processing instead of manual FFmpeg commands?

Script-driven media processing eliminates manual, error-prone FFmpeg commands by enforcing deterministic, reproducible workflows. It coordinates batch operations across images, audio, and video for development and archival pipelines.