Binary evals, trace-centric, error-analysis-first CLI for LLM evaluation. Built on Hamel Husain's principles.

LLM eval & testing toolkit

GitHub Action for evaluating MCP server tool calls using LLM-based scoring

Local React report UI for vitest-evals JSON artifacts.

Harness-backed AI testing on top of Vitest.

No description provided.

Shared primitives, schemas, and report collection helpers for vitest-evals.

A library for running evaluations for AI use cases

Test your LLM-powered apps with a TypeScript-native, Vitest-based eval runner. No API key required.

Rulvar evals: eval cases, golden outputs, rubric and judge graders, matrix sweeps, canary fingerprint.

List of binary file extensions

Check if a file path is a binary file

Much like tests in traditional software, evals are an important part of bringing LLM applications to production. The goal of this package is to help provide a starting point for you to write evals for your LLM applications, from which you can write more c

Harness AI Evals Service APIs integrated with react hooks

AI SDK harness adapter for vitest-evals.

Managed Deep Agents — the `defineDeepAgent` authoring interface plus the CLI that compiles and deploys a code-first Deep Agent repository to a managed LangGraph runtime.

The linux x64 distribution of the Sentry CLI binary.

Experimental replay and scoring kit for Relay executions

Helper function to build binary assignment operator visitors

CLI for installing qq-radio skills into Codex, Claude, and Cursor on Windows.