Clarification

Generate targeted clarification questions for low-confidence intent routing.

2|Updated Apr 19, 2026

Search Tags:#routing #localization #clarification #confidence #fallback #intent

Ready to run

npx skills add https://github.com/reaatech/agent-mesh --skill clarification-reaatech

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: Clarification
Source: https://github.com/reaatech/agent-mesh/tree/main/skills/clarification
Command: npx skills add https://github.com/reaatech/agent-mesh --skill clarification-reaatech

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

When the classifier runs with low confidence, this skill generates targeted clarifying questions to refine user intent and improve routing accuracy.

Core Features & Use Cases

Generates concise clarification questions when intent is ambiguous or confidence is low.
Caches and reuses clarification results for identical inputs and agents to reduce latency.
Provides language-aware fallback questions and structured processing through a defined toolset (generate_clarification_question, process_clarification_response, get_fallback_question).
Ensures safe prompts and output validation to prevent prompt injection or unsafe responses.

Quick Start

Use the Clarification skill by invoking the generate_clarification_question tool with parameters agent_name, user_input, detected_language, and intent_summary to obtain a clarifying question.

Frequently Asked Questions about Clarification

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I handle low-confidence intent routing in a multi-agent system?▼

Low-confidence intent routing is handled by generating targeted clarifying questions to refine ambiguous user inputs, improving classifier accuracy and directing queries to the correct agent.

How do I generate clarifying questions for ambiguous user intent?▼

To generate clarifying questions, invoke the generate_clarification_question tool with parameters including agent_name, user_input, detected_language, and intent_summary to produce a concise query for the user.

Can I cache clarification questions to reduce latency for identical inputs?▼

Yes, you can cache clarification results to reduce latency, as the system caches and reuses clarification outputs for identical user inputs and agents to optimize routing performance.

Does intent clarification support localization and fallback across multiple languages?▼

Intent clarification supports localization by providing language-aware fallback questions and structured processing, ensuring robust fallback behavior across multiple detected languages.

What are the limitations of using automated clarification for intent routing?▼

Automated clarification requires safe prompts and output validation to prevent prompt injection, and relies on structured toolsets, meaning poorly validated inputs or missing fallback policies can limit its effectiveness.