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/conversation-patterns

Turn-taking, repair sequences, grounding, and dialogue structure for human-AI interaction.

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ai-design-skills
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$ npx -y skills add owl-listener/ai-design-skills --skill conversation-patterns --agent claude-code

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  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/conversation-patterns

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Turn-taking, repair sequences, grounding, and dialogue structure for human-AI interaction.

SKILL.md

conversation-patterns.SKILL.md
name: conversation-patterns
description: Turn-taking, repair sequences, grounding, and dialogue structure for human-AI interaction.

Conversation Patterns

Conversation between humans and AI follows predictable structural patterns. Designing these deliberately — rather than leaving them to model defaults — is core interaction design work.

Turn-Taking Structure

Every human-AI conversation has a rhythm. The designer decides:

  • **Turn length**: Short exchanges (chatbot-style) vs. long-form (essay generation). Match turn length to task complexity.
  • **Turn initiation**: Who speaks first? Does the AI greet, or wait? Does it ask a clarifying question before acting?
  • **Turn boundaries**: How does the user signal "I'm done"? How does the AI signal "I need more"?

Repair Sequences

Conversations break down. Repair is how they recover:

  • **Self-repair**: The AI detects its own error and corrects ("Actually, let me revise that...")
  • **Other-repair**: The user corrects the AI ("No, I meant the other one")
  • **Clarification requests**: The AI asks for disambiguation before proceeding
  • **Graceful misunderstanding**: The AI acknowledges confusion without frustrating the user

Design repair sequences explicitly. Don't rely on the model to improvise them.

Grounding

Grounding is how participants establish shared understanding:

  • **Confirmation**: "Just to confirm, you want me to..."
  • **Summarisation**: "So far we've covered X, Y, and Z"
  • **Reference resolution**: Handling pronouns, anaphora, and ambiguous references
  • **Context anchoring**: Reminding the user what the AI knows and doesn't know

Dialogue Structure Patterns

Common structural patterns for human-AI conversation:

  • **Interview**: AI asks questions, user answers, AI synthesises
  • **Co-creation**: Turn-by-turn collaborative building
  • **Instruction-execution**: User gives command, AI performs, user evaluates
  • **Exploration**: Open-ended back-and-forth to discover possibilities
  • **Guided workflow**: AI leads the user through a multi-step process

Choose the pattern that matches the task. Don't default to instruction-execution for everything.

Design Artefacts

  • Conversation flow diagrams showing turn sequences
  • Repair protocol specifications
  • Grounding checkpoints mapped to conversation stages
  • Turn-taking rules per interaction context
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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.

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