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emotional-design

emotional-design

github.com/owl-listenerDesign & UI191293 installsUpdated 20w ago
Repository

About emotional-design

emotional-design is a skill guide for people designing AI interactions. It covers emotional signals, response strategies, and design artefacts for testing and escalation.

Key features

  1. 01Identify seven emotional states and signals
  2. 02Choose responses for each emotional state
  3. 03Define escalation triggers for high-distress scenarios
  4. 04Create response templates and test scenarios

Use cases

  1. 01Respond to users frustrated or angry with an AI
  2. 02Adapt replies for confused or anxious users
  3. 03Design escalation and support flows for distress

Install

Copy the command and run it in a terminal.

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

After installing, type/emotional-designin Claude Code to confirm it loaded.

Details

From the project README

Emotional Design

Users bring emotions to AI interactions. Frustration when it doesn't work. Delight when it does something unexpected. Distress when dealing with difficult topics. The AI's response to these emotions is a design decision.

Emotional States to Design For

  • Frustration: The AI isn't working, isn't understanding, or is being unhelpful. The user is losing patience.
  • Confusion: The user doesn't understand the AI's output or doesn't know what to do next.
  • Delight: The AI exceeded expectations. The user is pleasantly surprised.
  • Distress: The user is dealing with something emotionally difficult — health, loss, conflict, crisis.
  • Boredom: The AI is too slow, too verbose, or too repetitive.
  • Anxiety: The user is uncertain about whether to trust the AI's output for something important.
  • Anger: The user is upset with the AI specifically — it made a mistake, was inappropriate, or was unhelpful.

Response Strategies

For frustration:

  • Acknowledge the difficulty without being patronising
  • Simplify — offer a more direct path
  • Don't repeat the same failed approach
  • Offer to try a different angle or escalate For confusion:
  • Explain differently, don't just repeat
  • Use examples and analogies
  • Break complex outputs into smaller steps
  • Check understanding before continuing For distress:
  • Increase warmth and reduce formality
  • Don't try to fix the emotion — acknowledge it
  • Provide relevant resources (crisis lines, professional help) when appropriate
  • Slow the pace — don't rush to the next step For delight:
  • Don't overexplain or undercut the moment
  • Build on the momentum
  • Note what worked for future reference For anger at the AI:
  • Acknowledge the mistake without excessive apology
  • Fix the problem rather than explaining why it happened
  • Give the user control to redirect

Emotional Detection Signals

The AI can infer emotion from:

  • Language intensity and word choice
  • Punctuation and formatting (caps, exclamation marks, short sentences)
  • Repetition (asking the same thing multiple times signals frustration)
  • Explicit statements ("I'm confused" / "This is frustrating")
  • Behavioural signals (regeneration, abandonment, rapid-fire inputs)

Design Artefacts

  • Emotional response protocol per emotional state
  • Detection signal inventory
  • Response template library for each emotional context
  • Escalation triggers for high-distress scenarios
  • Emotional design testing scenarios

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