Scorer

The Scorer block leverages the power of LLM to assign a numerical score to an input based on specific criteria.

I/O	Feature	Type	Simple Explanation
input	`item`	string	The subject, entity, or text that needs to be scored.
input	`criteria`	string	The description of rules or scoring criteria used for evaluation.
input	`include_justification` (optional)	boolean	When enabled, the model returns reasoning for the evaluated score.
output	`score`	number	Reflects the assessment based on the provided criteria.
output	`justification` (optional)	string	Detailed explanation for the score if justification is enabled.

Consider how this block can enhance decision-making in various contexts:

Comparing Products: If you run an e-commerce site and want to rate various products for customers, this block can evaluate them based on parameters like price, quality, and user reviews.
Content Quality Review: For content creators assessing their blog articles or videos, using defined quality metrics will help quantify effectiveness and engagement levels.
Decision-Making Based on Standards: Organizations can utilize numerical scores from employee performance evaluations by applying consistent scoring criteria for better transparency in promotions and raises.
Record-Keeping Purposes: In academic settings or compliance-related fields, generate justifications that accompany assessments which aid in understanding decisions made over time.

In summary, whenever there’s a necessity to assess items against defined standards quantitatively, the Scorer block serves as a critical tool!