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Ambiguity Detection Skill

Detect ambiguous user input and determine if clarification is needed.

2|1|Updated Apr 19, 2026
Search Tags:#clarification#ambiguity#reasoning#nlp#disambiguation#input-analysis
One-click install
npx skills add https://github.com/reaatech/agents-md-kit --skill ambiguity-detection-skill
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: Ambiguity Detection Skill
Source: https://github.com/reaatech/agents-md-kit/tree/main/examples/classifier/skills/ambiguity-detection
Command: npx skills add https://github.com/reaatech/agents-md-kit --skill ambiguity-detection-skill

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Detects ambiguous or unclear input that may require clarification before processing, helping ensure correct interpretation and reduce miscommunication.

Core Features & Use Cases

  • Ambiguity detection in user input and generation of clarifying questions.
  • Confidence scoring and rationales to guide decisions.
  • Use Case: in chatbots, automatically flag vague requests and prompt for specifics.

Quick Start

Provide a short user message and optional context, and receive an is_ambiguous flag, a confidence score, and suggested clarifications.

Frequently Asked Questions about Ambiguity Detection Skill

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

FAQPage Schema
How do I detect ambiguous input in natural language prompts before processing?▼

Ambiguity detection works by analyzing user messages and optional context to return an ambiguity flag, confidence score, and rationale. It evaluates natural language prompts to determine if clarification is needed before taking action.

How do I automatically generate clarifying questions for vague chatbot requests?▼

Generate clarifying questions by flagging vague requests and returning a needs_clarification flag with suggested clarifications. This prompts users for specifics when ambiguous input is detected in chatbot interactions.

Can I use context to improve disambiguation across different domains?▼

You can improve disambiguation by providing optional context alongside user text. The analysis applies across domains to general natural language prompts and structured requests, using context to enhance interpretation accuracy.

What is the best way to score confidence for ambiguous input detection?▼

Score confidence for ambiguous input by analyzing text and optional context to return a numerical score with supporting reasons. This confidence scoring guides decisions on whether clarification is necessary before processing.

Do I need any external dependencies to perform input-analysis for ambiguity?▼

You do not need external dependencies to perform input-analysis for ambiguity. The skill operates independently to analyze text and optional context, returning ambiguity flags and clarification suggestions without additional components.

When should I not use automated disambiguation for user messages?▼

Avoid automated disambiguation when user messages are highly specific or when the domain requires immediate action without clarification. The skill targets detecting unclear input where miscommunication risks exist.

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