bias-detection-design
Designing review workflows to surface and mitigate bias in AI outputs.
Defining AI character, voice, and personality traits.
$ npx -y skills add owl-listener/ai-design-skills --skill persona-architecture --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/persona-architectureContext preview
The summary Claude sees to decide when to auto-load this skill.
Defining AI character, voice, and personality traits.
name: persona-architecture description: Defining AI character, voice, and personality traits.
An AI persona is not a gimmick. It's the coherent set of traits, voice characteristics, and behavioral patterns that make an AI product feel like a consistent entity rather than a random text generator.
Start with the product's purpose and user needs, not with "wouldn't it be fun if the AI was sassy": 1. **Who are the users?** Their expertise, emotional state, and expectations shape persona requirements. 2. **What's the task?** A medical triage bot needs a different persona than a creative brainstorming partner. 3. **What relationship serves the user?** Sometimes authority builds trust. Sometimes equality builds rapport. 4. **What's the brand?** The AI persona must align with the organisation's broader identity. 5. **What are the risks?** An overly casual persona in a serious context causes harm. An overly formal persona in a creative context stifles use.
A persona specification should include:
Part of the Designer Skills suite. Install this collection and four more with one command in Claude Code: /plugin marketplace add Owl-Listener/designer-skills This repo still works on its own. The suite just gives everyone one front door.
Designing review workflows to surface and mitigate bias in AI outputs.
Designing for informed user consent, opt-out, and human override.
When and how AI should escalate to humans, refuse, or ask for clarification.
Defining behavioral boundaries — what the AI should and shouldn't do.
Proactively identifying failure modes, misuse, and unintended consequences.
Showing users what the AI knows, doesn't know, and how confident it is.