dubery-v3-validator

Validate v3 UGC prompts against product fidelity, naturalism, and JSON schema.

Updated Mar 9, 2026
One-click install
npx skills add https://github.com/RASCLAW/DuberyMNL --skill dubery-v3-validator
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: dubery-v3-validator
Source: https://github.com/RASCLAW/DuberyMNL/tree/main/.claude/skills/dubery-v3-validator
Command: npx skills add https://github.com/RASCLAW/DuberyMNL --skill dubery-v3-validator

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill acts as a pre-spend gate for v3 UGC prompts, ensuring prompts align to product fidelity, naturalism constraints, and strict JSON schema before image-generation processing.

Core Features & Use Cases

  • Validates v3 UGC prompts against product fidelity, camera-relative directions, and category routing data.
  • Parses embedded JSON blocks and enforces a strict schema to prevent malformed or unsafe prompts.
  • Provides actionable feedback for RA and content teams, stopping invalid prompts early to save compute.

Quick Start

Feed the validator a v3 UGC prompt text file and receive a pass/fail report with detailed issues.

Frequently Asked Questions about dubery-v3-validator

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

FAQPage Schema
How do I validate UGC prompts against a JSON schema before image generation?

You can validate UGC prompts against a strict JSON schema by feeding the prompt text file to a pre-spend validation gate. This enforces required fields, product fidelity, and naturalism constraints to prevent malformed or unsafe image generation prompts.

What is pre-spend validation for UGC image prompts?

Pre-spend validation is a gate that checks v3 UGC prompts for product fidelity, naturalism, and JSON schema compliance before processing. It stops invalid prompts early to save compute and provides actionable feedback for content teams.

Does prompt validation check prodref routing and image input references?

Yes, prompt validation checks image_input references, sidecar prodref data, and category routing for kraft and hero assets. It applies discipline checks across V1–V8 to ensure prompts align with product fidelity and naturalism constraints.

How do I enforce strict JSON structure and required fields in UGC prompts?

To enforce strict JSON structure, the validator parses embedded JSON blocks within UGC prompts and checks for required fields. It enforces discipline checks across V1–V8 to prevent invalid prompts and unsafe content from reaching image generation.

Why does my v3 UGC prompt fail naturalism and product fidelity checks?

A v3 UGC prompt fails validation if it violates product fidelity, naturalism constraints, or the strict JSON schema. The validator generates a pass/fail report with detailed issues, stopping invalid prompts early to save compute resources.

Can I validate v3 pipeline outputs for kraft and hero assets?

Yes, you can validate prompts built from v3 pipeline outputs by checking category routing for kraft and hero assets. The validator enforces camera-relative directions and product fidelity constraints across V1–V8 disciplines before image generation.