clavix-improve

To optimize prompts for AI assistants, you need to evaluate them across six dimensions: Clarity, Efficiency, Structure, Completeness, Actionability, and Specificity. Applying targeted improvement patterns to these areas refines prompt quality and produces more accurate LLM outputs.

Prompt quality assessment is the process of analyzing a prompt across six dimensions including Clarity, Completeness, and Actionability. It calculates an initial quality score to determine whether a standard or comprehensive analysis depth is needed for effective prompt refinement.

Improving a vague prompt for code generation involves analyzing its structure and specificity, then applying improvement patterns to ensure it is precise, actionable, and contains all necessary technical details. This yields an enhanced prompt that generates more useful code.

Yes, you can save optimized prompts to a specified directory. The prompt optimization process generates an enhanced prompt and provides the option to save the refined output directly to your local file system for future use.

The choice between comprehensive and standard prompt analysis depends on the prompt's initial quality score. The system intelligently selects comprehensive analysis for lower-scoring prompts that require deeper refinement, while standard analysis handles prompts needing minor adjustments.

LLM output lacks detail when prompts score low in Completeness or Specificity. Assessing your prompt against a six-dimension quality framework identifies missing structural elements and applies refinement patterns to elicit more comprehensive AI responses.