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guideline-generation

Generate Markdown brand voice guidelines from documents and recorded conversations.

1|Updated Mar 30, 2026
Search Tags:#style-guide#brand-voice#confidence-scoring#tone-of-voice#conversation-analysis#document-analysis#guideline
One-click install
npx skills add https://github.com/ilove323/comlan-skills --skill guideline-generation-ilove323
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: guideline-generation
Source: https://github.com/ilove323/comlan-skills/tree/main/partner-built/brand-voice/skills/guideline-generation
Command: npx skills add https://github.com/ilove323/comlan-skills --skill guideline-generation-ilove323

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill transforms disparate brand materials—documents, discovery reports, and call recordings—into a single, actionable brand voice guideline so teams can produce consistent, on-brand content without manual synthesis or guesswork.

Core Features & Use Cases

  • Multisource synthesis: Ingests brand documents (PDF, PPTX, DOCX, MD, TXT), discovery reports, and conversation transcripts to extract voice attributes, messaging pillars, and tone patterns.
  • Structured, LLM-ready output: Produces a complete Markdown guideline following a template, with provenance for each claim, per-section confidence scores, and prioritized open questions for team review.
  • Quality assurance and safe saving: Runs checklist validation, removes or anonymizes PII, and archives previous versions when saving to the user's work directory for future enforcement and reuse.
  • Use case: Turn a set of uploaded brand PDFs and three sales call transcripts into a production-ready brand voice guide for onboarding content writers and aligning sales messaging.

Quick Start

Generate a comprehensive brand voice guideline from the uploaded brand documents and call transcripts, include confidence scores and open questions, and save the result to my work directory.

Frequently Asked Questions about guideline-generation

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

FAQPage Schema
How do I generate a brand voice guideline from multiple documents and call transcripts?▼

A brand voice guideline defines voice attributes, tone matrices, and messaging frameworks extracted from brand materials. It transforms documents and recorded conversations into a structured Markdown file, ensuring teams produce consistent, on-brand content without manual synthesis or guesswork.

Can I use recorded sales calls and discovery reports to create a style guide?▼

Brand voice guidelines include per-section provenance, confidence scores, and prioritized open questions with agent recommendations. They run checklist validation, remove or anonymize PII, and archive previous versions when saving to the work directory for future enforcement.

What is the best way to create onboarding materials for content writers from existing brand PDFs?▼

To build a brand voice guideline, upload brand documents and conversation transcripts into the work directory. The system analyzes the inputs, applies a provided template, generates a structured Markdown file with confidence scores, and saves it to .openclaw/brand-voice-guidelines.md.

Does the generated style guide include confidence scores and source tracking?▼

Brand voice guideline generation requires inputs like PDF, PPTX, DOCX, MD, TXT files, or conversation transcripts. It is suited for scenarios such as creating style guides, onboarding materials, content enforcement, and sales enablement, saving outputs when a user work directory is available.

Are there limitations when generating brand voice guidelines from text files and conversation transcripts?▼

After generating a brand voice guideline, the structured Markdown output is saved to the .openclaw directory for content enforcement and reuse. Downstream actions include using the guideline for onboarding materials, sales enablement, and aligning messaging across teams.

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