voice-validator

Validate content against a target voice using a negative-prompt checklist.

415|44|Updated Mar 18, 2026
One-click install
npx skills add https://github.com/notque/claude-code-toolkit --skill voice-validator
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: voice-validator
Source: https://github.com/notque/claude-code-toolkit/tree/main/skills/voice-validator
Command: npx skills add https://github.com/notque/claude-code-toolkit --skill voice-validator

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill implements a rigorous critique-and-rewrite loop that enforces voice fidelity across generated content, ensuring alignment with a specified target voice and preventing drift or misrepresentation.

Core Features & Use Cases

  • Iterative scan-revise-rescan workflow for voice content
  • Reports with quoted evidence and category labels for each violation
  • Automatic revision of content to fix voice violations while preserving meaning
  • Mode-based and checklist-driven validation for multiple voice profiles

Quick Start

Provide the target voice and content, then run the validator to begin the iterative critique.

Frequently Asked Questions about voice-validator

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

FAQPage Schema
How do I validate generated content against a specific brand voice?▼

Content voice validation works by applying a comprehensive negative-prompt checklist across tone, structure, language, emotion, questions, and metaphors to identify real-time violations and prevent voice drift.

How do I automatically fix voice violations in generated text?▼

You can automatically fix voice violations by running an iterative scan-revise-rescan workflow that automatically revises content to resolve issues while preserving the original meaning.

Can I validate content for multiple voice profiles using a checklist?▼

Yes, you can validate multiple voice profiles using mode-based and checklist-driven validation, which reports quoted evidence and category labels for each detected violation.

What is the best way to prevent voice drift in automated content generation?▼

The best way to prevent voice drift is enforcing an iterative critique-and-rewrite loop that rescans content up to three iterations to confirm all voice violations are resolved.

How many iterations does it take to confirm content passes voice validation?▼

Voice validation requires rescanning content up to three iterations after automatic revision to confirm a pass and ensure the generated text fully aligns with the target voice.