Assessment Intelligence

Enables classical test theory analysis, differential item functioning, local item dependence detection, and standard setting through MCP tools.

Enables AI hosts to perform reproducible psychometric and statistical analyses through constrained, schema-validated tools such as item analysis, Rasch modeling, descriptive statistics, and correlation matrices, without exposing arbitrary R or shell execution.

Enables local evaluation and revision comparison of how audience attention, curiosity, surprise, understanding, fatigue and mixed emotions evolve through a creative work, based on time-ordered cue annotations rather than automatic media analysis. Also exposes audience-panel weighting, sensitivity checks, dataset inspection, calibration fitting/application and parameter tuning, all computed from supplied objects without external calls.

Enables natural language analysis of mechanical test data files (CSV, TDMS, MDF) by providing tools for channel statistics, spectrum analysis, rainflow fatigue counting, thermal state detection, and report generation.