Arklex vs OpenAgent Eval

Arklex evaluates AI agents with simulated multi-turn conversations, helping teams check how agents respond across scenarios. Its open-source ArkSim framework creates synthetic users with different profiles, goals, and knowledge levels, then assesses responses using built-in measures for helpfulness, coherence, relevance, faithfulness, verbosity, goal completion, and agent behavior failures. Teams can add reusable custom metrics in plain language, review and dispute judge scores, and add human assessments while preserving the original scores. Calibration tracks agreement by metric. Reusable scenarios support comparisons between agent versions and regression checks; ArkSim can also act as a CI quality gate, returning a non-zero result when thresholds are not met. Agents connect through Python classes, Chat Completions HTTP endpoints, or the A2A protocol. The hosted Arklex Platform adds a UI for scenarios, conversations, and scoring. ArkSim is free and open source under Apache-2.0. Its documentation requires Python 3.10 through 3.13 and an API key from OpenAI, Anthropic, or Google; OpenAI is the default provider.

OpenAgent Eval has no write-up on Specifiction yet; its figures are above.