conversation-patterns
Turn-taking, repair sequences, grounding, and dialogue structure for human-AI interaction.
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- 328
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/owl-listener/ai-design-skills --skill conversation-patterns- 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 conversation-patterns 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.
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
FAQ
What does the conversation-patterns skill do?
Turn-taking, repair sequences, grounding, and dialogue structure for human-AI interaction.
How do I install conversation-patterns?
Run npx skills add https://github.com/owl-listener/ai-design-skills --skill conversation-patterns 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/conversation-patterns/ (personal) or .claude/skills/conversation-patterns/ (project).
Which AI agents can use conversation-patterns?
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 conversation-patterns 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 conversation-patterns?
It is published by owl-listener in owl-listener/ai-design-skills. It has 328 recorded installs.
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