brand-voice

Load brand-voice rules and anti-ai-tone constraints into content prompts.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/AllenZhou/MIRISE --skill brand-voice-allenzhou
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: brand-voice
Source: https://github.com/AllenZhou/MIRISE/tree/main/agents/uae-docs-pipeline/skills/brand-voice
Command: npx skills add https://github.com/AllenZhou/MIRISE --skill brand-voice-allenzhou

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Defines and enforces MIRISE's brand voice by combining brand-voice rules with anti-ai-tone constraints in content prompts, ensuring consistent messaging and avoiding AI-flavored writing.

Core Features & Use Cases

  • Establishes three positive principles (professional partnership, data-grounded statements, action-oriented language) and three prohibitions (no hype, no lecturing, no generic claims) to guide writing.
  • Provides integration guidance for content-agent prompts, including referencing the anti-ai-tone rules and a voice-examples repository for few-shot guidance.
  • Supports QA workflows by enabling consistent tone checks during copy review and editing, and by embedding explicit NEXT-step prompts in outputs.

Quick Start

Load brand-voice rules and anti-ai-tone constraints into content-agent prompts to start generating aligned MIRISE copy.

Frequently Asked Questions about brand-voice

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

FAQPage Schema
How do I maintain a consistent brand voice and avoid AI tone in generated content?▼

To maintain a consistent brand voice and avoid AI tone, load specific brand-voice rules and anti-ai-tone constraints directly into your content prompts. This enforces professional, data-grounded, action-oriented language while prohibiting hype and lecturing.

What is the best way to enforce tone guidelines during content QA workflows?▼

The best way to enforce tone guidelines during content QA workflows is to embed brand-voice rules and anti-ai-tone constraints into your review process. This enables consistent tone checks and ensures outputs include explicit next-step prompts.

How does data-grounding work when defining brand voice rules for content agents?▼

Data-grounding works by enforcing specific positive principles within brand voice rules, requiring content agents to generate professional, data-driven statements. This ensures all generated copy relies on factual data rather than generic claims.

Can I use few-shot examples to guide brand voice generation in content prompts?▼

Yes, you can use few-shot examples to guide brand voice generation by integrating a voice-example repository into your content-agent prompts. This provides specific few-shot guidance to align generated copy with the desired tone.

Does this brand voice approach work without external dependencies?▼

Yes, this brand voice approach works without external dependencies. It operates by loading internal brand-voice rules, anti-ai-tone constraints, and a voice-example repository directly into content prompts to guide writing tasks.

Why should I prohibit hype and lecturing when defining a brand voice?▼

You should prohibit hype and lecturing to ensure the brand voice remains professional and action-oriented. The brand voice rules explicitly ban hype, lecturing, and generic claims to maintain clear, data-grounded messaging.