Observability & Evals LangSmith Agent Evaluation Readiness Checklist
Implement the LangSmith evaluation checklist to ensure robust agent testing.
Implement the checklist steps in your agent development workflow.
Summary
The LangSmith Agent Evaluation Readiness Checklist provides a practical companion to the earlier article on agent observability. It outlines a step‑by‑step process for building, running, and shipping agent evaluations. The checklist emphasizes starting with simple end‑to‑end tests that give signal before adding complexity. It recommends manually reviewing 20‑50 real agent traces to surface failure patterns early.
Key items include defining unambiguous success criteria for a single task, separating capability and regression evaluations, and ensuring failures can be articulated. The checklist also stresses assigning ownership to a domain expert and ruling out infrastructure or data pipeline issues before blaming the agent. It advises choosing the appropriate evaluation level—single‑step, full‑turn, or multi‑turn—based on the agent’s behavior. Finally, it encourages a continuous flywheel from trace to dataset to experiments for ongoing improvement.
Key changes
- Use LangSmith to convert traces to annotation queue, datasets, and experiments.
- Manually review 20‑50 real agent traces before building eval infrastructure.
- Define unambiguous success criteria for a single task.
- Separate capability evaluations from regression evaluations.
- Ensure failures can be articulated and root causes identified.
- Assign eval ownership to a single domain expert.
- Rule out infrastructure or data pipeline issues before blaming the agent.
- Choose evaluation level: single‑step, full‑turn, or multi‑turn based on agent behavior.