openagent-eval is an open-source command-line framework designed for evaluating Retrieval-Augmented Generation (RAG) systems and AI agents. It provides tools and metrics for assessing LLM-based workflows, making it useful for AI researchers and developers who need to benchmark and analyze agent performance.
In the LLM eval & observability space, openagent-eval takes a focused approach. It focuses on evaluating the performance and effectiveness of RAG systems and AI agents efficiently. It is built as an open-source project for AI researchers and developers. The project is open source (Apache-2.0). It runs on the command line.
OpenAgentHQ builds and maintains openagent-eval, and it first shipped in 2026. Development happens publicly on GitHub with 67 commits in the last 90 days. Key capabilities include CLI interface, RAG evaluation, and agent benchmarking.
Summary written by a language model from the project’s public pages.
What PulseGate has recorded for this listing
Closest matches by what these projects do