CurveAhoead/ScoreRune

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

A Python library for LLM-based evaluation using weighted rubrics.

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

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

OpenJudge: A Unified Framework for Holistic Evaluation and Quality Rewards

Typed prompt-and-judge SDK, CLI, and evidence viewer for agent evaluations

Skills that guide AI coding agents to help you build product-specific AI evals.

Open-source AI evals toolkit: skills that guide AI coding agents to write eval rubrics, eval datasets (User Input Grid), trace codes, code evaluators and LLM-as-a-judge prompts. From the Reforge AI Evals course by Calibre.

AdaRubric: Adaptive Dynamic Rubric Evaluator for Agent Trajectories