Reverse-engineer and codify brand voice
brand-voice-analyzerskillsetup L1★135
OneWave-AI/claude-skills ↗Causal-lift measurements
brand-voice-management-4pp vs no-skill baselinewith-skill 96% · baseline 100%
Measured by running the task with and without this artifact, K=5, graded by deterministic checks — no LLM judging.
What it does
Extract and codify a brand's voice from content samples across channels
Best for
When you need to codify how a company actually sounds so new writers can match the voice consistently.
Inputs
- · Website copy, blog posts, emails, social media, sales collateral (3,000+ words minimum)
- · Multiple content channels (2+ types)
Outputs
- · Brand voice guide (markdown)
- · Voice extraction across 7 tone dimensions
- · Vocabulary inventory (power words, jargon, taboo terms)
- · Signature phrases and sentence structures
Preconditions
- · 3,000+ word corpus across 2+ channels exists
- · Content is from real company output
Failure modes
- · Corpus is too small (<1,000 words) — findings lack confidence
- · Only analyzes one channel (incomplete picture)
- · Confuses brand voice with business messaging
Trust signals
- · Phase 1-4 workflow (collection → extraction → triage → review)
- · 7-dimension tone spectrum (formality, humor, confidence, warmth, complexity, energy, irreverence)
- · Vocabulary patterns (power words, filler, taboo, jargon, signatures)
- · Sentence structure analysis with examples