safety medium complexity mvp
Agent Evaluation
Agent evaluation measures whether an agent chooses useful steps, calls tools safely, and reaches the goal under realistic conditions.
Decision
Add agent evaluation before expanding autonomy, tool access, or user-facing responsibility.
Use when
- Tool-using agents
- Research and operations assistants
- Multi-step workflows with uncertainty
- Regression testing agent changes
Avoid when
- Vague demos
- Tasks without observable success criteria
- Replacing product boundaries
- Measuring only final answer fluency
What agent evaluation measures
Agent evaluation looks beyond the final answer. It asks whether the agent chose the right steps, used the right tools, stopped at the right time, and recovered from failures.
For tool-using systems, the path matters as much as the output.
What to evaluate
Start with realistic tasks and inspect:
- tool selection
- argument quality
- recovery from failed tools
- stopping behavior
- unsafe or unnecessary actions
- final answer usefulness
Common mistakes
- Evaluating only the final response.
- Ignoring tool-call traces.
- Testing only happy paths.
- Expanding permissions before failures are understood.
Next decision
Use agent evaluation before adding broader tools, memory, or autonomy. If the agent cannot pass bounded tasks, keep the workflow in control.