bias-detection-design
Designing review workflows to surface and mitigate bias in AI outputs.
Turn-taking, repair sequences, grounding, and dialogue structure for human-AI interaction.
$ npx -y skills add owl-listener/ai-design-skills --skill conversation-patterns --agent claude-codeHow it fires
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/conversation-patternsContext preview
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Turn-taking, repair sequences, grounding, and dialogue structure for human-AI interaction.
name: conversation-patterns description: Turn-taking, repair sequences, grounding, and dialogue structure for human-AI interaction.
Conversation between humans and AI follows predictable structural patterns. Designing these deliberately — rather than leaving them to model defaults — is core interaction design work.
Every human-AI conversation has a rhythm. The designer decides:
Conversations break down. Repair is how they recover:
Design repair sequences explicitly. Don't rely on the model to improvise them.
Grounding is how participants establish shared understanding:
Common structural patterns for human-AI conversation:
Choose the pattern that matches the task. Don't default to instruction-execution for everything.
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.