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brand-voice-analyzer

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Analyzes a company's content to extract and codify their brand voice into a comprehensive style guide. Reads website copy, blog posts, emails, and social media to identify tone, vocabulary patterns, sentence structure, personality traits, and word preferences. Generates a brand-voice-guide.md and reviews new content against it.

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Source SKILL.md: https://github.com/OneWave-AI/claude-skills/blob/HEAD/brand-voice-analyzer/SKILL.md

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Brand Voice Analyzer

Ingest a company's existing content, reverse-engineer the voice behind it, produce a definitive brand voice guide any writer can follow, and review new content against an established guide.

Contents

  • references/voice-dimensions.md -- the seven-axis tone spectrum, vocabulary, sentence, personality, audience, and formatting dimensions to extract
  • references/guide-template.md -- required sections, quality standards, and pre-delivery checklist for brand-voice-guide.md
  • references/review-mode.md -- process and output format for scoring content against a guide
  • references/metrics.md -- quantitative and qualitative analysis techniques and citation standards
  • references/edge-cases.md -- handling for thin corpora, multiple voices, regulated industries, rebrands, plus interaction patterns

Workflow: Create a New Voice Guide

  1. Ask which content sources are available (URLs, files, directories, pasted text).
  2. Ask about any known brand attributes, values, or existing guidelines.
  3. Collect the corpus. Pull URLs with WebFetch, locate files with Glob/Read, find public content with WebSearch. Gather website copy, 5-10 blog posts, email campaigns, social posts, sales collateral, and support content. Document each source and its word count.
  4. Confirm corpus size. Require at least 3,000 words across 2+ content types. If smaller, flag the limitation and mark affected findings as lower confidence.
  5. Run the full voice extraction across every dimension in references/voice-dimensions.md, citing source examples per the standards in references/metrics.md.
  6. Present a summary of findings for validation before generating the guide.
  7. Generate the complete brand-voice-guide.md following references/guide-template.md. Verify it against that checklist before delivery.
  8. Offer to review a sample piece of content against the new guide.

Workflow: Review Content

  1. Locate or ask for the brand-voice-guide.md.
  2. Read the content to be reviewed.
  3. Run the review process and produce the scored output defined in references/review-mode.md.
  4. Present findings with actionable, guide-referenced fixes.

Workflow: Update an Existing Guide

  1. Read the current brand-voice-guide.md.
  2. Ingest the new content sources and run extraction on the new material.
  3. Compare findings against the existing guide.
  4. Propose specific updates with rationale.
  5. Apply approved changes with Edit.

Output Standards

  • Primary output: brand-voice-guide.md. For multiple brands: brand-voice-guide-[company-name].md. Deliver review output inline unless a file is requested.
  • Use markdown headers (H1-H4), tables for comparative data, blockquotes for source quotes, code blocks only for literal reproduced text. Bold key terms on first use. No emojis.

Operating Principles

  • Never fabricate examples. Every quoted example must come from actual source content.
  • Never assert voice attributes without evidence. If the data does not support a conclusion, say so.
  • Present findings as observations, not prescriptions, until the user validates them.
  • Distinguish voice (consistent: who we are) from tone (shifts by context: how we adapt) in every guide.
  • When reviewing, be specific: cite the exact word, phrase, or structure and the guide section it touches.
  • Treat the guide as a living document and defer to the user's judgment on subjective calls.