Method and System for Output Presentation for Large Language Models and Agents

A computer-implemented method for screening and scoring outputs generated by artificial intelligence language models, the method comprising:

• receiving, by a screening system, a generated output generated by an artificial intelligence language model in response to a user query;
• analyzing the output using a plurality of detection engines, wherein each detection engine evaluates a different error dimension, detecting one or more detected errors;
• for each detected error of the one or more detected errors, classifying the detected error into a severity level selected from a plurality of predefined severity levels;
• generating a color-coded visual indicator that corresponds to a highest severity level among the one or more detected errors, wherein different colors represent different severity levels;
• and
• generating remediation guidance configured to remediate at least one detected error of the one or more detected errors;
• and
• presenting, to the user, screening results comprising:
• the color-coded visual indicator;
• a list of the one or more detected errors with their respective severity levels and locations;
• and
• the remediation guidance.