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 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
---
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
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.