request-analyzer_skill

Overview

This skill proactively analyzes every incoming user request to determine task type, assess prompt quality, and recommend the most appropriate skills to activate. It acts as an intelligent coordinator that ensures workflows are efficient and that specialized skills (prompt-optimizer, ui-analyzer, react-component-generator, etc.) are used when they add value. The goal is faster, more accurate outcomes with minimal friction for the user.

How this skill works

On each new request the skill scores clarity, specificity, and completeness to identify gaps and potential ambiguities. It classifies the task (code implementation, debugging, design implementation, explanation, etc.) and matches the request against activation criteria for available skills. Based on scores and task type it recommends one of: optimize the prompt, delegate to a specialized skill, proceed directly, or ask clarifying questions. The skill can explicitly state the recommended action and trigger downstream skills when appropriate.

When to use it

• Activate for every incoming user request or at conversation start
• When a user submits a new task, question, or code/design request
• When intent or required deliverables are unclear or underspecified
• For UI/design-related requests or when images/screenshots are provided
• Whenever component-level React work is requested or implied

Best practices

• Always score clarity, specificity, and completeness before acting
• Recommend prompt-optimizer when any quality score is below threshold (≈60–70%)
• Prefer ui-analyzer when screenshots, Figma links, or design language appear
• Use react-component-generator only when component specs are clear or after optimization
• Ask targeted clarifying questions instead of assuming missing details
• Balance proactivity with brevity to avoid interrupting experienced users

Example use cases

• User says "Fix my code" → detect low quality, activate prompt-optimizer to gather missing context
• User attaches a screenshot and asks "Build this" → classify as design implementation and use ui-analyzer
• User requests "Create a React login form with TypeScript" with full specs → activate react-component-generator directly
• User asks a conceptual question (e.g., hooks differences) → proceed directly with explanation
• User gives partial component requirements → suggest prompt-optimizer, then hand off to react-component-generator after refinement