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conversation-patterns

@owl-listener · 收录于 5 天前 · 上游提交 1 个月前

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

场景对话设计交互优化ai对话

适合你，如果你在构建或优化AI对话系统的交互流程。

/ 下载安装
https://github.com/owl-listener/ai-design-skills/tree/main/claude-plugin/model-interaction-design/skills/conversation-patterns ↗
/ 通过 npx 安装 校验哈希
npx oh-my-skill add owl-listener/ai-design-skills/conversation-patterns
/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- owl-listener/ai-design-skills/conversation-patterns
/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify owl-listener/ai-design-skills/conversation-patterns
安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。
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~460上下文体积 · 单文件
索引托管

怎么用

商店整理自技能原文 · 版本 f41b650 · 表述以原文为准
它做什么

装上后，Claude会按照预设的对话规则与你互动：主动确认需求，在误解时澄清或纠正自己，并结构化地推进对话。

什么时候触发

当你与Claude开始对话时，这些模式会自动生效，管理对话的轮换、修复和理解。

装好后可以这样说
触发确认机制
触发修复序列
触发总结
技能原文 SKILL.md作者撰写 · MIT · f41b650

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
按 MIT 许可原样转载,未经改动 · 在 GitHub 查看 →

评论

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