Shot Quality Validator

Validate generated video shots against reference materials and technical specifications.

30|4|Updated Jan 26, 2026
One-click install
npx skills add https://github.com/kaigani/codeywood --skill shot-quality-validator
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: Shot Quality Validator
Source: https://github.com/kaigani/codeywood/tree/main/skills/production/shot-quality-validator
Command: npx skills add https://github.com/kaigani/codeywood --skill shot-quality-validator

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the critical quality assurance process for generated video shots, identifying and flagging issues to ensure visual consistency and technical soundness before animation.

Core Features & Use Cases

  • Automated Quality Checks: Validates generated shots against reference images and technical specifications.
  • Consistency Scoring: Measures adherence to character, location, and style guides.
  • Issue Identification: Flags specific problems like artifacts, anatomical errors, or composition mismatches.
  • Use Case: After generating a batch of 50 shot images for a scene, this Skill can automatically review them, categorize them by quality (passed, flagged, failed), and generate a report detailing any necessary regenerations.

Quick Start

Run the shot quality validator skill on the generated shots for episode 1.

Frequently Asked Questions about Shot Quality Validator

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

FAQPage Schema
How do I check AI generated video shots for visual consistency against character references?

To check AI generated video shots for visual consistency, you validate the images against defined character references, location data, and shot list specifications to identify deviations and ensure adherence to visual standards.

What is shot validation in an AI video production pipeline?

Shot validation in an AI video production pipeline is the post-generation quality assurance process of reviewing generated images to flag artifacts, anatomical errors, or composition mismatches before animation begins.

How do I automate quality assurance for a batch of generated shot images?

Automate quality assurance for generated shot images by running a validation review that categorizes shots by quality, flags technical issues, and outputs a report detailing any necessary regenerations.

Can I use a consistency check to detect anatomical errors in AI video shots?

Yes, a consistency check can detect anatomical errors in AI video shots by comparing the generated images against technical specifications and reference materials to identify specific visual deviations.

Does shot validation work for large batches of scene images?

Shot validation works for large batches of scene images by automatically reviewing the generated shots, categorizing them into passed, flagged, or failed groups, and generating a detailed report for the entire set.