What are the best tools for testing AI agents?
Short answer
There is no single best tool, because agent testing has several distinct jobs. For evaluation you have frameworks like Promptfoo, DeepEval, LangSmith, and Braintrust. For observability, Langfuse, Phoenix, and Helicone. For safety, OWASP's LLM Top 10 plus tools like garak, PyRIT, and Guardrails AI. For capability comparison, benchmarks like SWE-bench and tau-bench. For realistic environments, vendor test modes and cross-service sandboxes. Pick one per job that fits your stack.
This is a working map of the agent testing landscape, grouped by what each tool does. It is not exhaustive and it is not a ranking. Use it as a starting point, then pick the few tools that fit your stack.
Evaluation and testing frameworks
- LangSmith Tracing and evaluation from the LangChain team, tightly integrated with LangChain and LangGraph.
- Braintrust Evaluation, prompt playground, and dataset management for LLM products.
- Promptfoo Open-source, config-driven eval and red-teaming that runs well in CI.
- DeepEval Open-source unit-testing style framework for LLM outputs, with many built-in metrics.
- Ragas Metrics for retrieval-augmented generation and faithfulness.
- OpenAI Evals OpenAI's open framework for writing and running evals.
- Inspect Evaluation framework for agents from the UK AI Safety Institute.
- TruLens Open-source evaluation and tracking with feedback functions.
- MLflow LLM Evaluate General ML platform with LLM evaluation support.
Observability and tracing
- Langfuse Open-source tracing, evals, and prompt management for LLM apps.
- Arize Phoenix Open-source LLM observability and evaluation from Arize.
- Helicone Logging, monitoring, and cost tracking for LLM calls.
- W&B Weave Tracing and evaluation toolkit from Weights & Biases.
- OpenTelemetry GenAI conventions Vendor-neutral semantic conventions for recording GenAI activity.
- OpenLLMetry Open-source OpenTelemetry instrumentation for LLM frameworks.
Safety, red-teaming, and guardrails
- OWASP Top 10 for LLM Applications The standard catalog of security risks for LLM applications.
- garak Open-source vulnerability scanner for LLMs from NVIDIA.
- PyRIT Microsoft's Python risk identification toolkit for generative AI.
- Promptfoo red teaming Automated red-teaming built into Promptfoo.
- Guardrails AI Open-source framework for input and output validation.
- NeMo Guardrails NVIDIA's toolkit for programmable conversational guardrails.
- Purple Llama and Llama Guard Meta's safety tools including Llama Guard.
- Giskard Open-source scanning for quality and safety issues.
- Patronus AI Automated evaluation and safety testing platform.
- Galileo Evaluation and guardrailing platform for GenAI.
Benchmarks
- SWE-bench Real GitHub issues for evaluating coding agents.
- WebArena Realistic web environments for browser-using agents.
- tau-bench Tool use and dialogue in customer-service settings, with shared state.
- GAIA General assistant questions requiring multi-step reasoning.
- AgentBench A multi-environment benchmark for broad agent ability.
- Berkeley Function-Calling Leaderboard A leaderboard focused on function and tool-calling accuracy.
- ToolBench Tool-use evaluation across many real APIs.
Environments and sandboxes
- Arga Labs Hosted replicas of the external services an agent depends on, with shared state, for exercising an agent against production-like behavior.
- Stripe test mode and test cards Stripe's own test mode and test cards.
- Salesforce Developer Edition and scratch orgs Free Salesforce developer orgs and scratch orgs.
- HubSpot developer test accounts HubSpot developer test accounts.
Further reading
- Building effective agents Anthropic's guide to how effective agents are built.