conversation-patterns

Installation
SKILL.md

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
Installs
126
GitHub Stars
137
First Seen
Jun 2, 2026
conversation-patterns — owl-listener/ai-design-skills