Open source agent-evaluation projects

Every project in the registry tagged agent-evaluation, ranked by real GitHub adoption.

projects 4 combined stars ★ 28K refresh nightly
01 iFixAi ★ 15K

Independent Auditing of AI Agents. Run by human or the agent itself, to answer the most crucial question in the AI Agent Economy. Is the agent doing what is sup

last push42 hours ago languagePython licenseApache-2.0
02 giskard-oss ★ 5.8K

🐢 Open-Source Evaluation & Testing library for LLM Agents

last pushyesterday languagePython licenseApache-2.0
03 coze-loop ★ 5.7K

Next-generation AI Agent Optimization Platform: Cozeloop addresses challenges in AI agent development by providing full-lifecycle management capabilities from d

last push2 hours ago languageGo licenseApache-2.0
04 pandaprobe ★ 787

open source agent engineering platform: traces, evals, and metrics to debug and improve your AI agents. Integrates with LangGraph, CrewAI, Claude Agent SDK, and

last push23 days ago languagePython licenseApache-2.0

← all tags

Frequently asked questions

How many open source agent-evaluation projects are there?

This registry tracks 4 projects tagged agent-evaluation, with 27,713 GitHub stars between them. The most-adopted is iFixAi at 15,364 stars.

Are these agent-evaluation projects free to use?

Yes — 4 of the 4 carry an explicit open-source licence across 1 distinct licence, so there is no licence fee. Where a project also sells a hosted or enterprise version, the self-hosted path remains free.

Which agent-evaluation project should I choose?

The list above is ranked by GitHub stars, but stars measure attention rather than fit. Check three things on each card: the licence (permissive versus copyleft), the language it is written in, and the last-push date — a high-star project that has not been pushed in a year is a liability.

Are these agent-evaluation projects still maintained?

4 of the 4 were pushed in the last 90 days, and every card shows its exact last-push date so you can see the rest. Sort your shortlist by that date before committing to a migration.