Generates targeted 2-4 option questions to clarify ambiguous user intent in conversations.
npx skills add https://github.com/oathgames/Merlin --skill clarify-intent
Please help me install this Agent Skill. Skill: clarify-intent Source: https://github.com/oathgames/Merlin/tree/main/.claude/skills/clarify-intent Command: npx skills add https://github.com/oathgames/Merlin --skill clarify-intent
Clarify Intent helps resolve ambiguous user requests by asking concise, targeted questions to accurately identify user needs.
When the user’s request is ambiguous, ask a 2–4 option question to clarify their intent before proceeding.
High-intent search queries and answers about installing and using this skill.
To disambiguate vague user requests in conversational AI, you can prompt the user with 2-4 targeted multiple-choice questions based on context analysis. This accurately identifies specific user intent and preferred actions before execution, minimizing errors in skill selection.
You should ask clarifying questions to resolve user intent whenever a user issues a vague or high-stakes command. Prompting for disambiguation before proceeding ensures the correct action is taken and reduces the risk of misinterpreting unclear conversational requests.
To prevent errors when executing ambiguous conversational commands, generate 2-4 option questions to determine specific user intent. By clarifying the preferred action beforehand, you minimize misinterpretation and ensure the correct skill is selected and executed accurately.
Yes, clarifying user intent works for high-stakes conversational commands by asking concise, targeted multiple-choice questions. This disambiguation process analyzes the context of the request to accurately identify user needs and prevent critical execution errors.
The best way to structure clarification questions for conversational AI is to provide 2-4 specific options for the user to choose from. This targeted approach directly addresses the ambiguity in the request, allowing you to determine the exact preferred action efficiently.
udsy19Guide users through structured interviews to clarify underspecified requirements.
jinzhezenggroupRoute ASE atomistic-workflow requests to task-specific subskills by intent.
kolife01Restore AI agent session memory from existing context data.
887Generate brief, high-signal responses to user queries.
