Brand Voice Extractor

Quick Start

Extract brand voice for [company]. Use their blog at [url].

Extract brand voice for [client]. Use the content inventory at clients/[client]/research/content-inventory.json.

Inputs

Process

Phase 1: Select Content to Analyze

1. Read the content inventory from

   site-content-catalog

   output
2. Select a diverse sample of 10-20 pages, prioritizing:
   • Blog posts (primary voice indicator)
   • Landing pages (marketing voice)
   • Case studies (storytelling voice)
   • Mix of recent and older content (to detect voice evolution)
   • Mix of topics (to see consistency across subjects)

• 8-10 blog posts (mix of how-to, opinion, product updates)
• 2-3 landing pages (homepage, product page, solutions page)
• 2-3 case studies or customer stories (if available)
• 1-2 comparison/vs pages (if available)

Phase 2: Fetch and Extract Text

1. WebFetch the page
2. Extract the main content body (strip nav, footer, sidebar)
3. Store: title, URL, raw text, word count

Phase 3: Analyze Voice Dimensions

A) Tone

• Formality spectrum: Casual ↔ Professional ↔ Academic
• Emotional register: Excited ↔ Measured ↔ Dry
• Authority stance: Peer/friend ↔ Expert/teacher ↔ Institution
• Humor usage: Frequent ↔ Occasional ↔ None
• Directness: Direct/bold ↔ Hedged/diplomatic

B) Vocabulary & Language

• Reading level: Approximate grade level (simple vs. complex)
• Jargon usage: Heavy industry jargon ↔ Plain language
• Technical depth: Assumes expertise ↔ Explains everything
• Power words: Common persuasion/action words they favor
• Banned patterns: Words or phrases they conspicuously avoid
• Unique vocabulary: Distinctive terms or phrases they use repeatedly

C) Sentence Structure

• Average sentence length: Short/punchy ↔ Long/complex
• Paragraph length: 1-2 sentences ↔ 3-4 ↔ 5+
• Opening patterns: How they start articles (question, stat, story, bold claim)
• Transition style: How they connect ideas
• Use of fragments: Do they use incomplete sentences for emphasis?

D) Formatting Patterns

• Headers: Frequency, style (question-based, how-to, numbered)
• Lists: Bullets vs. numbered, frequency
• Bold/italic: How they use emphasis
• Images/media: Frequency, types (screenshots, illustrations, photos)
• CTAs: Placement, style, frequency, language used
• Pull quotes/callouts: Do they use them?

E) Content Structure

• Typical article length: Short (<800), Medium (800-1500), Long (1500+)
• Introduction style: Hook type, length
• Conclusion style: Summary, CTA, open question
• Use of data/stats: Frequent ↔ Rare
• Use of examples: Frequent ↔ Rare
• Storytelling: Narrative-driven ↔ Information-driven

F) Persona & Audience

• Who they write for: Inferred target reader (role, seniority, industry)
• Assumed knowledge level: Beginner ↔ Intermediate ↔ Expert
• Point of view: First person singular (I) ↔ First person plural (we) ↔ Second person (you) ↔ Third person
• Reader relationship: Peer ↔ Teacher ↔ Service provider

Phase 4: Generate Brand Voice Profile

# Brand Voice Profile: [Company Name]
**Analyzed:** [Date] | **Content pieces analyzed:** [N]
**Sources:** [list of URLs analyzed]

---

## Voice Summary (2-3 sentences)

[Company] writes in a [tone] voice that [description]. Their content targets
[audience] and assumes [knowledge level]. The overall feel is [adjectives].

---

## Tone Profile

| Dimension | Position | Evidence |
|-----------|----------|----------|
| Formality | [e.g., Professional-casual] | [Example quote] |
| Emotional Register | [e.g., Measured, occasionally excited] | [Example] |
| Authority | [e.g., Expert/teacher] | [Example] |
| Humor | [e.g., Rare, dry when used] | [Example] |
| Directness | [e.g., Very direct, bold claims] | [Example] |

---

## Language & Vocabulary

### Reading Level
[Grade level estimate and what that means]

### Signature Phrases
- "[phrase 1]" — used frequently to [purpose]
- "[phrase 2]" — recurring pattern in [context]

### Jargon & Technical Depth
[How much industry jargon they use, how they handle technical concepts]

### Words They Love
[List of frequently used power words, adjectives, verbs]

### Words They Avoid
[Notable absences or patterns they steer away from]

---

## Structure & Formatting

### Typical Article Structure
[Outline of how their articles are typically organized]

### Sentence & Paragraph Style
- Average sentence length: [X words]
- Typical paragraph: [X sentences]
- Notable patterns: [fragments, rhetorical questions, etc.]

### Formatting Habits
- Headers: [style]
- Lists: [frequency and style]
- Emphasis: [bold/italic patterns]
- CTAs: [where, how often, what language]

---

## Audience & Persona

### Target Reader
[Role, seniority, industry, pain points they address]

### Knowledge Assumptions
[What they assume the reader already knows]

### Point of View
[I/we/you usage and what it signals]

---

## Writing Guidelines (Actionable)

Use these guidelines when writing content, outreach, or campaigns for [Company]:

### Do
- [Guideline 1 with example]
- [Guideline 2 with example]
- [Guideline 3 with example]

### Don't
- [Anti-pattern 1]
- [Anti-pattern 2]
- [Anti-pattern 3]

### Voice Samples

**Their style:**
> [2-3 representative quotes from their content that exemplify the voice]

**How to match it:**
> [2-3 example sentences written in their voice about a neutral topic]

Tips

• 15 pages is the sweet spot. Fewer than 10 won't capture enough variation. More than 25 adds cost without much signal.
• Blog posts are the best voice signal. Landing pages are more formulaic. Blog posts show the authentic voice.
• Look for consistency AND inconsistency. If their tone shifts dramatically between content types, note it — they may have multiple voice modes.
• Check for ghost-written content. If some posts feel dramatically different, they may use external writers. Flag this in the analysis.
• This skill has no code script. It's an agent-executed skill — the AI agent reads the content via WebFetch and performs the analysis directly. The structured output template above guides the analysis.

Dependencies

• Web fetch capability (for reading content pages)
• Optional:

  site-content-catalog

  output (for selecting which content to analyze)
• No API keys or paid tools required