voice-dna

name	voice-dna
description	Discovers voice patterns from the InTheWake content corpus. Measures rhythm, vocabulary, and experiential fingerprints across port guides, ship profiles, logbook entries, and restaurant pages — data-driven voice profiling that feeds like-a-human and voice-audit.
version	2.0.0

Voice DNA — Voice Discovery from the Cruise Corpus

Don't guess the voice. Measure it.

Purpose

like-a-human enforces the voice. voice-audit checks the voice. voice-dna discovers the voice by measuring the actual InTheWake corpus. Run it to extract real patterns so the other voice skills are calibrated against this site's prose, not against a generic "travel writing" abstraction.

The cruise voice is not the sermon voice. It is the voice of a steady observer who has actually sailed the route, walked off the pier, paid the price, and reports back without marketing varnish. Measurement protects that voice from drift.

When to Fire

• On /voice-dna command
• When establishing voice for a new content type (e.g., a new ship line, a new port region, accessibility content)
• When a reviewer reports voice has drifted toward generic travel-blog
• After every 50 new published pages, to refresh the baseline

Sample Selection

Select 12–18 pages that represent the voice at its best. Mix:

• 3–4 gold-standard port pages (e.g., dubai.html, juneau.html) — the voice anchor.
• 2–3 ship profiles with strong logbook entries (Royal, Carnival, NCL, Virgin, MSC — mix lines so vocabulary doesn't skew to one fleet).
• 2–3 restaurant/venue pages that handle real food and real prices.
• 2 accessibility or solo/grief pages (vulnerable-audience voice; pastoral guardrails active).
• 2 article/logbook entries with first-person attestation.
• 1–2 tool/calculator descriptions (they have a different voice; measure the difference deliberately).

Avoid: thin port stubs, scraped ship-spec tables, anything flagged by voice-audit as High risk.

Pattern Extraction

For each sample, measure:

Sentence Rhythm

• Average sentence length (words)
• Sentence length variance — high variance = human; low variance = AI
• Shortest sentence in a confidence-building moment ("You will see whales.")
• Longest sentence in narrative or sensory passages
• Fragment frequency per page

Paragraph Structure

• Average paragraph length
• One-sentence paragraph frequency
• Length variance across a page (uniform = AI; varied = human)
• Position of first paragraph break (early = scannable; late = essay-style)

Vocabulary Fingerprint

• Most frequent concrete nouns (deck names, port features, ship names, price terms)
• Cruise terminology preferences ("tender" vs. "shuttle boat"; "specialty dining" vs. "upscale restaurant")
• First-person attestation density ("I sailed," "we tendered," "my wife and I") per page
• Limitation acknowledgements per page ("I haven't done X," "I can't speak to Y")
• Words used that AI would not choose unprompted
• Cruise-marketing vocabulary that should be absent ("world-class," "stunning," "luxurious," "elevate," "unforgettable," "pristine")

Experiential Texture

• Sensory detail frequency (smell, sound, temperature, footing, queue length, wait time)
• Specific-number density (deck numbers, dollar figures, distances, minutes)
• Named-real-people frequency (crew members, fellow passengers, family members) per page
• Negative/critical content frequency (honest weaknesses) per page
• "From the pier" specificity (what you actually see when you step off)

Cadence Patterns

• Compression-release frequency (stacked short → one longer reflective sentence)
• Anaphora instances (repeated sentence starts) per page
• Pause-and-pivot moves (em-dash, semicolon used for breath, not decoration)
• Direct reader address frequency ("if you're nervous," "you owe no one your story")
• Questions asked per page (cruise voice asks fewer than sermon voice; measure)

Structural DNA

• Average page length (words)
• Number of major sections per page
• Opening pattern (orientation? attestation? warning?)
• Closing pattern (logbook signoff? practical checklist? pastoral note?)
• Image-to-prose ratio
• Schema/data-block density (should be low in body prose, contained in headers/sidebars)

Profile Output

Produce a Voice DNA Profile:

## Voice DNA Profile — InTheWake — [date]
**Corpus:** [N] pages analyzed
**Baseline pages:** [list]

### Rhythm
- Avg sentence: [N] words (σ=[N])
- Shortest at confidence moment: [N] words
- Fragment frequency: [N] per page
- Paragraph variance: [high/medium/low]

### Vocabulary
- Top concrete nouns: [list with frequency]
- First-person attestation: [N] instances per page avg
- Limitation acknowledgements: [N] per page avg
- Banned vocabulary appearances: [should be 0]
- Signature phrases: [list of 5–10 phrases unique to this corpus]

### Experiential
- Sensory details: [N] per page
- Specific numbers (decks/$/min): [N] per page
- Named real people: [N] per page
- "From the pier" specificity: [N] per page

### Cadence
- Compression-release: [N] per page avg
- Anaphora: [N] per page avg
- Em-dash for breath: [N] per page avg
- Direct reader address: [N] per page avg

### Structure
- Avg length: [N] words
- Sections: [N] avg
- Opening pattern: [orientation / attestation / warning / scene]
- Closing pattern: [logbook signoff / checklist / pastoral note]

Different Voice Profiles Within the Site

The same site has several voices; measure them separately so they don't bleed into each other:

• Logbook voice — first-person attested, dated, specific. The anchor.
• Port-guide voice — second-person guidance + first-person attestation; calmer than the logbook.
• Ship-profile voice — less first-person; more steady-observer; specs in tables, personality in prose.
• Restaurant/venue voice — sensory-forward; honest about value; price-anchored.
• Accessibility / solo / grief voice — pastoral guardrails. Slower cadence. Direct address. "Someone thought about me."
• Tool / calculator voice — terse, instructional, no marketing.

A voice-dna run can extract any one of these from the right sample subset.

Feeding Other Skills

The Voice DNA Profile feeds:

• like-a-human — update measured patterns, replace guesses with numbers.
• voice-audit — calibrate Low/Medium/High thresholds against this corpus.
• port-page-generator and venue-page-writer — these generators sample the profile to stay on-voice.
• emotional-hook-test — confirms the measured voice still produces the target feeling.

Encode to Memory

python3 /home/user/ken/orchestrator/memory_ops.py encode inthewake pattern \
  "Voice DNA: avg sentence 16 words, σ=9. Sensory details 4.2/page. First-person attestation 1.8/page. Banned vocab: world-class, stunning, luxurious, elevate, unforgettable, pristine." \
  --tags voice-dna,voice-profile,baseline --protected

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The reader can tell a sailor from a brochure inside a paragraph. Measure what makes the difference.