What system requirements are needed for this skill?

The skill requires FFmpeg and FFprobe installed on your system path, along with Python 3.8 or higher to execute the analysis scripts.

Does the report require a web server to view?

No, the script generates a single, self-contained HTML file with embedded base64 images that works offline and can be shared easily.

Can I compare videos of different file formats?

Yes, as long as FFmpeg supports the formats. It commonly handles .mp4, .mov, .avi, .mkv, and .webm comparisons.

Which video quality metrics are included in the report?

It calculates PSNR (Peak Signal-to-Noise Ratio) for pixel-level similarity and SSIM (Structural Similarity Index) for perceptual similarity measurement.

How does the skill handle videos of different durations?

The script will automatically truncate the comparison to the shortest video's length and provide a warning notification in the terminal and report.

Video Quality Comparer

Name: Video Quality Comparer
Author: daymade

bydaymade

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147

Developer Tools

Generates interactive visual and metric-based comparison reports for analyzing video compression and quality differences.

About

Video Quality Comparer is a professional utility designed for developers and media engineers to evaluate video compression efficiency by comparing original and processed files. It automates the extraction of frame-by-frame visual data and calculates industry-standard metrics like PSNR and SSIM, delivering a self-contained, interactive HTML report. This skill is ideal for fine-tuning codec settings, optimizing bitrates, and performing automated quality assurance on video delivery pipelines directly within the Claude Code environment.

Key Features

Interactive HTML reports with slider, side-by-side, and grid views
Configurable sampling intervals for performance and detail control
Integrated FFmpeg validation and secure path handling
Automated PSNR and SSIM quality metric calculation
Self-contained report generation with base64 embedded frame data
147 GitHub stars

Use Cases

Automating quality audits for video transcoding and processing pipelines
Evaluating visual fidelity loss across different bitrate targets
Benchmarking performance between codecs like H.264, HEVC, and AV1

About

Key Features

Interactive HTML reports with slider, side-by-side, and grid views
Configurable sampling intervals for performance and detail control
Integrated FFmpeg validation and secure path handling
Automated PSNR and SSIM quality metric calculation
Self-contained report generation with base64 embedded frame data
147 GitHub stars

Use Cases

Automating quality audits for video transcoding and processing pipelines
Evaluating visual fidelity loss across different bitrate targets
Benchmarking performance between codecs like H.264, HEVC, and AV1