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domain-voice

domain-voice

github.com/owl-listenerAgent workflows191128 installsUpdated 20w ago
Repository

About domain-voice

A design skill for defining how AI should communicate across professional domains. It helps teams specify vocabulary, precision, citation, risk, authority, and ethical boundaries, then document and test those expectations.

Key features

  1. 01Domain voice components
  2. 02Profiles for five professional domains
  3. 03Guidance for designing and testing voice
  4. 04Voice design artefacts

Use cases

  1. 01Define a medical or legal AI persona
  2. 02Create domain vocabulary and guardrails
  3. 03Test voice expectations with practitioners

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/owl-listener/ai-design-skills --skill domain-voice

After installing, type/domain-voicein Claude Code to confirm it loaded.

Details

From the project README

Domain Voice

A coding assistant, a medical advisor, a creative writing partner, and a legal research tool should not sound the same. Domain voice is how you adapt AI behavior to fit the norms, expectations, and requirements of specific professional contexts.

Domain Voice Components

  • Vocabulary: The terminology and jargon appropriate to the domain
  • Precision level: How exact the AI needs to be (legal and medical demand high precision; creative work tolerates ambiguity)
  • Citation norms: Whether and how the AI references sources (academic style, legal citation, informal attribution)
  • Risk tolerance: How cautious the AI should be about uncertain outputs
  • Authority stance: Whether the AI positions itself as expert, assistant, or peer
  • Ethical boundaries: Domain-specific ethical considerations (medical ethics, legal privilege, creative attribution)

Domain Voice Profiles

Medical/Health:

  • High precision, extensive hedging
  • Always recommends professional consultation
  • Careful distinction between information and advice
  • Sensitive to patient dignity and autonomy Legal:
  • Very high precision, formal register
  • Explicit disclaimers about not constituting legal advice
  • Jurisdiction awareness
  • Careful with privileged information Creative:
  • Lower precision, higher expressiveness
  • Encouraging and exploratory tone
  • Comfortable with ambiguity and multiple interpretations
  • Collaborative rather than authoritative Technical/Engineering:
  • High precision, moderate formality
  • Code-aware, specification-oriented
  • Direct and concise
  • Comfortable with technical depth Education:
  • Adaptive precision based on learner level
  • Encouraging and patient
  • Socratic when appropriate
  • Scaffolded explanation style

Designing Domain Voice

  1. Research the domain: Talk to practitioners. Understand their communication norms.
  2. Identify non-negotiables: What must the AI always or never do in this domain?
  3. Map to persona: How does domain voice overlay on the base persona?
  4. Test with practitioners: Domain experts are the best judges of whether the voice feels right.
  5. Document edge cases: Where domain norms conflict with general AI behavior.

Design Artefacts

  • Domain voice profiles per professional context
  • Domain vocabulary guides (terms to use, terms to avoid)
  • Domain-specific guardrail specifications
  • Practitioner testing protocols
  • Domain voice evaluation rubrics

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