paper-instruments/rubric

A Python library encapsulating best practices for rubric-based evaluation of LLM/VLM outputs using AI judges such as LLMs and decision models.

Deterministic rubric engine for AI response review - weighted criteria, evidence-backed scores, stable rankings, Python and C# runtimes.

Agent-as-a-Judge grading framework for evaluating AI outputs/deliverables

AutoEvals is a tool for quickly and easily evaluating AI model outputs using best practices.

AdaRubric: Adaptive Dynamic Rubric Evaluator for Agent Trajectories

Evaluation for AI outputs against trusted educational rubrics. Measure and improve content quality with research-backed rubrics — ensuring rigor, reliability, and alignment to classroom needs.

Readymade evaluators for your LLM apps

EvalAssist is an open-source project that simplifies using large language models as evaluators (LLM-as-a-Judge) of the output of other large language models by supporting users in iteratively refining evaluation criteria in a web-based user experience.