Classify user requirements as Skill or Agent and output metadata YAML.
npx skills add https://github.com/khw1031/ai-library --skill create-ai-tool-khw1031
Please help me install this Agent Skill. Skill: create-ai-tool Source: https://github.com/khw1031/ai-library/tree/main/.claude/skills/create-ai-tool Command: npx skills add https://github.com/khw1031/ai-library --skill create-ai-tool-khw1031
It helps analysts determine the correct AI tool type (Skill or Agent) for a given requirement and guides the user to the appropriate creation path.
Analyze a user request to determine whether to create a Skill or an Agent, then direct to the appropriate creation path.
High-intent search queries and answers about installing and using this skill.
To decide between an AI Skill or an Agent, you classify user requirements using a decision tree that validates prompt metadata and outputs a structured YAML guiding the creation path.
The difference between a Skill and an Agent in prompt engineering depends on tool type classification, where Skills handle specific guided tasks and Agents manage broader autonomous workflows based on requirement analysis.
To validate required metadata when designing an AI tool prompt, check the SKILL.md file for the presence of a name and description, evaluate optional components, and output a structured metadata YAML.
Yes, you can use a decision tree to classify AI tooling requests by analyzing user specifications for what to build and how it should be invoked, routing them to the correct creation path.
The best way to structure metadata for an AI creation tool is to generate a structured metadata YAML after validating the presence of required name and description fields alongside optional components.
You should not use a Skill for your AI workflow design when the user requirement classification process determines the request involves autonomous decision-making, routing it to the Agent creation path instead.
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