conversational-refinement
CommunityRefine uncertainty via natural dialogue.
Authordrhayf
Version1.0.0
Installs0
System Documentation
What problem does it solve?
When data is uncertain or incomplete, this pattern guides the system to refine understanding through natural dialogue instead of direct questioning, reducing ambiguity and improving reliability.
Core Features & Use Cases
- Pattern-driven conversational refinement for LLMs, including uncertainty declarations, hypothesis tracking, and probe-driven evidence gathering.
- Supports an end-to-end lifecycle: from uncertainty declaration to probe generation, session management, and final confirmation.
- Use Case: Deploy this pattern to resolve ambiguous user intents or missing factual data within an autonomous module, by engaging in controlled dialogue and logging evidence.
Quick Start
Start a conversational refinement session to collect uncertain data and resolve open hypotheses.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: conversational-refinement Download link: https://github.com/drhayf/GUTTERS/archive/main.zip#conversational-refinement Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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