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damionrashford
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workflow-analysis-quality

Audit media files with ffprobe, MediaInfo, and VMAF/PSNR/SSIM metrics.

15|4|Updated Apr 18, 2026
Search Tags:#video#quality-control#loudness#ffprobe#vmaf#mediainfo#scene-detect
One-click install
npx skills add https://github.com/damionrashford/media-os --skill workflow-analysis-quality
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: workflow-analysis-quality
Source: https://github.com/damionrashford/media-os/tree/main/skills/workflow-analysis-quality
Command: npx skills add https://github.com/damionrashford/media-os --skill workflow-analysis-quality

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automate, unify, and validate media quality control across the encode-to-delivery pipeline, surfacing issues before ship.

Core Features & Use Cases

  • ffprobe stream details and MediaInfo diagnostics for deep metadata visibility.
  • Quality metrics across codecs (VMAF, PSNR, SSIM) with scalable reporting.
  • Scene and content analysis (PySceneDetect) plus crop/silence/black-frame/interlacing detection.
  • Playback scopes (ffplay) and bitstream forensics for DoVi/HDR metadata.
  • Metadata audits and automatic loudness compliance checks against common specs (Spotify/Apple/ATSC/EBU).
  • Automated CI QC gates to fail builds when encodes do not meet the spec.

Quick Start

Run the QC workflow on your latest encode to generate a full diagnostic report and CI-ready gate results.

Frequently Asked Questions about workflow-analysis-quality

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

FAQPage Schema
How do I automate media quality control checks across a transcoding pipeline?▼

Automate media quality control by probing files end-to-end with ffprobe and MediaInfo to surface metadata, quality, and compliance gaps before delivery. This generates a repeatable diagnostic workflow covering codecs, visual metrics, and CI gate automation.

How do I check loudness compliance against broadcast specs like EBU and ATSC?▼

Check loudness compliance by running automatic audits against common specs including Spotify, Apple, ATSC, and EBU. The workflow analyzes audio streams to detect violations and outputs CI-ready gate results to fail non-compliant encodes.

What is the best way to calculate VMAF, PSNR, and SSIM metrics for video encodes?▼

Calculate VMAF, PSNR, and SSIM quality metrics using scalable reporting within an automated QC workflow. This approach exposes visual quality degradation and generates comprehensive diagnostic reports for delivery validation.

How do I detect black frames, silence, and interlacing artifacts in video files?▼

Detect black frames, silence, and interlacing artifacts by running dedicated crop, black, silence, and idet detection probes. This scene and content analysis identifies delivery issues and outputs actionable audit results.

Can I fail a CI build automatically if an encode does not meet delivery specs?▼

Fail CI builds automatically by implementing automated QC gates that evaluate ffprobe analyses, loudness compliance, and visual quality metrics. Builds fail when encodes do not meet the defined spec, preventing delivery issues before ship.

How do I detect scene changes and audit Dolby Vision HDR metadata?▼

Detect scene changes using PySceneDetect and audit Dolby Vision or HDR metadata through bitstream forensics. This playback scope analysis validates advanced metadata compliance and exposes content variations for delivery prep.

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