
emotional-design
How the AI responds to user frustration, confusion, delight, and distress.
- Installs
- 292
- Last 24h
- —
- Trending rank
- —
- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/owl-listener/ai-design-skills --skill emotional-design- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads emotional-design automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
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
FAQ
What does the emotional-design skill do?
How the AI responds to user frustration, confusion, delight, and distress.
How do I install emotional-design?
Run npx skills add https://github.com/owl-listener/ai-design-skills --skill emotional-design in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/emotional-design/ (personal) or .claude/skills/emotional-design/ (project).
Which AI agents can use emotional-design?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is emotional-design safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains emotional-design?
It is published by owl-listener in owl-listener/ai-design-skills. It has 292 recorded installs.
More from owl-listener/ai-design-skills
system-prompt-structure
owl-listener/ai-design-skills
Anatomy of effective system prompts — role, context, constraints, format.
guardrail-design
owl-listener/ai-design-skills
Defining behavioral boundaries — what the AI should and shouldn't do.
constraint-specification
owl-listener/ai-design-skills
Defining output format, length, tone, and content boundaries within prompts.
generative-ui
owl-listener/ai-design-skills
Designing interfaces where AI generates UI components dynamically.
conversation-patterns
owl-listener/ai-design-skills
Turn-taking, repair sequences, grounding, and dialogue structure for human-AI interaction.
progressive-disclosure
owl-listener/ai-design-skills
Revealing AI capability gradually to match user mental models.
Popular other skills
hyperframes-cli
heygen-com/hyperframes
The HyperFrames CLI by job - scaffold, check, look at frames, edit the timeline, preview, render locally or in the cloud, publish, project history - plus reading its JSON and recovering from build or render failures.
triage
mattpocock/skills
Move issues and external PRs through a state machine of triage roles, categorise, verify, grill if needed, and write agent-ready briefs.
ask-matt
mattpocock/skills
Ask which skill or flow fits your situation. A router over the skills in this repo.
to-questionnaire
mattpocock/skills
Turn a decision you can't fully answer into a questionnaire for someone else to fill in.
loop-me
mattpocock/skills
Grill me about specs for the workflows I want to build, within this workspace.